Colorimetric Molecularly Imprinted Polymer-Based Sensors for Rapid Detection of Organic Compounds: A Review

Abstract

This review offers a comprehensive examination of the development and current state of the art in the field of molecularly imprinted polymer (MIP)-based colorimetric sensors, focusing on their potential for the rapid detection of organic compounds. These MIP-sensors are gaining considerable attention due to their distinctive capacity to modify sensor surfaces by creating recognition cavities within the polymer matrix, providing a versatile and highly selective platform for detecting a broad spectrum of analytes. This review systematically examines different types of MIP-based colorimetric sensors, attending to the target analyte, highlighting their applications in on-site sample detection, drug monitoring, environmental analysis, and food safety detection. The integration of novel technologies, such as nanozymes and smartphone-based detection, which enhance the capabilities of colorimetric MIP sensors, is also addressed. The sensors are particularly valuable due to their low cost, rapid response times, portability, and ease of use. Finally, the review outlines the future challenges for the development of MIP-based colorimetric sensors, focusing on overcoming existing limitations, improving sensor performance, and expanding their applications across various fields.

1. Introduction

In situ chemical analysis has emerged as a significant advancement in analytical chemistry, offering numerous advantages, such as reduced time and costs, and the ability to avoid sample alterations during transport and storage [1,2,3,4]. In this context, chemical sensors play an important role as devices designed to detect, measure, and monitor specific chemical compounds in a given environment, providing essential data for a wide range of scientific, industrial, medical, and environmental applications [5,6,7]. These sensors operate by interacting with a sensitive material, which generates a signal that can be interpreted to determine the concentration of the target compound. Their ability to detect analytes at minimal concentrations has led to widespread utilization in areas such as environmental monitoring, clinical diagnostics, food safety, and the pharmaceutical industry. As the demand for precise and reliable data in these fields increases, the development of highly selective sensors has become a research focal point.

Among chemical sensors, colorimetric sensors stand out for their simplicity and ease of use [8]. These sensors detect the presence of a target analyte by causing a color change in a sensing material, typically a chromogenic compound. This simplicity and cost-effectiveness make colorimetric sensors attractive for a variety of applications, from water quality monitoring to food safety tests [9,10,11,12,13,14,15,16]. However, one significant limitation of colorimetric sensors is that the color change can also be influenced by external factors such as pH, temperature, ionic strength, and, in particular, the presence of other compounds with similar optical properties [17]. This issue creates a challenge in terms of selectivity and specificity. In many cases, sensors need to distinguish between the target analyte and other substances with similar chemical structures, which may lead to cross-reactivity, especially in complex samples like biological or environmental ones. This lack of specificity [18] can hinder the performance of sensors, particularly in medical diagnostics, where precise measurements of low-concentration biomarkers are critical. As a result, the inability to differentiate between the target analyte and interfering substances often leads to false positives or negatives.

To address these challenges, significant advances have been made in the development of molecularly imprinted polymers (MIPs) [19,20]. MIPs are highly selective materials designed to recognize and bind specifically to target molecules by creating molecular cavities within their polymeric structure [21]. These cavities are generated through a polymerization process using the analyte as a template. Once the template is removed, the cavities remain, allowing the polymer to recognize and bind the analyte even at extremely low concentrations. This ability to “mimic” specific molecular interactions provides advantages over other recognition materials, such as antibodies or aptamers, which tend to be more expensive and have limited shelf lives [22]. Consequently, MIPs enable, to a certain extent, the use of highly specific molecular recognition in applications that were historically limited to biological sensors.

While MIPs have clear advantages, they also exhibit certain disadvantages when compared to biological sensors. Biological sensors are still widely used today [23,24] due to their unrivalled specificity and sensitivity, especially in medical and biochemical contexts. However, their high cost, difficulty of preservation, and poor stability under certain conditions [25] present important limitations. In contrast, MIPs exhibit exceptional stability under harsh conditions, lower production costs, and versatility in recognizing a wide variety of target molecules. These characteristics make MIPs an attractive option for applications requiring durability and reusability, although their specificity may not always match the molecular recognition capabilities of biological receptors [26].

The fabrication of chemical sensors based on MIPs takes advantage of these non-covalent interactions, such as hydrogen bonds, Van der Waals forces, electrostatic interactions, or hydrophobic interactions. This characteristic allows MIPs to detect a wide range of chemical compounds, including pharmaceuticals, pesticides, organic pollutants, and biomolecules [27,28,29]. Unlike traditional sensor technologies, such as electrochemical or optical sensors based on antibodies, MIPs do not depend on biological elements, making them less expensive, more stable, and easier to mass-produce. Advancements in MIP design and functionalization have enabled their integration into various sensing platforms, particularly colorimetric ones. The incorporation of MIPs into wearable sensors and smartphone-based sensor systems has significantly enhanced their practical applications. For instance, MIP-based sensors can offer accurate monitoring of specific biomarkers in bodily fluids or environmental pollutants, with the added benefit of high selectivity. Wearable devices incorporating MIPs can track critical health parameters, such as glucose or lactate levels in sweat or saliva, providing precise readings even in the presence of interfering substances. Similarly, smartphone sensors equipped with MIPs can enable real-time, on-site chemical analysis for applications ranging from environmental quality monitoring to personalized medical diagnostics [30,31].

In the field of MIP-based sensors, several reviews have been published in recent years, ranging from highly specialized to more general overviews. Generalist reviews, such as those by Nazim et al. [32] and Leibl et al. [33], provide broad insights into MIP-based analytical techniques, summarizing advancements in various methods, including electrochemical, chromatographic, mass spectrometry, and colorimetric approaches, thereby demonstrating the versatility of MIPs in analyte determination.

On the other hand, more specific reviews focus on distinct applications or detection methods. Ayerdurai et al. [34] and Kamel et al. [35] concentrated on MIP-based electrochemical sensors for food safety and chlorophenols detection in water, respectively. Liu and Co [36] reviewed recent design strategies, developments, and representative applications of luminescent MIP-based chemosensors. Wang et al. [37] systematically presented the preparation methods of MIP-based colorimetric sensors, focusing on substrates and MIP materials while providing examples of their applications in various fields. Karadurmus et al. [38] explored advancements in MIP sensors for explosives detection, emphasizing electrochemical, fluorescence, and chemiluminescence sensing techniques. Ostrovidov et al. [39] addressed MIP sensors for skeletal and cardiac muscle analytes, briefly mentioning colorimetric applications but largely focusing on other formats like impedimetric and potentiometric sensors. Zarejousheghani et al. [40] reviewed MIP sensors for Environmental Protection Agency (EPA) priority pollutants across diverse detection techniques, mentioning colorimetric approaches but only including two older examples of colorimetric sensors for the label-free detection of p-nitrophenol [41] and nitroaromatic molecules [42].

While generalist reviews provide a wide-ranging context and most of specific reviews focus on particular analytes or non-colorimetric detection methods, our review offers a detailed exploration of a specific detection technique: MIP-based colorimetric sensors. It also presents a comprehensive classification of these sensors by analyte type, systematically categorizing their applications in environmental, healthcare, and food analysis. In contrast to previous studies, the present work elucidates the underlying mechanisms of these colorimetric sensors and explores how advancements in the field, such as the integration of nanozymes and smartphone-based technologies, have further enhanced the sensors’ sensitivity, selectivity, and practicality.

In this work, we undertake a comprehensive review of the recent developments in molecularly imprinted polymer (MIP)-based colorimetric sensors for the detection of organic compounds over the past six years, emphasizing their applications and potential for addressing current challenges in chemical sensing. This review not only categorizes these sensors by analyte type but also provides a systematic exploration of their underlying mechanisms and technological advancements. Through this approach, we aim to highlight how MIP-based sensors are evolving and their growing impact across diverse fields, including environmental monitoring, medical diagnostics, and food safety.

2. Molecularly Imprinted Polymers (MIPs)

MIPs are synthetic materials designed to have specific recognition sites for a target molecule or a group of molecules. These recognition sites are created through a process known as molecular imprinting, where a template molecule (usually the target analyte) is “imprinted” into a polymer matrix. The process involves the polymerization of functional monomers in the presence of the template, which forms a three-dimensional network around the molecule. Once the template is removed, the resulting polymer retains cavities that are complementary in shape, size, and functional group arrangement to the template [21]. Scheme 1 shows a representation of the molecular imprinting process. In molecular imprinting, the extraction of the template from the imprinted polymer is a critical step, as some residual template may remain even after extensive washing, potentially causing later interferences. In such cases, a dummy template is used instead of the target analyte [43]. This is particularly necessary when the target is present in low concentrations, unstable, toxic, or susceptible to leakage due to incomplete template extraction or dissociation during polymerization.

The key feature of MIPs is their ability to selectively recognize and bind to the target analyte, even in the presence of other similar molecules. In the most used imprinting approach, established by Mosbach group [44], imprinting is based on the non-covalent bonding between the template and polymer network, and the MIP selectivity is due to the specific molecular interactions between the template molecule and the polymer matrix, such as hydrogen bonding, van der Waals forces, or ionic interactions. As a result, MIPs can be designed to bind a wide range of molecules, including small organic compounds, peptides, proteins, nucleic acids, and even larger biomolecules, making them valuable in various fields such as environmental monitoring, pharmaceutical analysis, and medical diagnostics [45,46,47,48]. One of the major advantages of MIPs is their robustness and stability. Unlike biological recognition elements such as antibodies or enzymes, MIPs are not prone to degradation or denaturation, which makes them ideal for use in harsh conditions, such as extreme pH, temperature, or solvent environments [49]. Additionally, MIPs can be synthesized by inexpensive monomers, making them cost-effective alternatives to traditional recognition elements. They are also highly customizable, allowing for the tailoring of their binding properties by selecting appropriate monomers and cross-linkers. In Figure 1, the chemical structures of some typical functional monomers used for the fabrication of MIP via non-covalent approach are presented.

Polymerization is typically carried out using one of the following methods [50]: (i) Bulk polymerization involves mixing the template, monomer, crosslinking agent, and initiator in a solvent and sealing it under vacuum for crosslinking. It offers simplicity and a single system but results in irregular shapes, complex post-processing, and difficulty in template elution [51,52]. (ii) Suspension polymerization disperses the organic phase with the components in a solvent, which is then stirred. This method yields uniform particle size and stable polymers but is complex and sensitive to material properties [53,54]. (iii) Precipitation polymerization creates molecularly imprinted microspheres (MIMs) by dissolving the template and components in a medium for polymerization. It is simple, with a large specific surface area, but requires large amounts of solvent and solvents with high viscosity [55,56]. (iv) Sol–gel method forms a gel from an inorganic precursor in the presence of the template. It offers mild operating conditions and good thermal and chemical stability, but the material is brittle and requires precise pH control [57,58]. (v) Electrochemical polymerization uses electrolysis to polymerize monomers on an electrode, offering simple equipment, adjustable structures, and uniform surface imprinting. However, electrode modification is necessary to enhance sensitivity [59,60].

MIPs have found widespread applications in a variety of sensing platforms, including electrochemical sensors [27,61] and optical chemosensors [62,63]. They are particularly attractive for use in sensor technology due to their high stability, low cost, and the ease with which they can be integrated into different sensor devices. Furthermore, MIPs are versatile in that they can be designed for both selective detection and sample enrichment, allowing for the isolation and identification of trace levels of analytes in complex samples. In recent years, the development of MIPs has extended beyond traditional applications to include more advanced fields such as drug delivery systems [64,65], tissue engineering [66], and diagnostic assays [67]. The continuous evolution of MIP-based technologies holds great promise for future applications in both fundamental research and industrial use, providing innovative solutions for molecular recognition and analysis.

The development of MIPs for chemical sensors requires careful consideration of the polymerization method as it could directly impact the sensor’s sensitivity, selectivity, and robustness. Different applications demand specific material properties, and the choice of polymerization technique must align with these requirements to ensure optimal performance.

Bulk polymerization remains a practical choice for applications where cost-effectiveness and high output are prioritized over fine structural control. For large-scale production, bulk polymerization offers simplicity and scalability, but its limitations in morphological control can hinder the uniformity and reproducibility of binding sites, which are critical for high precision analyte detection, especially for large molecules [26].

In contrast, applications that demand highly uniform particles, such as optical or fluorescence-based sensors, benefit from suspension polymerization. This polymerization technique enables the production of stable polymers with consistent particle sizes, ensuring homogeneity in sensor responses. Similarly, precipitation polymerization excels in creating monodisperse microspheres with large specific surface areas, a feature that enhances binding efficiency and analyte diffusion. These properties are particularly advantageous in biosensing and separation-based sensors, where reliable and reproducible performance is paramount [68].

Sensors designed for harsh environments, such as those used in environmental monitoring or industrial applications, often require materials with exceptional stability. The sol–gel method meets these demands by producing MIPs with high thermal and chemical resilience. Additionally, the porous structure inherent to sol–gel-derived materials facilitates rapid analyte diffusion, improving sensor response times [69]. However, the brittleness of sol–gel materials and the need for precise pH control during synthesis highlight the importance of tailoring the process to the specific application [70].

Wearable and portable chemical sensors, for which miniaturization and rapid response are essential characteristics, greatly benefit from electrochemical polymerization [71,72]. This technique enables the direct deposition of MIPs onto the electrode surfaces, ensuring strong adhesion and intimate contact between the polymer and the transducer. The ability to control the polymer structure through applied potential enhances reproducibility compared to other polymerization methods and allows for the precise adjustment of sensor characteristics, making it ideal for detecting trace analytes in complex matrices [73,74]. Furthermore, electropolymerization can be carried out under mild conditions, such as in aqueous media and at room temperature, which is particularly advantageous when imprinting biological molecules [75].

3. Colorimetric Sensors

Chemical sensors are devices designed to detect the presence and concentration of chemical substances in a sample by converting a chemical interaction into a measurable signal. According to the International Union of Pure and Applied Chemistry, a chemosensor is “a device that transforms chemical information, ranging from the concentration of a specific sample component to total composition analysis, into an analytically useful signal”. [76]. This definition underscores the essential role of the sensor in transducing chemical changes into quantitative data, which is fundamental for its use in a variety of real-time monitoring and analytical applications. These sensors play an important role in a wide range of applications, from environmental monitoring and industrial process control to medical diagnostics and food safety [77,78,79,80]. A basic chemical sensor consists of two main components: the sensitive element (receptor), which interacts with the target chemical species, and the transducer, which converts this interaction into a measurable output (typically an electrical signal) [81]. The output is then processed and analyzed to quantify the target analyte. Chemical sensors can be classified from several perspectives, including their principle of operation, their target analytes, and their application areas. Based on the type of transducer, chemosensors can be categorized as electrochemical, optical, piezoelectric, and calorimetric sensors [82] (Figure 2).

Optical sensors use light as the signal transduction method. An optical sensing system typically consists of a light source, a sensing platform, a light detector and a data processor [83]. They detect changes in light properties (such as absorbance, fluorescence, or reflectance) caused by interactions between light, and converting them into measurable signals relates to the concentration of the analyte. There are various types of optical sensors, each tailored to specific applications based on the type of light interaction and the measurement principle. Common types include absorption sensors, fluorescence sensors, and surface plasmon resonance (SPR) sensors [84]. Between these types of optical sensors, colorimetric sensors are particularly advantageous due to their simplicity and cost-effectiveness.

Colorimetric sensors operate primarily in the visible spectrum, making them less complex and more accessible for routine use. Furthermore, the visual nature of the response simplifies the analysis, enabling rapid, on-site measurements without the need for sophisticated instrumentation [85]. This makes colorimetric sensors particularly useful in environmental monitoring [86], clinical diagnostics [18], and field-based analysis [87], where ease of use and fast results are essential. Their ability to provide precise measurements based on clear color changes makes them a powerful tool in applications requiring rapid chemical detection.

3.1. Smartphone-Based Colorimetry

Smartphone-based colorimetry offers significant advantages due to the portability, cost-effectiveness, and accessibility of devices. Their compact design allows for field-based measurements, making them ideal for in situ data collection in remote areas or environments where specialized laboratory equipment is impractical. Additionally, the integration of high-resolution cameras enables precise color analysis, which, when combined with image processing software, supports both qualitative and quantitative assessments. This makes smartphones suitable for applications like food analysis, environmental monitoring, and diagnostics. Moreover, smartphones are equipped with a complete and integrated technological package including multiple built-in functionalities, such as GPS, internet connectivity, and voice recording [88]. These features facilitate the integration of location-based and contextual data, which can be especially valuable in environmental monitoring applications. Another plus is its great potential for citizen science as it allows the public to contribute to large-scale data collection efforts, such as environmental monitoring or pollution tracking [89].

Concentration levels are difficult to distinguish with the naked eye, so imaging processing software (Adobe Photoshop, Image J, etc.) is necessary to link quantified images data and analyte concentration [90] (Scheme 2). The accuracy of smartphone-based colorimetry can be influenced by factors like camera angle, sample distance, and ambient lighting, which may reduce its precision compared to specialized equipment [91]. However, with the use of specific algorithms, smartphone-based colorimetry offers a broader measurement range, with a comparable limit of detection, compared to absorbance-based models [92].

There are several color models or color spaces: RGB (red, green, and blue), CMYK (cyan, magenta, yellow, and black), HSV (hue, saturation, and value), and CIE (Commission Internationale de l’éclairage), etc., which are frequently used in digital image colorimetry. As previously indicated, one of the potential problems that can be encountered with a smartphone-based sensor is variations in illumination. For example, the RGB model exhibits heightened sensitivity to these variations in comparison to the CIE and HSV models and shows values dependent on the smartphone itself, thereby compromising its reliability, which makes the incorporation of image processing necessary to rectify the disparities among smartphones [93]. Martinez-Aviño et al. [94], in a smartphone-mini-spectrometer design, developed a color correction palette and a set of 45 colors with different groups to optimize color analysis in polymeric chemosensors (Scheme 3). The goal was to establish guidelines for selecting the appropriate setup for accurate measurements. The research found that using RGB coordinates, particularly when the sensor’s color tone was close to its complementary color, improved accuracy. A correction method was proposed to better approximate the true color, enhancing the reliability of sensor readings and image analysis.

Ongoing progress in smartphone technologies and mobile applications enables fast, cost-effective, and environmentally friendly analysis [95]. In recent years, smartphones have been increasingly utilized in various colorimetric sensors for assessing food quality [91,96,97], environmental monitoring [98,99,100], and clinical diagnosis [101,102,103], and some authors have developed or used smartphone applications for image processing and colorimetric sensing in the Android [88,104,105,106] and iOS [107,108] operating systems. Currently, the Photometrix app [109] is available for both Android and iOS and can be downloaded free of charge.

3.2. Nanozymes

Historically, various organic chromogenic molecules have been used as colorimetric sensors for detecting a wide range of analytes. Recently, the integration of nanostructured materials into colorimetric techniques has significantly advanced the field, driving both research progress and practical applications in colorimetric sensors. Nanozymes, which are nanomaterials that exhibit enzyme-like catalytic activity, have gained increasing attention due to their cost-effectiveness, high stability, good biocompatibility, and ease of modification. These properties make them suitable for a wide range of applications in environmental and food safety [110]. The analytical applications of nanozymes are particularly attractive, as using a catalytic agent for substrate detection provides an inherent amplification mechanism that enhances sensitivity in the identification of analytes [111].

Common classifications of nanozymes are typically based on their catalytic action and material composition (Figure 3). Based on catalytic activity, nanozymes are primarily classified into peroxidase (POD), oxidase (OXD), catalase (CAT), and superoxide dismutase (SOD) nanozymes [112], with the presence of multi-activity nanozymes also being noteworthy [113]. In terms of material composition, nanozymes can be categorized into metal-based, metal oxide-based, carbon-based, and other material-based nanozymes [114].

• Main nanozyme catalytic mechanisms

Nanozymes with peroxidase-like mechanism (POD) mimic the activity of natural peroxidases (PO) by catalyzing the breakdown of hydrogen peroxide (H₂O₂) in the presence of electron donors [115]. These nanozymes facilitate the oxidation of various organic and inorganic compounds, including substrates such as 3,3′,5,5′-tetramethylbenzidine (TMB), o-phenylenediamine (OPD), and 2,2′-azinobis [3-ethylbenzothiazoline-6-sulfonic acid] (ABTS). The catalytic activity of these nanozymes is based on a radical mechanism, which involves electron transfer and the formation of reactive-free radicals capable of reacting with substrates [116]. Various nanostructured materials, including carbon-based nanozymes, metal oxides, metals, and metal sulfides, have been found to exhibit peroxidase-like activity. For example, carbon-based nanozymes, which contain functional groups such as –C=O and –O=CO–, show excellent catalytic performance, whereas Fe₃O₄ nanoparticles operate through a ping-pong mechanism [117].

The oxidation of TMB by peroxidase-like nanozymes typically occurs in a two-step electron transfer process, with the formation of a TMB radical cation followed by the creation of a blue charge-transfer complex. This catalytic reaction generates colorimetric responses, as shown in Scheme 4, and the resulting oxidation products can be detected spectrophotometrically, forming the basis of various diagnostic and sensor applications [118,119,120,121].

Oxidase-like nanozymes (OXD) mimic the action of natural oxidases, catalyzing the oxidation of substrates in the presence of O₂. These reactions result in the formation H₂O₂ or water, depending on the specific catalytic process [122]. Unlike peroxidase nanozymes, which require H₂O₂ for their activity, oxidase nanozymes generate H₂O₂ in situ, which can then be used to oxidize a variety of substrates, often producing reactive oxygen species (ROS) such as singlet oxygen (¹O₂), hydroxyl radicals (•OH), and superoxide anions (O₂^•−). This wide range of ROS generated allows oxidase nanozymes to catalyze oxidation reactions with a broad substrate scope, but it also means that these nanozymes tend to lack the specificity found in other enzyme classes [123]. Oxidase nanozymes are useful in sensing applications where the colorimetric products formed upon oxidation can be easily detected. The absence of H₂O₂ in the reaction pathway offers an advantage as it avoids potential interference or instability issues. The colorimetric response of oxidized products has been used in several sensor systems [124,125].

The nanozymes presented below have been scarcely explored for the development of colorimetric chemical sensors [126]. Catalase (CAT)-like and superoxide dismutase (SOD)-like nanozymes have not received as much attention as other types, such as peroxidase (POD)-like or oxidase (OXD)-like nanozymes [104]. CAT-like nanozymes can catalyze the decomposition of H₂O₂ into molecular water and oxygen, whereas SOD-like nanozymes catalyze the dismutation of superoxide radicals (O₂^•−) into H₂O₂ and oxygen [127].

• Main nanozymes according to the composition material

The most common and straightforward classification of nanozymes based on their material composition divides them into four categories: metal-based, metal oxide-based, carbon-based, and other types. The “other types” category includes materials such as metal–organic frameworks (MOFs), covalent organic frameworks (COFs), and other specialized materials [114].

Metal- and metal oxide-based nanozymes could be classified into monometal, metal alloy, metal oxide, core–shell, and hybrid nanomaterials [128]. Monometallic nanozymes, typically noble metals, exhibit good chemical stability and excellent optical properties but can aggregate, leading to reduced catalytic activity [129]. The structure, size, and morphology of these nanozymes influence their catalytic properties [130]. Monometal nanozymes demonstrate various enzymatic activities, including oxidase (OXD), peroxidase (POD), catalase (CAT), and superoxide dismutase (SOD) activities. For instance, noble metal nanoparticles have been shown to promote the oxidation of substrates like TMB when exposed to H₂O₂ in acidic environments, with the reaction intermediate (O*) exhibiting POD activity instead of producing free radicals. Furthermore, under basic conditions, these nanozymes can facilitate the breakdown of H₂O₂ into water and oxygen, mimicking the behavior of catalase (CAT) enzymes [131]. Gold and silver nanoparticles (Au, AgNPs) have been widely utilized in the development of colorimetric sensing systems [132,133,134]. Manganese nanomaterials, including MnO₂, Mn₂O₃, and Mn₃O₄ exhibit notable oxidase-like catalytic activities and have been used in multiple colorimetric sensors [135,136]. In comparison to monometallic nanozymes, metal alloy nanozymes are more cost-effective and have been observed to have better performance in biocatalytic reactions [132].

Carbon-based nanozymes have emerged as a highly promising class of materials due to their enzyme-like catalytic properties, biocompatibility, low cost, and ease of modification. These nanozymes are derived from carbon nanomaterials, including allotropes such as graphene, carbon nanotubes (CNTs), carbon nanodots (C-dots), fullerenes, and amorphous carbon. The catalytic activities observed in these materials, such as POD-like, CAT-like, OXD-like, and SOD-like activities, are primarily attributed to their unique electronic structures and surface functional groups [137]. The presence of sp² hybridized carbon atoms, π-conjugation, and the ability to host metal ions in some carbon nanomaterials further enhances their catalytic potential. One of the key factors that influences the catalytic efficiency of carbon-based nanozymes is their morphology. Zero-dimensional (0D) carbon nanomaterials, such as fullerenes and graphene quantum dots (GQDs), possess high surface energy and a large surface-to-volume ratio, which increases their interaction with substrates and promotes faster diffusion of reactants and products. These properties are directly linked to the materials’ high specific surface area and porosity, which facilitate access to active catalytic sites. Additionally, carbon is a versatile element capable of forming stable covalent bonds with a wide range of atoms, enabling the formation of diverse molecular structures. This flexibility allows for the rational design of carbon-based nanozymes with tailored properties, making them suitable for various applications in colorimetric sensors [138,139,140]. Unlike traditional enzymes, carbon-based nanozymes lack specific substrate binding pockets, limiting their substrate specificity and catalytic selectivity. To overcome these limitations, there is a need for more sophisticated design strategies that can fine-tune the surface chemistry and electronic structure of these materials, thereby enhancing their catalytic performance and substrate recognition.

In recent years, MOFs and COFs have become leading platforms for the development and modification of nanozymes. These materials, composed of metal ions and organic ligands or nodes connected by bonds, offer advantages such as high surface area, tunable pore sizes, and modifiable functional sites. MOFs and COFs exhibit enzyme-like activity, often outperforming traditional nanozymes in terms of catalytic efficiency, selectivity, and reusability [141]. They can also be combined with other nanomaterials or biomolecules, forming multifunctional hybrid materials with unique properties. MOFs typically rely on metal centers for redox activity, with various metal-based MOFs (e.g., Fe, Cu, Ni) showing enzyme-like capabilities. COFs, on the other hand, derive their catalytic activity from bionic sites, π-conjugation, or metal-containing units, and are particularly useful in light-induced catalysis due to their high-density bionic sites. MOF-based nanozymes, especially Cu-based ones, have been widely explored for applications in oxidase activity and detection methods for substances like catechol. COF-based nanozymes generally exhibit lower catalytic activity, but their light-absorbent properties can enhance performance. MOFs and COFs have also been used for the colorimetric detection of several targets using both oxidase- [13,142] and peroxidase-like [143,144] mechanisms.

Recently, single-atom nanozymes (SANzymes) have emerged as a highly researched topic. Scheme 5 shows a representation of the synthesis process for Fe-N-C. The atomically dispersed metal active sites of SANzymes are similar to the active centers of natural metalloenzymes, which has led to high expectations with respect to their ability to enhance enzyme-like activities. Due to their maximum atom utilization efficiency and improved enzyme-like activity, SAzymes have garnered increasing attention in the scientific community, opening new possibilities for various catalytic applications [145].

However, challenges remain in integrating SANzymes into practical sensors, including issues of reproducibility, scalability, and stability. Addressing these challenges through improved synthesis and advanced encapsulation techniques will be essential for their successful large-scale application in fields like environmental monitoring, biomedical diagnostics, and industrial catalysis [146].

One of the main challenges in the development of nanozymes is improving their specificity for certain substrates. Unlike natural enzymes, which exhibit highly selective recognition of their substrates, nanozymes often lack the same level of selectivity. This limitation can impact the accuracy and reproducibility of results, particularly in diagnostic and sensing applications [147]. Therefore, improving substrate specificity is a crucial goal for enhancing the performance of nanozymes. To address this challenge, various strategies have been explored to enhance the selectivity of nanozymes [148]. One promising approach involves the combination of nanozymes with MIPs [149].

MIPs introduce highly specific molecular recognition sites that complement the catalytic activity of nanozymes, enabling more precise detection of target analytes. This integration not only improves substrate recognition but also enhances the overall performance of nanozyme-based systems. Recent studies have demonstrated that coating nanozymes with an MIP layer significantly enhances their selectivity, up to 100-fold in some cases, by creating specific binding pockets for the target analyte [150]. This modification allows the imprinted molecules to selectively access the catalytic core of the nanozyme while preventing other substrates from interfering with the reaction, thereby improving both specificity and catalytic performance. Such synergistic strategies effectively mimic the dual functionality of natural enzymes, where the apoenzyme determines substrate affinity and the coenzyme drives catalytic activity. By integrating MIPs as apoenzyme mimics, nanozymes achieve enhanced selectivity similar to natural enzymes [151].

Moreover, MIP-coated nanozymes have shown remarkable potential in addressing limitations associated with both materials. The molecular cavities in the MIP layer provide specificity, while the nanozyme core offers amplified catalytic activity, resulting in sensors with superior sensitivity, selectivity, and robustness [148]. This approach has already been applied successfully in several fields, such as environmental monitoring, and medical diagnostics [152,153]. The integration of tailored MIPs on nanozymes represents a novel and promising way for advancing this field further. This strategy expands the potential applications of nanozymes, particularly in complex sample matrices. In summary, the combination of nanozymes with MIPs addresses fundamental limitations in both materials, offering a pathway to highly selective, sensitive, and versatile sensing technologies [149].

While the integration of MIPs with nanozymes has significantly improved their specificity, real-world applications often face the challenge of interference from complex sample matrices, such as biological fluids, environmental samples, and food products. These interferences can arise from two primary sources. First, compounds structurally similar to the target analyte may compete for the recognition sites within the MIP layer, reducing the selectivity of the sensor. Second, non-specific interactions with abundant background compounds—unrelated to the target analyte—can lead to signal distortion or blockage of active sites. For example, proteins in serum or dissolved organic matter in environmental water samples may adsorb onto the sensor surface, complicating accurate detection.

To address these challenges, several strategies have been developed to mitigate interference and ensure reliable performance in complex matrices. One approach involves optimizing the design of MIPs to incorporate functional monomers that enhance selectivity for the target analyte, even in the presence of structurally similar interferents [154]. Additionally, experimental conditions such as pH, ionic strength, and temperature can be adjusted to promote specific interactions while minimizing non-specific adsorption. The use of blocking agents, such as surfactants or proteins like bovine serum albumin [67,155], further reduces the impact of non-specific binding by occupying sites susceptible to interference. Moreover, selective washing protocols can remove loosely bound interferents without affecting the sensor’s recognition capabilities.

These strategies, combined with the unique properties of MIPs, have demonstrated remarkable effectiveness in real-world scenarios, such as achieving high recovery rates (>90%) and low relative standard deviations (<5%) in complex samples like blood serum and environmental water [156,157].

4. MIP-Based Colorimetric Sensors

MIP-based colorimetric sensors represent a cutting-edge class of chemical sensors that utilize MIPs as the recognition element. MIPs are synthetic polymers that are designed with specific cavities or “imprints” designed to selectively bind target molecules, mimicking the high specificity of biological receptors. These cavities are created through a polymerization process in the presence of the target molecule (template), which is subsequently removed, leaving behind a binding site tailored to the shape and chemical properties of the analyte. In colorimetric sensor applications, MIPs are typically coupled with optical transducers to detect the presence or concentration of target analytes. MIP-based colorimetric sensors offer significant advantages over traditional sensing methods, including remarkable selectivity and sensitivity due to the high affinity of imprinted cavities for target molecules, enabling the detection of trace analytes in complex samples. They are highly stable under varying environmental conditions, cost-effective to produce, and reusable, making them ideal for harsh or field-based environments. These sensors can be tailored to detect a wide range of analytes, such as organic compounds, pharmaceuticals, toxins, and biomolecules, which make them versatile for applications in environmental monitoring, food safety, and biomedical diagnostics. Due to their combination of selectivity, stability, cost-efficiency, and reusability, MIP-based sensors are emerging as promising tools in molecular recognition and chemical sensing, with ongoing research aimed at enhancing their sensitivity and broadening their applicability in real-world scenarios.

4.1. MIP-Based Colorimetric Sensors Mechanisms

MIP-based colorimetric sensors utilize the specific recognition between a target analyte and pre-formed imprinted sites within a polymer matrix. The distinguishing characteristic of these sensors is their ability to induce a measurable color change upon analyte binding, which can be monitored with simple optical techniques such as UV–visible spectroscopy [147].

Direct monitoring of analyte binding: The simplest and most direct strategy involves monitoring the concentration of the analyte before and after interaction with the MIP. This method measures the change in the absorbance of the solution or the polymer itself when the analyte binds to the imprinted sites. The difference in concentration between the initial and post-rebinding concentrations corresponds to the amount of analyte bound to the MIP (Scheme 6). A notable advantage of this approach is that it does not require any modification of the analyte, relying instead on the analyte’s natural ability to absorb light at specific wavelengths. However, this method can be limited by the requirement for the analyte to possess a chromophore and potential interference from other spectroscopically active compounds in complex samples.

Chromogenic substrate reactions: A colorimetric detection strategy can also be based on the reaction of the analyte with a chromogenic substrate that changes color upon oxidation or other chemical interactions. In MIP-based colorimetric sensors, this is often achieved by using nanoparticles or other redox-active materials that mimic enzyme activity. For example, the interaction of the analyte with nanozymes can generate reactive oxygen species (e.g., hydroxyl radicals) that oxidize a colorless chromogenic substrate, leading to a visible color change. This method provides a straightforward, rapid means of detecting analytes, particularly in the presence of nanomaterials that can replace natural enzymes in these reactions. The aggregation of nanoparticles can result in a visible color change, which can be easily detected by the naked eye or through optical instruments.

Dye displacement assays: Another approach for colorimetric detection involves using a dye displacement assay. In this method, the imprinted polymer can be loaded with colored dye. Upon the binding of the analyte, the dye is displaced, resulting in a color change that can easily be quantified. This technique allows for highly specific and sensitive detection, even for analytes that do not inherently have chromophore groups and can be applied to complex mixtures without the need for extensive sample preparation.

4.2. MIP-Based Colorimetric Sensors by Target

MIP-based sensors can be classified in various ways depending on sensor design, material composition, and detection techniques. However, classifying these sensors based on the target analyte is particularly effective. This approach directly reflects the sensor’s application and the specific chemical or biological molecule it detects, making it easier to identify sensors tailored for fields like environmental monitoring, medical diagnostics, or food safety. By organizing sensors by their targets, it is possible to link their design features—such as recognition elements, binding sites, and chromophore choices—to the properties of the analyte. This classification provides a clear understanding of each sensor’s strengths and limitations in relation to its intended use. Additionally, a target-based classification helps researchers focus on the challenges of detecting specific analytes. Developing MIP sensors for small molecules, heavy metals, or pathogens requires unique considerations for molecular recognition, sensitivity, and stability. This method highlights trends and improvements for each target, promoting more efficient design strategies for future sensors.

In this section, we aim to categorize MIP-based colorimetric sensors according to the analyte they are designed to detect, providing a comprehensive overview of the current state of the field. This classification will help to elucidate the diverse capabilities of MIP sensors and their potential applications, while also highlighting the ongoing innovations in sensor development tailored to specific detection needs (Figure 4).

4.2.1. Pharmaceuticals

The analysis of pharmaceuticals, which includes drug quality control, metabolism analysis, and residue analysis, is increasingly important in scientific research and public health, being essential for ensuring safety and efficacy of drugs [158] and monitoring pharmaceutical contaminants in the environment for the protection of human and ecological health [159].

• Antibiotics

Antibiotic residues in the environment constitute a rising health concern, making their detection important for analytical chemists. Antimicrobial resistance is driven by pathogens that adapt to antibiotics, with environmental and biological contamination playing a key role. Recent food safety incidents have highlighted the need for improved monitoring of antibiotic residues and illegal additives [160,161,162].

Until 2019, the use of molecularly imprinted polymers (MIPs) for antibiotic determination was based primarily on the direct extraction of analytes from a solution. Lamaoui et al. [163] introduced a colorimetric method utilizing a magnetic MIP for the detection of sulfamethoxazole (SMX), a sulfonamide antibiotic used in both veterinary and human medicine. The method involved mixing a ferrofluid solution of Fe₃O₄ nanoparticles with a prepolymerization solution containing methacrylic acid (MAA), ethylene glycol dimethacrylate (EGDMA), and SMX as the template molecule. Polymerization was carried out using ultrasound and ammonium persulfate (APS) as the radical initiator. Spectrophotometric measurements at 538 nm were performed to determine SMX concentrations in the solution after the Bratton–Marshall reaction (diazotization of sulfonamides with sodium nitrite under acidic conditions) and subsequent MIP-SMX extraction. This method was applied to spiked real water samples, achieving a limit of detection (LOD) of 0.06 μg mL⁻¹, a working range of 0.2 to 5 μg mL⁻¹, and recovery rates between 83.0% and 95.4%. Three years later, the integration of innovative techniques into MIP-based colorimetric sensors that enhance speed, portability, accessibility, simplicity, and affordability, such as the use of paper-based analytical devices (PADs) and smartphones, enabled Lamaoui et al. [164] to create a colorimetric sensor for SMX. In their approach, a suspension of MIP specific to SMX was vacuum-immobilized onto the porous structure of hydrophobic paper PADs. The detection process involved depositing 20 μL of an SMX sample onto the MIP-PAD, where SMX binding occurred. Subsequently, reagents, including sodium nitrite (NaNO₂), hydrochloric acid (HCl), sulfamic acid, and naphthyl ethylenediamine dihydrochloride (NED), were sequentially added. The final addition of NED, a coupling agent, produced an immediate pink color. The colorimetric assay was then analyzed using both a UV–vis spectrophotometer at 540 nm and a smartphone equipped with ImageJ software. The smartphone-based measurement demonstrated a linear range of 0.5–10 ppm with a limit of detection (LOD) of 0.17 ppm. To assess the practical applicability of the method, SMX detection was performed on spiked tap and river water samples. Recovery rates for these real-world samples ranged from 100% to 104%, with a relative standard deviation (RSD) below 3.5%.

In 2021, Lowdon et al. [165] synthesized an MIP to perform a dye displacement assay for the colorimetric detection of amoxicillin in aqueous media. Using an emulsion polymerization process, they combined MAA, EGDMA, and azobisisobutyronitrile (AIBN) with amoxicillin as the template, under UV irradiation and stirring, to produce MIP particles measuring 8–10 μm. To develop the colorimetric sensor, the researchers tested various dyes (malachite green, crystal violet, and mordant orange 1) and selected mordant orange due to its easy displacement in the presence of amoxicillin. The absorbance measurement of the resulting solution at 385 nm allowed differentiation between high and low concentrations of amoxicillin. However, the lack of linearity in the response limited the sensor to qualitative applications, precluding its use for quantitative analysis.

The incorporation of nanomaterials with enzyme-like properties (nanozymes) enhances sensitivity in detection methods through catalytic activity. Liu et al. [166] developed a colorimetric assay for tetracycline (TC) detection by introducing molecularly imprinted sites onto the surface of Fe₃O₄ nanozymes. Dopamine, serving as both a functional monomer and crosslinking agent, was polymerized to form Fe₃O₄@MIP particles, using TC as the template. This structure provided numerous channels for substrates to access the Fe₃O₄ core, which exhibited peroxidase-like activity, catalyzing the oxidation of the colorless substrate TMB into a blue product. In the presence of TC, the MIP shell selectively captured the drug, partially blocking the substrate-accessible cavities and thereby inhibiting the catalytic reaction that produces the blue color. As the TC concentration increased, the blue color intensity visibly decreased. Absorbance measurements at 652 nm showed a linear detection range of 2–225 μM with an LOD of 0.4 μM. The method was validated in water samples, achieving recovery rates of 95–105%. Liu et al. 2023 [167] were able to develop a new sensor for the determination of tetracycline that improved the sensitivity of the previous one and avoided the use of H₂O₂. For this purpose, a Mn-based Prussian blue analog (Mn-PBA) was prepared and treated with NaOH to increase oxidase-like activity. Finally, the MIP was obtained following a surface molecular imprinting approach, using TC as the template and N-[3-(dimethylamino)propyl]methacrylamide (DMAPMA) and EGDMA as the monomer and crosslinker, respectively. The use of NaOH enhanced the catalytic capacity of Mn-PBA for the oxidation of TMB, which produces a strong UV–vis signal. As in the previous case, the presence of TC blocks the cavities of the MIP, masking the active sites of Mn-PBA and inhibiting TMB oxidation, leading to a corresponding decrease in color intensity (Scheme 7). By measuring the absorbance at 652 nm, the LOD and linear range values were significantly improved, achieving an LOD of 0.07 μM and a linear range of 0.2−200 μM.

Li et al. [168] developed an MIP colorimetric detection system for erythromycin (ERY) in river water and milk samples. Using similar principles, they synthesized molecularly imprinted modules by polymerizing MAA and EGDMA on modified Fe₃O₄ nanoparticles to produce ERY-imprinted nanozymes (ERY-MIPNs). These nanozymes utilized the selective recognition capability of the imprinted sites for ERY detection. To enable bicolor colorimetric detection of ERY at neutral pH, adenosine triphosphate (ATP) was incorporated as a cofactor. In the absence of ERY, hydrogen peroxide diffuses through the MIPN pores and reacts with the Fe₃O₄ core, catalyzing the oxidation of TMB to produce a blue color. When ERY is present, it binds specifically to the imprinted sites, blocking H₂O₂ access to Fe₃O₄ and preventing TMB oxidation. Rhodamine B was added as a secondary indicator for bicolor detection, providing a stable pinkish-purple background color. This creates a clear visual shift from blue to pinkish-purple, depending on TMB oxidation levels, enabling easy visual identification. The system was integrated with a smartphone-based platform for rapid and convenient color quantification through a mobile application. A strong linear relationship was observed between the red/blue (R/B) value of the samples and ERY concentration, with an LOD of 4.27 μM and a linear range of 15–135 μM. The method was validated on spiked real samples, achieving recovery rates between 95.57% and 103.20%.

Murugan et al. [169] prepared and incorporated to a sensing system a hybrid nanocomposite consisted of a nitro-doped carbon nanodots/polyaniline/molecularly imprinted polymer (N-CNDs/PAni/MIP) for the detection of ciprofloxacin (CIP) in lentic and tap waters. This nanocomposite functions as a fluorescence probe, emitting blue luminescence under UV light and displaying typical excitation-dependent emission properties. Additionally, it demonstrated strong peroxidase-like catalytic activity. When CIP was introduced into the N-CNDs/PAni/MIP/TMB/H₂O₂ system, the solution’s blue color diminished due to the reduction of blue ox-TMB to colorless TMB. The sensor achieved a detection limit of 3.5 nM for the colorimetric probe, with a linear detection range of 0.038–200 nM.

Yan et al. [170] focused on the detection of fluoroquinolone antibiotics and developed a light-activated nanozyme sensor array (TiO₂ NRs/CuO/rMIP) for the qualitative and quantitative detection of four fluoroquinolones, namely, enrofloxacin (ENR), levofloxacin (LEV), ciprofloxacin (CIP), and norfloxacin (NOR), in water. The nanozyme’s sensitivity was enhanced by regulating imprinted sites through photodeposition, surpassing the performance of traditional TiO₂ NRs/CuO/erMIP prepared by electropolymerization. Photodeposited CuO generated photoactive sites on TiO₂, while molecularly imprinted sites were anchored to these active sites using antibiotic templates. This alignment improved enzyme-like activity and detection performance through color variation when fluoroquinolones were present. By adjusting the types and ratios of templates, sensor arrays with distinct response signals for each fluoroquinolone were prepared. A smartphone-based RGB analysis system, combined with principal component analysis (PCA), allowed both qualitative and quantitative detection. The sensor array demonstrated a broad detection range (0.1–3000 μM) with high sensitivity, showing great potential for real-world antibiotic detection in water environments.

• Psychoactive Compounds and Stimulants

Monitoring the presence of psychoactive compounds and stimulants in biological fluids allows for the accurate diagnosis of drug use, whether for medical or illegal purposes, and ensures patient safety [171]. Recent advancements in non-invasive colorimetric sensor designs have significantly enhanced the ability to detect this type of drugs in biological samples, increasing their practical application in clinical and forensic settings.

Lowdon et al. [172] developed a simple and low-cost sensor based in an MIP dye displacement assay for the visual detection of amphetamine in urine samples. The synthesis of the MIP was carried out with MAA and EGDMA against amphetamine and several dyes were tested (crystal violet, basic blue, pararosaniline, mordant orange and phenol red), providing crystal violet the most specific binding towards the MIP. The dye displacement from the MIP when amphetamine is present follows a linear range between 0.01 and 0.20 mg mL⁻¹, with higher concentrations showing a reduced ability to displace the dye, and an LOD of 0.009 mg mL⁻¹. Since amphetamine concentrations in urine decrease rapidly in the following days to levels two or three orders of magnitude lower than the sensor’s detection capacity, the method would need to be optimized for regulatory drug abuse testing. However, it remains useful for semi-quantitative visual detection of unknown solid powder samples.

Akhoundian and Alizadeh [173] reported the first methamphetamine (MTM) colorimetric sensor based on MIP technology combined with ninhydrin, a reagent capable of distinguishing amine-containing drugs. The MIP was synthesized through precipitation polymerization of MAA, vinyl benzene (VB) and EGDMA in the presence of MTM as a template. In the presence of a sample, MTM adsorbed onto the polymer reacts with the ninhydrin reagent, resulting in a color change in the polymer that varies from pink to purple depending on the MTM concentration. A calibration curve was generated using images captured by a smartphone, which served as an optical signal processor. The RGB color codes were analyzed, with the green channel showing the highest sensitivity. It is crucial to note that both temperature and time significantly impact the color development in this method, necessitating strict control of these parameters. This method demonstrated the ability to quantitatively measure MTM concentrations ranging from 5 to 100 μM, with an LOD of 1.44 μM in urine samples. The same authors (2024) [174] designed an MIP-based colorimetric sensor for the qualitative and quantitative detection of ephedrine (EPD) in urine samples. The EPD-imprinted polymer was synthesized using the precipitation polymerization method with MAA and VB as monomers. This polymer was employed to fabricate an EPD colorimetric sensor utilizing carbon disulfide and Cu²⁺ as reagents, which are well-known for their ability to react with secondary amines to produce a color change through the formation of a dithiocarbamate–copper ion complex in alkaline medium. The calibration curve for varying EPD concentrations was constructed using images captured by a smartphone, analyzing the associated RGB data (Figure 5). This sensor platform demonstrated a relatively wide linear calibration range (1–100 μM) and a detection limit of 0.6 μM, offering an efficient, reliable, and user-friendly approach for EPD analysis in urine samples.

Using a substrate displacement approach, Lowdon et al. [175] conducted a rapid assay capable of detecting 2-methoxyphenidine (2-MXP) in powder mixtures at concentrations as low as 0.015 mg mL⁻¹. A malachite green displacement assay was developed, where the target analyte exhibits a higher affinity for the synthesized MIP than the dye, displacing it from the nanocavities of the receptor. This displacement results in a color change in the filtrate, observable to the naked eye. To facilitate this process, a low-cost drug identification kit was designed by embedding dye-loaded MIP particles into syringe filters. When a solution containing 2-MXP is passed through the syringe filter, intense coloration appears on the filter due to the binding of the target analyte to the MIP and the subsequent displacement of the dye into the filtrate. This provides a visual confirmation of successful immobilization.

Caffeine, widely recognized as a stimulant in coffee, tea, and energy drinks, also serves as an active component in various pharmaceuticals. It is commonly included in pain relief medications (frequently paired with aspirin or acetaminophen), as well as treatments for migraines and remedies for drowsiness or fatigue. With the aim of detecting caffeine in beverages, Deng et al. [176] carried out a colorimetric approach using silver nanoparticles (AgNPs) that was combined with pretreatment by magnetic molecularly imprinted polymer (MMIP). For the synthesis of MMIP, magnetic Fe₃O₄ nanoparticles, Fe₃O₄@mSiO₂ microspheres and vinyl-modified Fe₃O₄@mSiO₂ microspheres were prepared before mixing with MAA and EGDMA. The MMIP was employed to isolate and concentrate caffeine from samples such as Cola beverages and tea. Subsequently, AgNPs sensors enabled rapid semi-quantitative analysis visible to the naked eye and precise quantification through UV–vis spectrophotometry. Under optimal conditions, caffeine concentrations ranging from 0 to 30 mg L⁻¹ were tested, with the method relying on color changes from yellow to red in the solution. The approach allows for the rapid screening of caffeine levels ≥ 5 mg L⁻¹ by visual inspection and the accurate quantification of levels between 0.1 and 5 mg L⁻¹ at 393 nm using UV–vis spectroscopy.

• Analgesics and anti-inflammatory drugs

Analgesics and anti-inflammatory drugs, particularly non-steroidal ones, are among the most widely consumed pharmaceuticals. These compounds can be found in all ecosystems, with a particularly pronounced presence in aquatic ecosystems [177,178].

Hassan et al. [179] introduced a highly sensitive and selective colorimetric sensor combining nanozyme technology with polydopamine molecularly imprinted polymers (Fe₃O₄ @ MIP NPs) for the detection of antipyrine (ANT) and benzocaine (BEN) in pharmaceutical ear drops and spiked water samples. Fe₃O₄ nanoparticles acted as magnetic carriers and exhibited peroxidase-like catalytic activity, facilitating the colorimetric detection of the target drugs. Dopamine self-polymerization was employed to create specific MIPs, enhancing selectivity by inhibiting the nanozyme’s enzymatic activity upon drug binding. The system was based on the catalytic oxidation of o-phenylenediamine (OPD) in the presence of H₂O₂, producing a yellow color whose intensity varied with the drug concentration. As drug levels increased, the interaction with the MIP reduced the nanozyme’s enzymatic activity, leading to a diminished yellow coloration. Quantitative relationships were established between absorbance and concentrations of ANT (5.0–60.0 ng mL⁻¹, LOD: 1.405 ng mL⁻¹) and BEN (5.0–65.0 ng mL⁻¹, LOD: 0.658 ng mL⁻¹). Factors influencing the enzymatic reaction were optimized, achieving recoveries of 100.07% and 100.57% for ANT and BEN, respectively.

To address the potential health risks associated with ketoprofen (KP) in animal-derived foods, a selective and efficient colorimetric detection method was developed by integrating MIPs with Cu-doped Fe₃O₄ nanozymes (Fe₃O₄–Cu) by Su et al. [180]. The Fe₃O₄–Cu nanozymes, synthesized via a solvothermal process, exhibited enhanced peroxidase-like activity, enabling the oxidation of TMB to its blue oxidized form (OxTMB) in the presence of H₂O₂. Chitosan (CS) and glutaraldehyde were utilized as functional monomers and cross-linkers to fabricate MIPs@Fe₃O₄–Cu with abundant imprinted cavities. When KP was introduced, it was selectively captured within these imprinted cavities, effectively blocking the interaction between Fe₃O₄–Cu and the chromogenic substrate, thereby inhibiting the color change. The sensor demonstrated high selectivity for KP over structural analogs, with a linear detection range of 0.25–100 μM and an LOD of 0.073 μM. The colorimetric assay was utilized to measure KP levels in milk samples, achieving low relative standard deviations (0.47–4.09%) and excellent recovery rates (98.7–104%).

• Others

There are numerous other pharmaceuticals that might be present in distinct environmental compartments, or for which quantifiable blood levels are crucial for diagnosis and treatment monitoring, rendering the development of rapid and reliable detection methods highly advantageous [181].

Attallah et al. [182] presented an optimized method for determining the antiepileptic drug levetiracetam (LEV) in human plasma using a colorimetric assay. Fe₃O₄@MIP nanoparticles (NPs) were fabricated by coating Fe₃O₄ NPs with an MIP layer, leveraging surface imprinting and nanotechnology. The fabrication process involved synthesizing Fe₃O₄ NPs via wet chemical co-precipitation, followed by oleic acid modification to support silica coating with tetraethoxysilane (TEOS). The silica shell improved hydrophilicity, biocompatibility, and stability while enabling the addition of functional groups. A molecularly imprinted layer was formed using MAA as the monomer, EGDMA as the crosslinker and LEV as the template. The resulting Fe₃O₄@MIP NPs provided accessible recognition sites for LEV and could be magnetically separated, streamlining plasma clean-up. The colorimetric assay for LEV detection relied on Fe³⁺ reduction by the drug in the presence of K₃Fe(CN)₆, producing Fe²⁺, which then reacted under acidic conditions to form soluble Prussian blue. Absorbance was measured at 775 nm obtaining an LOD of 2.32 mg mL⁻¹. Recovery tests indicated that MI-MSPE achieved high recovery rates of 91.74–93.47% with the colorimetric assay, demonstrating minimal loss of LEV and excellent process efficiency.

Shen et al. [183] introduced a new colorimetric detection technique for thrombin, a blood enzyme relevant to the blood clotting process and a biomarker for blood-related disorders, by integrating two recognition mechanisms, namely, MIPs for template-specific binding and aptamers for high-affinity interactions. The MIP–aptamer–Fe₃O₄ NP system achieves exceptional selectivity for thrombin, outperforming methods relying on a single recognition element. This method used Fe₃O₄ nanoparticles (NPs) functionalized with surface MIPs and aptamers (MIP–aptamer–Fe₃O₄ NP). These NPs exhibit peroxidase-like catalytic activity, enabling a sensitive and specific assay for thrombin. When thrombin binds to the imprinted cavities of the MIP–aptamer–Fe₃O₄ NPs, the surface area available for catalytic activity decreases. This reduction, combined with the inhibitory effects of the thrombin’s reductive amino acids on the oxidation of TMB in the presence of H₂O₂, leads to a diminished color change, resulting in a light blue solution. The assay demonstrates a linear detection range from 108.1 pmol L⁻¹ to 2.7 × 10⁻⁵ mol L⁻¹ and a detection limit as low as 27.8 pmol L⁻¹.

Zhang et al. [184] described the development of a selective colorimetric sensor based on MIP-modified gold nanoparticles (AuNPs) integrated with silica dioxide (SiO₂) for the real-time detection of glutathione (GSH) in serum samples. The MIPs were synthesized directly onto the surface of SiO₂ using GSH as the template molecule, providing specific recognition sites for target detection. Subsequently, AuNPs were in situ synthesized on the surface of MIP-coated SiO₂, resulting in a composite material (AuNPs@MIP-SiO₂) with enhanced peroxidase-like activity and selectivity. The incorporation of hydrophilic SiO₂ into the composite served to stabilize and protect the AuNPs, reducing aggregation and improving catalytic efficiency. This system facilitated the catalysis of H₂O₂ into hydroxyl radicals (·OH), which oxidize TMB into a colored product. However, the presence of GSH inhibited the oxidation process, enabling its quantification. This platform enabled both visual detection through noticeable color changes and quantitative analysis by measuring absorbance at 652 nm. The developed sensor exhibited high sensitivity, detecting GSH in a linear range of 5–40 μM with a detection limit of 1.16 μM. Another version of a colorimetric sensor based on MIP for the detection of GSH was fabricated by Lu et al. [185]. In this case, a sandwich-structured composite nanozyme (NH₂-MIL-101(Fe)@Au@MIP) was developed by integrating MIPs, metal–organic frameworks (MOFs), and gold nanoparticles (AuNPs) to create a highly selective colorimetric sensor. The inner component, NH₂-MIL-101(Fe)@Au, combines the peroxidase-like catalytic activity of the MOF (NH₂-MIL-101(Fe)) with the surface plasmon resonance (SPR) effects of AuNPs, significantly enhancing its enzymatic performance. The outer layer, an MIP formed using oxidized glutathione as a dummy template with acrylamide (AM) as a functional monomer and EGDMA as crosslinker, provides highly specific binding sites, ensuring excellent selectivity for GSH detection. The ability of GSH to form strong Au–S bonds with AuNPs, inhibits the catalytic activity of NH₂-MIL-101(Fe)@Au, thereby reducing the oxidation of TMB to its colored products. The reduction in absorbance at 450 nm correlates with GSH concentration, enabling precise quantification. This sensor demonstrated a detection range of 1–50 μM with an LOD of 0.231 μM and was successfully validated in fetal bovine serum.

Tariq et al. [186] developed a novel enzyme-mimicking sensor by combining a porphyrin-based nanozyme, 5,10,15,20-tetrakis(4-hydroxyphenyl)-21H,23H-porphyrin (THPP), with MIPs to detect etoposide (ETO) selectively and cost-effectively. The THPP nanozyme provided predefined binding affinity and catalytic properties, while the MIPs enhanced the specificity through the formation of target-specific recognition cavities. Together, they formed a THPP@MIP interface capable of oxidizing TMB to a blue product in the absence of hydrogen peroxide. The presence of ETO inhibited this reaction by blocking access to catalytic sites, enabling detection. The THPP@MIP was imprinted on disposable cellulose paper using UV curing, creating a portable, low-cost sensor (Figure 6). This device achieved an LOD of 0.002 μg mL⁻¹ with a linear range of 0.005–10 μg mL⁻¹ and showed exceptional selectivity against other drugs. It successfully differentiated serum samples from lung cancer patients and healthy individuals, demonstrating its clinical potential. The cellulose paper-based sensor is portable, rapid (<10 min), easy to use, and ideal for point-of-care applications.

Table 1. MIP-based colorimetric sensors for the detection of pharmaceuticals.

Application	Analyte	Sample	LOD	Linear Range	Ref.
Environmental	Sulfamethoxazole	Water	0.06 μg mL−1	0.2–5 μg mL−1	[163]
	Sulfamethoxazole	River and tap water	0.17 μg mL−1	0.5–10 μg mL−1	[164]
	Amoxicillin	Aqueous media	Qualitative	-	[165]
	Tetracycline	Water	0.4 μM	2–225 μM	[166]
	Tetracycline	Water	0.07 μM	0.2–200 μM	[167]
	Ciprofloxacin	Lentic and tap water	3.5 nM	0.038–200 nM	[169]
	Fluoroquinolones	Water	-	0.1–3000 μM	[170]
Healthcare	Amphetamine	Urine	0.009 mg mL−1	0.01–0.20 mg mL−1	[172]
	Methamphetamine	Urine	1.44 μM	5–100 μM	[173]
	Ephedrine	Urine	0.6 μM	1–100 μM	[174]
	2-methoxyphenidine	Powder mixtures	0.015 mg mL−1	-	[175]
	Antipyrine and Benzocaine	Ear drops	1.405 ng mL−1 0.658 ng mL−1	5.0–60.0 ng mL−1 5.0–65.0 ng mL−1	[179]
	Levetiracetam	Human plasma	2.32 mg mL−1	-	[182]
	Thrombin	Blood	27.8 pmol L−1	108.1 pmol L−1–2.7 × 10−5 mol L−1	[183]
	Glutathione	Serum	1.16 μM	5–40 μM	[184]
	Glutathione	Bovine serum	0.231 μM	1–50 μM	[185]
	Etoposide	Serum	0.002 μg mL−1	0.005–10 μg mL−1	[186]
Foods	Erythromycin	Milk and river water	4.27 μM	15–135 μM	[168]
	Caffeine	Beverages	-	0.1–5 mg L−1	[176]
	Ketoprofen	Milk	0.073 μM	0.25–100 μM	[180]

summarizes the MIP-based colorimetric sensors fabricated for the detection of pharmaceuticals.

4.2.2. Pesticides

The use of pesticides is essential for food production, yet it increasingly threatens both human health and ecosystems. Pesticide residues in food and the environment raise significant concerns, as misuse and overuse can lead to toxic buildup and resistance in pests. Thus, ecological monitoring using advanced, cost-effective methods is vital to address pesticide residues and their impact [187,188].

Chlorpyrifos (CPF), a widely used organophosphate insecticide, is frequently detected in fruit juices, including apple juice. Feng et al. [189] fabricated a novel dual-sensor system combining MIPs with surface-enhanced Raman spectroscopy (SERS) and colorimetric analysis for the rapid and accurate detection of CPF in apple juice. MIPs were synthesized via bulk polymerization with MAA and EGDMA to selectively adsorb and separate CPF from apple juice samples. Silver nanoparticles served a dual role as both a colorimetric indicator and a SERS-active substrate. When CPF standards solutions from 1 to 5 mg L⁻¹ were added to freshly prepared AgNPs colloidal solutions the color darkened from yellow to brown. However, when the CPF concentration was further increased to 20 mg L⁻¹, the solution lost its color, turning colorless or light gray due to the extensive aggregation of AgNPs. The colorimetric method allowed for rapid screening and semi-quantification of CPF concentrations ≥ 5 mg L⁻¹ by visual observation, while UV–vis spectroscopy enabled more precise quantification of CPF in the range of 0.1–10 mg L⁻¹. For trace-level CPF detection (as low as 0.01 mg L⁻¹), SERS provided high sensitivity and accuracy, validated using principal component analysis (PCA) and partial least squares regression (PLSR) models (RMSEC = 0.0453; R² = 0.9885).

Ye et al. [190] devised a straightforward and cost-efficient colorimetric method to detect 3-Phenoxybenzaldehyde (3-PBD). A sol–gel process was used to deposit a layer of MIP onto nanoparticles of silica. 3-Aminopropyltriethoxysilane (APTES) and phenyltrimethoxysilane (PTES) were selected due to their capacity to interact with 3-PBD through hydrogen bonding and π-π stacking interactions. This dual functionality improves the affinity and absorption capacity of the synthetic MIPs compared to using a single functional monomer. The MIP-coated nanoparticles were used to detect 3-PBD by exploiting a color fading phenomenon resulting from the reduction of potassium permanganate. As 3-PBD was eluted from the MIPs, it caused the potassium permanganate solution to fade in color, and this change was monitored for detection. Under optimal conditions, the method demonstrated a linear concentration range for 3-PBD from 0.1 μg mL⁻¹ to 1 μg mL⁻¹, with a low detection limit of 0.052 μg mL⁻¹. The method was successfully applied to detect 3-PBD in real-world samples such as river water, fruit juice, and beverages, with recovery rates ranging from 90.0% to 98.9%, demonstrating the method’s potential for detecting pyrethroid pesticide residues.

Atrazine, a widely used herbicide, is a common chemical contaminant in agri-food products. Zhao et al. [191] developed a novel dual-chemosensor system that combined MIPs for selective extraction, a gold nanoparticle (AuNP)-based colorimetric assay for rapid detection, and surface-enhanced Raman spectroscopy (SERS) for precise quantification. Apple juice was used as a model to demonstrate the sensor’s capability. The MIPs (MAA + EGDMA) were synthesized to specifically extract atrazine from apple juice with high recovery rates (~93%) and were incorporated into a solid-phase extraction (SPE) system. AuNPs of three sizes (large, medium, and small) were synthesized and evaluated for their performance in the dual sensing system. Large AuNPs (43 nm) exhibited the highest sensitivity for the colorimetric assay, achieving an LOD of <0.01 mg L⁻¹, enabling rapid screening of atrazine by visual observation or UV–vis spectroscopy. The system allows for the detection of atrazine in apple juice within 25 min, including 20 min for MIPs-based extraction and 5 min for the colorimetric assay.

Amirzehni et al. [192] reported a novel and efficient colorimetric sensor for the on-site detection of dimethoate, a harmful organophosphate toxin, based on its inhibitory effect on the catalytic activity of cobalt-zinc bimetallic ZIF (CoZn ZIF). This bimetallic MOF exhibits superior catalytic performance compared to single-metal frameworks, enabling the oxidation of TMB in the presence of H₂O₂ to produce an intense blue color. The presence of dimethoate interferes with this reaction, reducing the blue color intensity in proportion to its concentration. To enhance the sensor’s specificity, an MIP layer was synthesized on the surface of the CoZn ZIF using dimethoate as the template molecule. This MIP-CoZn ZIF composite demonstrated exceptional selectivity and sensitivity, as the MIP layer selectively captured dimethoate molecules while maintaining the high catalytic activity of the CoZn ZIF. The sensor exhibited a linear detection range of 0.02–1.2 μM and an impressive detection limit of 5.6 nM. The sensor was validated through its application to fruit and agricultural wastewater samples, obtaining satisfactory results with recoveries of 96.13 to 101.71%.

Glyphosate is a commonly used herbicide which helps improve crop yield and quality. Despite its benefits, there are growing concerns about its potential impact on non-target ecosystems and human health. Sawetwong et al. [193] developed a novel three-dimensional microfluidic paper-based analytical device (3D-μPAD) for the colorimetric detection of glyphosate using an MIP embedded with Mn–ZnS quantum dots (Mn–ZnS QD-MIP). The glyphosate-MIP was prepared on the surface of Mn–ZnS QD using poly(N-isopropylacrylamide) (NIPAM) and N, N′-methylenebisacrylamide (MBA) as functional monomers, with glyphosate as the template molecule. When glyphosate binds to the surface cavities of Mn-ZnS QD, it inhibits ABTS oxidation by H₂O, producing a color change from dark green to light green, which correlates with the glyphosate concentration. Scheme 8 illustrates the preparation of Mn-doped ZnS quantum dot (Mn-Zs QD) nanoparticles and the synthesis of MIP-coated on the Mn-Zs QD surface (Mn-Zs QD-MIP). This sensor demonstrates high selectivity and sensitivity, with a detection limit of 0.002 μg mL⁻¹ and an operating range of 0.005–50 μg mL⁻¹. The device was successfully applied to determine glyphosate in whole grain samples, showing analytical recoveries in a range of 80.6–119.9%.

Carbaryl is a toxic compound that has been classified as a carcinogen [194]. Amatatongchai et al. [195] introduced a novel origami microfluidic paper-based sensor for colorimetric detection of carbaryl in fruit samples. In this study, MIP (MAA + EGDMA)-coated silica–platinum nanoparticles (MSNPtNPs@MIP) were utilized as the sensor’s catalyst for the oxidation of TMB by H₂O₂. Carbaryl selectively binds to the cavities on the MSNPtNPs surface, inhibiting the TMB oxidation and leading to a color change from dark blue to light blue, which is dependent on carbaryl concentration in the 3D-μPAD detection zone. The design of the origami 3D-μPAD assay can detect carbaryl in the dynamic range of 0.002–20.00 mg kg⁻¹, with an LOD of 1.5 ng g⁻¹.

Maleic hydrazide (MH) is a plant growth regulator, herbicide, and sprout inhibitor used to enhance the growth and quality of certain vegetables and fruits. However, due to its genotoxic and carcinogenic effects, it is important to analyze MH residues in food. Elfadil et al. [196] detailed a novel, portable analytical system for on-site MH detection, combining a Fe₃O₄ MMIP with a smartphone-based colorimetric assay. The MMIP was synthesized through rapid radical polymerization using microwave-assisted synthesis, significantly reducing the processing time to just 30 min. The colorimetric detection of MH was achieved using the immobilized Folin–Ciocalteu reagent (FCR) on a 96-well microplate, with a smartphone sensor providing sensitivity suitable for detecting MH at concentrations as low as 0.6 ppm, well below the maximum residue limits (5 ppm). The addition of maleic hydrazide (MH) to the FCR results in the oxidation of its hydroxyl groups, leading to the reduction of Mo and W ions. The reduction reaction in question is accompanied by a color change from yellow to blue. This color change is indicative of the formation of a complex between the reduced metal ions and the MH. The combined MMIP extraction and smartphone-based detection system demonstrated excellent performance when tested on food samples such as potatoes and carrots, with recovery rates ranging from 79% to 96%, high repeatability (RSD 4.5%, n = 10), and strong selectivity for MH.

Han et al. [197] developed a sensor capable of determining the concentration of 2,4-dichlorophenoxyacetic acid (2,4-D) in water samples in situ. The synthesis of the molecularly imprinted sensors (Zn/Co-MOF@MIPs) was carried out by surface imprinting, using APTES and TEOS as functional monomer and crosslinker, respectively, and bimetallic MOFs (Zn/Co-MOF) as support carriers and catalysts. The resulting 2-methylimidazole-ligand mediated Zn/Co-MOF@MIPs exhibited oxidase-like activity, catalyzing the oxidation of TMB to generate a blue-colored oxidized TMB even in the absence of H₂O₂. The molecularly imprinted layer on the Zn/Co-MOF nanosheets selectively recognized 2,4-D, which led to a reduction in the oxidase-like activity and a noticeable decrease in the blue color intensity. As the concentration of 2,4-D increased, the absorbance at 650 nm gradually decreased. This behavior was leveraged to establish a colorimetric method for the in situ determination of 2,4-D in environmental water samples with an LOD of 2.26 μM and a linear detection range from 6 to 45 μM. When applied to real water samples, the sensor demonstrated excellent recovery rates ranging from 96.5% to 101.5%.

Wang et al. [198] developed an MIP-based colorimetric sensor for the detection of the organophosphate pesticide phoxim, utilizing a manganese–nitrogen co-doped carbon nanozyme (Mn@NC) with peroxidase-like activity. The sensor works by catalyzing the oxidation of TMB in the presence of H₂O₂, resulting in the formation of a blue-colored product, oxidized TMB. This color change is directly proportional to the concentration of phoxim in the sample, allowing its detection through visual observation or absorbance measurement at 653 nm. The catalytic activity of the Mn@NC nanozyme is inhibited by acetylcholinesterase (AChE) and acetylthiocholine, which produce thiocholine, a reducing substance that interferes with the peroxidase-like activity of the nanozyme. However, the presence of phoxim restores the Mn@NC activity by inhibiting AChE, leading to a recovery of the colorimetric signal. This competitive inhibition mechanism allows the sensor to specifically detect phoxim. The sensor demonstrated high sensitivity, with an LOD of 1.27 ng mL⁻¹ and a good linear relationship between absorbance and phoxim concentration (5–1000 ng mL⁻¹). Practical application tests on fruit and vegetable samples showed recoveries between 95.00% and 107.93%, indicating that the sensor is suitable for monitoring pesticide residues in real samples.

Table 2. MIP-based colorimetric sensors for the detection of pesticides.

Application	Analyte	Sample	LOD	Linear Range	Ref.
Environmental	2,4-dichlorophenoxyacetic acid	Water	2.26 μM	6–45 μM	[197]
Foods	Chlorpyrifos	Apple juice	5 mg L−1	-	[189]
	3-Phenoxybenzaldehyde	Fruit juice, beverages and river water	0.052 μg mL−1	0.1 μg mL−1–1 μg mL−1	[190]
	Atrazine	Apple juice	0.01 mg L−1	-	[191]
	Dimethoate	Fruit	5.6 nM	0.02–1.2 μM	[192]
	Glyphosate	Whole grain	0.002 μg mL−1	0.005–50 μg mL−1	[193]
	Carbaryl	Fruit	1.5 ng g−1	0.002–20.00 mg kg−1	[195]
	Maleic hydrazide	Potatoes and carrots	0.6 ppm	-	[196]
	Phoxim	Fruit and vegetable	1.27 ng mL−1	5–1000 ng mL−1	[198]

summarizes the MIP-based colorimetric sensors fabricated for the detection of pesticides.

4.2.3. Toxins

Toxins are a major threat to food safety, causing severe health issues and economic losses globally. They can be introduced at any stage of the food production process, from harvesting to consumption, making the entire chain vulnerable to contamination [199].

Xiang et al. [200] developed a hybrid microfluidic device combining cloth and paper (μCPADs) for the rapid, on-site detection of gonyautoxin (GTX1/4), a marine algal toxin, using MIPs and MOFs. Guanosine was used as a dummy template for surface imprinting, allowing for the specific recognition of GTX1/4. The MOF@MIP composites, prepared with NH₂-MIL-101(Fe), facilitated a catalytic color reaction with hydrogen peroxide and TMB to detect GTX1/4. The sensing substrates, based on cloth, were assembled into 3D origami μPADs, forming user-friendly colorimetric devices. When combined with a smartphone, the μCPADs achieved a low detection limit of 0.65 μg L⁻¹, within the range of 1–200 μg L⁻¹, providing rapid visual detection of GTX1/4. The method demonstrated successful detection of GTX1/4 in real shellfish and seawater samples, with recoveries of 95.9–106.5% and a detection time of only 22 min.

Chen et al. [201] reported a colorimetric method for detecting total aflatoxins (AFs). This method utilizes the Emerson reaction and was used to detect AFs in peanut oil without specific antibodies. The sensitivity and selectivity of the method was improved by integrating colorimetric detection with MMIPs for solid-phase extraction.

MMIP-coated iron oxide (Fe₃O₄) nanospheres facilitated the extraction and rapid separation of AFs from the sample under an external magnetic field. The AFs solution was initially colorless and turned green when NaOH, 4-aminoantipyrine (4-AAP), and potassium ferricyanide are present, which could be quantified through UV–vis spectrophotometry or smartphone-based colorimetry, allowing for quantification. The smartphone method showed a detection range of 0.5–57 μg kg⁻¹, with a detection limit of 0.21 μg kg⁻¹. Another colorimetric MIP-based sensor for AFB1 was developed by Damphathik et al. [202] by integrating cerium MOF (Ce-MOF) with MIP (APTES + TEOS), resulting in a composite (Ce-MOF@MIP). The Ce-MOF component provides peroxidase-like activity, catalyzing the oxidation of TMB in the presence of hydrogen peroxide, while the MIP imparts specificity for AFB1 by having tailored binding cavities. The detection of AFB1 is achieved by observing the suppression of catalytic activity, resulting in a measurable colorimetric shift that can be analyzed using ImageJ software. The sensor demonstrates two distinct linear detection ranges (0.5–5 ng mL⁻¹ and 5–50 ng mL⁻¹) and achieves a detection limit of 0.25 ng mL⁻¹. In real-world applications, including peanuts, chicken feed, and corn, the sensor demonstrated recoveries ranging from 95.1% to 109.4%.

Wu et al. [203] reported a molecularly imprinted dual-mode magnetic sensor (MIDMs) for the sensitive and selective detection of saxitoxin (STX), a potent neurotoxin found in contaminated seafood. The sensor was based on Fe₃O₄ magnetic nanoparticles (MNPs) modified with Au-Pt nanozymes (MS@Au-Pt NZs), which were further functionalized with MIPs to specifically recognize STX. The MIPs were synthesized using STX as a template molecule, with 3-aminopropyltriethoxysilane as a functional monomer and tetraethyl orthosilicate as a crosslinker. These MIP-modified MS@Au-Pt NZs catalyzed the oxidation of TMB in the presence of hydrogen peroxide. When STX bound to the recognition cavity of MIP, it obstructed the catalytic site of the nanozyme, inhibiting the color development reaction, which could then be measured by Raman spectroscopy or colorimetry. The MIDMs sensor demonstrated a wide linear detection range (0.01 μM to 100 μM for colorimetry and 0.1 nM to 100 nM for Raman detection), with low limits of detection (3.1 nM for colorimetry and 0.03 nM for Raman). The method was successfully applied to real mussel and clam samples, achieving recovery rates of 78.0–96.2%.

Table 3. MIP-based colorimetric sensors for the detection of toxins.

Application	Analyte	Sample	LOD	Linear Range	Ref.
Environmental	Gonyautoxin	Shellfish and seawater	0.65 μg L−1	1–200 μg L−1	[200]
Foods	Aflatoxins	Peanut oil	0.21 μg kg−1	0.5–57 μg kg−1	[201]
	Aflatoxin B1	Peanut, chicken feed, and corn	0.25 ng mL−1	0.5–5 ng mL−1 and 5–50 ng mL−1	[202]
	Saxitoxin	Seafood	3.1 nM	0.01 μM–100 μM	[203]

summarizes the MIP-based colorimetric sensors fabricated for the detection of toxins.

4.2.4. Amino Acids and Proteins

The accurate detection and identification of biomolecules is of the utmost importance in the field of modern medical diagnostics [204]. In this area, colorimetric sensors are significant as reliable, precise, and affordable methods for the selective detection of amino acids [205].

Wang et al. [206] present a colorimetric paper-based sensor for detecting thyroglobulin (Tg) using MIPs prepared on hemin-graphene nanosheets (H-GNs). The fabrication process, involved preparing H-GNs via π-π interactions, which were then embedded into filter paper through filtration under negative pressure and heating at 60 °C. The H-GNs served multiple roles in the process: they enriched the template protein, initiated free-radical polymerization, and catalyzed the oxidation of TMB for colorimetric detection. The sensor exhibited a direct proportionality between the grey intensity of the sensor and the Tg concentration, ranging from 5 to 100 ng mL⁻¹. A novel methodology was proposed for the quantification of Tg levels in serum samples. This approach is characterized by its simplicity, rapidity, and cost-effectiveness, with a detection limit of 1 ng mL⁻¹ (15 fM).

Even at low concentrations (1 ng mL⁻¹), changes in grey intensity were observed, despite higher error. The intra- and inter-assay precision showed a coefficient of variation of <7.6%, and spiked recoveries ranged from 99.8% to 102.3%, with a relative standard deviation (RSD) of <7.8%. These results suggest that this sensor has significant potential for on-site detection of Tg, offering an accessible and efficient tool for medical diagnostics.

Xu et al. [207] introduced a rapid and sensitive colorimetric method for detecting ovalbumin (OVA), the main allergen in vaccines, using a sandwich detection strategy. The method combines Ni-Fe-MOF nanozymes and magnetic silicon dioxide surface molecularly imprinted particles (MSi-MIPs) to provide a good detection tool without the need for natural antibodies or enzymes. The ultra-thin Ni-Fe-MOF nanozyme, with a large surface area and numerous peroxidase active sites, enhances the sensitivity and stability of the assay. The MSi-MIPs are designed using surface molecular imprinting with boronic acid, enabling specific recognition of OVA. The sandwich structure consists of OVA, MSi-MIPs, and Ni-Fe-MOF nanozymes, which work together to amplify the colorimetric signal by catalyzing the oxidation of the substrate TMB to oxidized (oxTMB) (Scheme 9). The assay demonstrated a linear detection range from 2.5 to 25 ng mL⁻¹ and a low detection limit of 1.02 ng mL⁻¹, with results obtainable in just 20 min for the detection of OVA in vaccine samples.

Akhoundian et al. [208] developed a colorimetric sensing platform based on MIPs for the selective detection of proline, an essential amino acid and biomarker for various physiological conditions. The platform utilizes a proline-selective polymer synthesized through precipitation polymerization (MAA + EGDMA), which serves as the recognition element. The procedure began with the creation of a half-millimeter-deep square cavity in a glass slide. A blend of 2 milligrams of polymer and 4 milligrams of silicone adhesive was meticulously applied to the designated cavity, followed by the submergence of the slide in a proline solution, allowing proline to be extracted into the polymer. After washing, a reagent solution was prepared by dissolving 125 mg of ninhydrin in 3 mL of acetic acid and 2 mL of phosphoric acid (6 M). Proline’s reaction with the ninhydrin reagent resulted in a color change from white to pink, which could be quantified using RGB analysis through ImageJ software. The sensor demonstrated a wide detection range (0.5 to 700 μM) and a low detection limit (0.07 μM), with excellent selectivity against other amino acids. It was successfully applied to vegetable samples, offering a cost-effective, portable, and easy-to-use method for proline detection in complex samples.

Sarcosine (Sar) has emerged as a non-invasive biomarker for prostate cancer, making its precise detection significant for diagnostic purposes. Liu et al. [209] developed a highly selective colorimetric sensor for detecting Sarcosine (Sar) by integrating molecular imprinting sites directly onto the surface of Zn/Ce-based zeolitic imidazolate framework (Zn/Ce-ZIF) nanozymes. The Zn/Ce-ZIF nanozyme, composed of cerium as the catalytic element and ZIF-8 as the structural scaffold, demonstrates strong oxidase-like catalytic activity. MIPs (2-acrylamido-2-methyl propane sulfonic acid (AMPS) + 4-vinylpyridine (4-Vp)), were incorporated to selectively recognize and capture Sar, thereby modulating the colorimetric response through the inhibition of the TMB oxidation reaction. As the concentration of Sar increased, the color of the Zn/Ce-ZIF@MIP + TMB system gradually lightened. The sensor shows excellent selectivity and a low detection limit of 1.32 μM, with a wide range of 2 μM to 500 μM, offering a good method for Sar detection in simulated urine samples.

Table 4. MIP-based colorimetric sensors for the detection of amino acids and proteins.

Application	Analyte	Sample	LOD	Linear Range	Ref.
Healthcare	Thyroglobulin	Serum	1 ng mL−1	5–100 ng mL−1	[206]
	Ovalbumin	Vaccine	1.02 ng mL−1	2.5–25 ng mL−1	[207]
	Sarcosine	Urine	1.32 μM	2 μM–500 μM	[208]
Foods	Proline	Vegetable	0.07 μM	0.5–700 μM	[209]

summarizes the MIP-based colorimetric sensors fabricated for the detection of amino acids and proteins.

4.2.5. Colorants

Given the potential dangers that dyes cause to living organisms, it is very important to develop analytical methods capable of detecting dyes in various environments, including surface water, commercial formulations, industrial effluents, food, hair dyes, and other cosmetics [210].

Kuşçuoğlu et al. [211] and Kuşçuoğlu et al. [211] developed a low-cost, easy-to-use molecularly imprinted sensor for the colorimetric detection and quantification of basic red 9 (BR9), a model textile dye. The reversible addition–fragmentation chain transfer (RAFT) agent dithiobenzoate (CDB) and monomers (MAA + EGDMA) were used to carry out the graft polymerization on poly(ethylene terephthalate) (PET) surfaces with benzophenone (BP) functioning as photoinitiator. The PET grafted films was submerged in the sample solution and dried at room temperature prior taking smartphone images, whose color was analyzed by mathematical algorithm. The method demonstrated good performance for the detection and quantification of analytes with chromophores, suggesting its potential for a wide range of applications. The LOD and the linear range obtained were 1.9 μM and 1.9–173 μM, respectively. This MIP-colorimetric sensor was successfully applied to determine basic red 9 in spiked real tap and industrial wastewater samples.

Elfadil et al. [212] presents a sensing system for determining erythrosine B (ERT-B) in food samples. A composite of polydopamine-based molecularly imprinted polymers (PDA@MIP) coated on magnetic nanoparticles (Fe₃O₄) was synthesized and used for the magnetic dispersive solid-phase extraction (MDSPE) of ERT-B. After the MIP-MDSPE extraction of ERT-B, NaOH, as a desorption solvent, was added to elute the adsorbed ERT-B, and after magnetic separation, the supernatant was analyzed by smartphone-based colorimetric detection, offering comparable performance to UV–vis spectroscopy (Scheme 10). The developed strategy combined a sustainable and green synthesis approach for the Fe₃O₄@PDA@MIP composite, an effective extraction procedure (MIP-MDSPE), and straightforward, cost-effective smartphone-based detection. This smartphone method enabled the quantification of ERT-B, showing an LOD of 0.04 mg L⁻¹ and a linear range of 0.5–10 mg L⁻¹. This method yielded recovery rates ranging from 82% to 97% when applied to the analysis of ERT-B in food samples.

Malachite green (MG) is a toxic dye widely used in silk, jute, leather, paper, acrylic, and food industries [213] that has been reported to be carcinogenic and mutagenic [214]. Wang et al. [215] developed a colorimetric sensing system for MG in real water samples using magnetic (Fe₃O₄ NPs) MIPs (MAA + EGDMA) synthesized via surface imprinting. Following the adsorption of MG from the samples, the MIPs were magnetically separated, and the adsorbed MG was eluted to measure the absorbance at 620 nm in a colorimetric tube. This colorimetric method exhibited a good linearity (R² = 0.9982) in the concentration range of 0–60 μg L⁻¹ with an LOD of 1.1 μg L⁻¹.

Tartrazine (Tz) is a synthetic dye commonly used in food products such as dairy, beverages, and candies that must be regulated due to its potential risks to human health [216]. Jacinto et al. [217] synthesized an MIP using acrylamide and N,N′-methylenebisacrylamide (NMBA) to develop an MIP-colorimetric sensor for the determination of Tz. This process involves capturing images of MIP exposed to various tartrazine concentrations using a smartphone camera. The captured images are analyzed using Image-J software to extract red, green, and blue (RGB) color values, as well as hue, saturation, and value (HSV) parameters. Multivariate calibration, using partial least squares (PLS) regression, was employed to quantify tartrazine in carbonated beverages in the 0–30 mg L⁻¹ range, with an optimal working range of 0–20 mg L⁻¹ and a limit of detection (LOD) of 1.2 mg L⁻¹.

Table 5. MIP-based colorimetric sensors for the detection of colorants.

Application	Analyte	Sample	LOD	Linear Range	Ref.
Environmental	Basic red 9	Tap and industrial wastewater	1.9 μM	1.9–173 μM	[211]
	Malachite green	Water	1.1 μg L−1	0–60 μg L−1	[215]
Foods	Erythrosine B	Juice and candy	0.04 mg L−1	0.5–10 mg L−1	[212]
	Tartrazine	Soda	1.2 mg L−1	0–20 mg L−1	[217]

summarizes the MIP-based colorimetric sensors fabricated for the detection of colorants.

4.2.6. Other Compounds

Bisphenol A (BPA) is an industrial chemical used extensively in plastics and a prevalent environmental pollutant that causes serious risks to both the environment and human health. It is associated with various health issues, including reproductive problems, cancer, cardiovascular diseases, infertility, and mental health disorders. As a result, there has been considerable focus on detecting BPA to ensure food safety, protect environmental well-being, and safeguard human health for a sustainable future [218,219].

Kong et al. [220] developed a paper-based colorimetric sensor for detecting BPA leveraging the peroxidase-like activity of ZnFe₂O₄ magnetic nanoparticles and the properties of imprinted membranes. The membranes were synthesized using acrylamide as a functional monomer and BPA as a template by bulk polymerization. The sensor works by using the peroxidase-mimicking activity of ZnFe₂O₄ MNPs to catalyze a chromogenic reaction when TMB is present, leading to a visible color change. The intensity of the color is directly proportional to BPA concentrations, with a detection range from 10 nM to 1000 nM and a detection limit of 6.18 nM. The colorimetric changes, resulting from oxidation reactions, can be visually observed or quantified using software. El Hani et al. [221] created an MIP-colorimetric paper-based sensor (MIP-PAD) capable of quantify BPA by image software in water samples. The work involved synthesizing an MIP (MAA + EGDMA) with high affinity for BPA through radical polymerization in an ultrasonic bath. To prepare the MIP-PAD, a glass microfiber membrane was selected for its high porosity and filtration efficiency. The MIP layer was applied via vacuum filtration, followed by the drying and cutting of the membrane into small discs. A diazotized reagent mixture was added to each disc and dried. The MIP-PAD enabled rapid colorimetric detection of BPA, where adding a sample and phosphate buffer resulted in a yellow color, confirming successful BPA adsorption onto the MIP-PAD (Scheme 11). The MIP-PAD demonstrated high sensitivity with a detection limit of 0.03 μg mL⁻¹ and a quantification limit of 0.10 μg mL⁻¹ for BPA.

Yarynka et al. [222] developed a smartphone-compatible sensor based on MIPs for the detection of BPA in wastewater samples. The sensor utilizes MIP films made from ethylene glycol methacrylate phosphate (EGMP) that exhibit high porosity and selectively bind to BPA. The colorimetric detection method is based on the 4-aminoantipyrine reaction; BPA molecules adsorbed by the MIP film reacted with 4-aminoantipyrine, forming a pink color in alkaline conditions with potassium ferricyanide. The intensity of the pink color correlated with BPA concentration. The MIP film was wet, with a 2% 4-aminoantipyrine and 10% ammonium hydroxide mixture, followed by treatment with 2% potassium ferricyanide, resulting in pink staining. The staining intensity was quantified using a smartphone. The sensor demonstrated a wide detection range from 5 to 250 μM BPA, with a detection limit of 5 μM. When tested on real wastewater samples, the sensor yielded recovery values between 87.1% and 114.6%. Eldafil et al. [223] developed a sensing system for BPA using a molecularly imprinted (MAA + EGDMA) solid-phase extraction (MIP-SPE) coupled with a colorimetric assay. The MIPs were synthesized via photopolymerization and used as selective adsorbents in SPE columns. After MIP-SPE extraction of a sample containing BPA, an elution step with colorimetric reagents containing diazotizing solution, water, and buffer was used. The eluted solution corresponds proportionally to the BPA retained, and its yellow color can be precisely determined at a wavelength of 450 nm or using the smartphone with the blue color channel. The method provided a linear range from 0.25 to 8 mg L⁻¹, with an LOD of 0.144 mg L⁻¹.

Puerarin is an isoflavone used and prescribed in some countries. However, its metabolism remains poorly understood, and adverse reactions have been reported [224]. Guo et al. [152] reported a colorimetric sensor for puerarin detection based on the combination of MIPs and functionalized graphene composites with peroxidase-like activity. The graphene was functionalized with poly(styrene sulfonate) (PSS), onto which bimetallic nanoparticles composed of platinum and cooper were deposited to form the catalytic nanocomposite. This nanocomposite efficiently catalyzed the oxidation TMB in the presence of H₂O₂, mimicking peroxidase activity. This sensor demonstrated a linear detection range from 2 × 10⁻⁵ to 6 × 10⁻⁴ mol L⁻¹, with an LOD of 1 × 10⁻⁵ mol L⁻¹.

Acute myocardial infarction is one of the leading causes of death in cardiovascular diseases, with its diagnosis primarily depending on the detection of the cardiac biomarker troponin I (cTnI). Zhang et al. [225] presented a dual-mode electrochemical–colorimetric sensing strategy for the detection cTnI in serum. The sensor integrates an aptamer-functionalized Fe³⁺-polydopamine (Apt@Fe³⁺-PDA) construct as a self-sacrificial beacon and a MMIP to specifically recognize cTnI. Upon the binding of cTnI, the beacon forms a sandwich-like complex with the target, which, under acidic conditions, disintegrates and releases Fe³⁺, leading to the formation of Prussian blue (PB). This reaction enables two modes of detection. In the electrochemical mode, the presence of PB provides a sensitive response proportional to the amount of cTnI. In the colorimetric mode, the addition of K₃[Fe(CN)₆] to the PB produces different colors, allowing for visual detection (Scheme 12). The system exhibits a linear range for cTnI detection from 1.0 × 10⁻² to 1.0 × 10³ ng mL⁻¹, with detection limits of 3.2 and 7.4 pg mL⁻¹ for electrochemical and colorimetric modes, respectively.

Tetrabromobisphenol A (TBBPA) is a brominated flame retardant used in various consumer goods. It is known to disrupt endocrine function and has been widely detected in the environment because of industrial processes, as well as in human biological samples [226]. Zeng et al. [227] introduce a sol–gel method to create MIPs (APTES + TEOS) integrated with a copper-based MOF, HKUST-1, on paper substrates for the selective recognition of TBBPA. TBBPA recognition is coupled with its degradation under the presence of H₂O₂, which weakens the catalytic properties of HKUST-1 due to reduced imprinted cavities. As TBBPA is adsorbed and degraded, the catalytic oxidation of TMB results in less distinct coloration, which is used as an amplification strategy for the ultrasensitive, colorimetric detection of TBBPA. The method demonstrates a linear response in the concentration range of 0.01–10 ng g⁻¹, with a low LOD of 3 pg g⁻¹ and excellent selectivity, as blank intensities from TBBPA analogs are minimal (<1%). The spiked recovery rates ranged from 94.4% to 106.6%, with relative standard deviations under 8.6%. This technique is successfully applied to environmental dust extract samples, providing a reliable method for monitoring TBBPA exposure.

Aloe-emodin (AE) is a natural anthraquinone derivative found in plants like Cassia occidentalis, Rheum, Aloe vera, and Polygonum multiflorum Thunb. It has shown promising pharmacological properties, including antiviral, anti-inflammatory, antibacterial, immune-boosting, and anticancer effects. Due to its presence in various commercial formulations and bulk drugs, there is a growing need for reliable analytical methods to regularly monitor aloe-emodin content in these products [228]. Wang et al. [229] developed a dual-modal sensing system for the detection of AE using both electrochemical and colorimetric methods. This system involved the in situ hydrothermal synthesis of Fe₃O₄ micro-particles on exfoliated graphite paper (EGP), followed by the electropolymerization of pyrrole in the presence of AE to create an MIP film. In the colorimetric mode, the peroxidase-like activity of the Fe₃O₄ micro-particles catalyzed the oxidation of TMB in the presence of hydrogen peroxide, producing a deep blue color. However, when the AE molecules rebounded into the imprinted cavities, they blocked the Fe₃O₄’s catalytic activity, resulting in a lighter blue color, which was used for visual detection. The method was applied to real samples with recoveries of 99.4 to 106%.

Lysophosphatidic acid (LPA) is a signaling lipid mediator that is linked to ovarian cancer, making it a potential biomarker for early diagnosis. Tarannum et al. [230] developed an MIP-based colorimetric sensor for the detection of LPA. The method employs β-Ccclodextrin (β-CD) polymers imprinted with LPA as a template, enabling specific recognition of LPA in blood serum samples. The MIP selectively captures LPA through host–guest complexation, which is detected using a colorimetric assay based on enzymatic cycling. The assay is simple, specific, and highly sensitive, with a detection limit of 0.078 μmol L⁻¹ in spiked serum samples.

Enterovirus 71 (EV71) is a primary pathogen responsible for hand, foot, and mouth disease (HFMD). As EV71 can occasionally affect the central nervous system (CNS), leading to severe and life-threatening neurological complications, it has become a significant concern in pediatric infectious diseases, especially in the Asia–Pacific region [231]. Tang et al. [232] developed a a highly sensitive MIP dual sensor for detecting enterovirus 71 (EV71) utilizing an amplification strategy. The sensor combines magnetic particles coated with carbon quantum dots (Fe₃O₄@CDs) as carriers and fluorescent probes, along with aptamers to enhance virus recognition. The virus binds to the imprinted particles, causing fluorescence quenching. Signal amplification occurs when the aptamer-modified ZIF-8, loaded with phenolphthalein, binds to EV71 (Scheme 13). Upon adjusting the pH to 12, ZIF-8 disintegrates, releasing phenolphthalein and causing the solution to turn red, resulting in a second amplification of the signal. This dual-mode detection system offers both fluorescence and visual detection, with detection limits of 8.33 fM (fluorescence) and 2.08 pM (visual). The application of the sensor to the analysis of EV71 in human fluids (saliva and serum) resulted in a recovery range of 94.7–108.1%.

The purity of milk, once considered a symbol of health and nutrition, has been compromised by the troubling problem of melamine (MLM) contamination [233]. Dikici et al. [234] reported a colorimetric sensing system for detecting melamine in raw milk. The method utilizes melamine-imprinted polymeric membranes with 2-hydroxyethyl methacrylate (HEMA) as monomer and N,N′-methylenebisacrylamide (MBAm) as a crosslinker. The interaction between melamine and the membrane, marked by Fe³⁺ ions, causes a visible color change, which is directly correlated with melamine concentration. The color intensity of the membranes is easily analyzed using a smartphone application, ImageJ, for color analysis, making the method portable and efficient. Under optimal conditions, the LOD was 9.9 μM. The method showed a strong linear correlation (R² = 0.995) for melamine concentrations ranging from 10 μM to 50 μM.

Cholesterol plays a vital role in maintaining cellular structure and functions in the human body. It is essential for maintaining cell membrane integrity and serves as a precursor for the synthesis of important substances, such as steroid hormones, bile acids, and vitamins. However, both excessive and insufficient cholesterol levels can lead to severe health issues, making its regulation crucial. Cao et al. [235] developed a novel method for detecting cholesterol using an MIP-based colorimetric sensor (U₆NH₂@AuNPs-ChOx@MIPs) based on an amino-functionalized MOF (UiO-66-NH₂, or U₆NH₂). The sensor integrates gold nanoparticles (AuNPs) and cholesterol oxidase (ChOx) immobilized on the framework, along with MIPs that specifically recognize cholesterol. The process begins by removing cholesterol template molecules from the U₆NH₂@AuNPs-ChOx@MIPs surface, creating imprinted channels. Cholesterol molecules in the solution enter these channels and are catalytically reacted by cholesterol oxidase in the presence of oxygen, producing H₂O₂ and 4-cholesten-3-one. The H₂O₂ then catalyzes the production of •OH by U₆NH₂@AuNPs, which oxidizes TMB to blue oxTMB, generating a detectable signal. The fabricated sensor allows for efficient and selective cholesterol detection in blood samples using a simple colorimetric method. The detection range is between 2.9 mM and 6.7 mM, with an LOD of 2.4 mM, while the normal cholesterol level in blood should be below 5.18 mM.

Propyl gallate (PG), a common synthetic antioxidant used in edible oils, cookies, and fried foods, has raised significant concerns due to its potential toxic effects on human health [236]. Sarnaghi et al. [237] developed an MIP-based sensor for the detection of PG in n-propyl gallate (n-PG) in edible oils. The MIP (acrylamide + MAA) was synthesized on a cellulose substrate in the form of a thin film using the surface imprinting method. This MIP-based thin film served as an efficient smart sorbent for the selective extraction of n-PG through the microextraction by packed sorbent (MEPS) method. The extracted n-PG was then detected using digital image colorimetry (DIC), which provided a simple and fast colorimetric readout. The method was validated for natural sesame oil, achieving a linear dynamic range of 0.1–1 μg mL⁻¹, with a limit of detection and quantification of 0.03 and 0.1 μg mL⁻¹, respectively. The MIP-MEPS-DIC method demonstrated good performance for n-PG detection in various vegetable oils, including olive oil, coconut oil, and canola oil, with relative recoveries ranging from 83.0% to 108.6%.

Nhiem et al. [238] fabricated a novel glucose sensor based on glucose-imprinted polydopamine (PDA) and Fe₃O₄ nanoparticles (NPs), offering a user-friendly colorimetric detection method for glucose at micromolar concentrations. The creation of printed cavities on the surface of the polydopamine-coated Fe₃O₄ NPs was successfully executed. These cavities were key to the sensor’s glucose detection mechanism, as they facilitated a catalytic reaction where Fe₃O₄ NPs helped decompose hydrogen peroxide H₂O₂ to produce hydroxyl radicals (•OH). These radicals oxidized a colorimetric indicator, TMB, causing a visible color change from colorless to blue. When glucose molecules interacted with the imprinted cavities, the catalytic activity was reduced, leading to a corresponding change in color intensity that was directly proportional to the glucose concentration. The obtained LOD was 10 μM, much lower than usual concentration of glucose in human blood (3.9–5.6 mmol L⁻¹). The sensor’s performance was tested across a range of glucose concentrations from 10 μM to 0.01 M, with the color change being observable by the naked eye, making it ideal for use in non-laboratory settings. Vaidya et al. [239] developed a novel approach to glucose monitoring using MIPs (MAA + EGDMA) integrated into non-invasive sensor for the colorimetric detection of glucose in saliva, offering a promising alternative to traditional blood glucose monitoring. The sensor was developed on three different platforms, namely, cotton swabs, paper strips, and polymeric films, using a colorimetric assay to detect glucose. The MIPs were designed to specifically recognize and rebind glucose molecules, utilizing a semi-covalent imprinting method and colorimetric detection enabled by a TCS3200 RGB sensor interfaced with an Arduino Uno microcontroller. The sensor platforms demonstrated a low LOD of 0.9 mg dL⁻¹, with strong correlations (0.99–0.98) to blood glucose levels in diabetic patients. This suggests that the MIP-based sensors can offer highly accurate and rapid glucose detection from saliva, bypassing the discomfort and invasiveness of traditional glucose monitoring methods.

Table 6. MIP-based colorimetric sensors for the detection of other compounds.

Application	Analyte	Sample	LOD	Linear Range	Ref.
Environmental	Bisphenol A	-	6.18 nM	10 nM–1000 nM	[220]
	Bisphenol A	Water	0.03 μg mL−1	0.1 μg mL−1–5 μg mL−1	[221]
	Bisphenol A	Wastewater	5 μM	5–250 μM	[222]
	Tetrabromobisphenol A	Dust	3 pg g−1	0.01–10 ng g−1	[227]
	Aloe-emodin	Cassia seed and aloe	5.0 × 10−8 mol L−1–1.0 × 10−4 mol L−1	3.8 × 10−8 mol L−1	[229]
Healthcare	Puerarin	Plasma	1 × 10−5 mol L−1	2 × 10−5–6 × 10−4	[152]
	Troponin I	Serum	7.4 pg mL−1	1.0 × 10−2–1.0 × 103 ng mL−1	[225]
	Lysophosphatidic acid	Serum	0.078 μmol L−1	-	[230]
	Enterovirus 71	Serum	2.08 pM	-	[232]
	Cholesterol	Blood	5.18 mM	2.9 mM–6.7 mM	[235]
	Glucose	Blood	10 μM	10 μM–0.01 M	[238]
	Glucose	Saliva	0.9–3.9 mg dL−1	0.5–22 mg dL−1	[239]
Foods	Bisphenol A	Juice	0.144 mg L−1	0.25–8 mg L−1	[223]
	Melamine	Milk	9.9 μM	10 μM–50 μM	[234]
	Propyl gallate	Sesame oil	0.03 μg mL−1	0.1–1 μg mL−1	[237]

summarizes the MIP-based colorimetric sensors fabricated for the detection of other compounds.

5. Conclusions and Future Challenges

MIP-based colorimetric sensors have demonstrated significant potential in a variety of applications, including environmental monitoring, healthcare, and food safety, among others. These sensors offer a unique combination of high selectivity, ease of use, low cost, and rapid detection capability, which are key attributes for real-time and in situ analysis. Despite their promising advantages, several challenges must be addressed to enable their broader adoption and commercial scalability.

One of the primary obstacles in the development of MIP sensors is the complexity and time-consuming nature of their fabrication process. While these sensors exhibit excellent reproducibility, the complexity of their design and functionalization impede large-scale production. To address this, the development of automated manufacturing systems and standardized protocols is critical. Such advances would reduce costs and simplify production and scalability. Furthermore, microfabrication and nanofabrication techniques could facilitate miniaturization and batch processing, smoothing the way for compact, portable devices.

Another significant challenge lies in the detection of multiple analytes, which is often required in real-world applications involving complex matrices. Current MIP-colorimetric sensors are highly effective at targeting single analytes or groups of chemically similar compounds. To overcome this limitation, future research should focus on the following: (i) developing new MIPs capable of recognizing multiple analytes, potentially through the application of artificial intelligence (AI) to design and optimize these materials, and (ii) integrating multiple MIPs into a single-sensor platform. In this regard, the integration of MIP sensors with microfluidic systems presents a promising pathway, enabling the simultaneous detection of diverse analytes within a single device.

Emerging technologies, such as nanozymes and smartphone-based detection systems, present new opportunities for advancing MIP-colorimetric sensors. Nanozymes, which emulate natural enzyme activity, exhibit enhanced chemical stability and catalytic efficiency but often lack specificity for specific substrates. By integrating nanozymes with MIPs, it is possible to enhance substrate recognition, catalytic activity, and overall sensor sensitivity. This synergy holds promise for applications requiring extreme low detection limits in challenging environments, such as biomedical diagnostics or environmental monitoring. However, fully leveraging these advanced technologies requires addressing reproducibility, scalability, and specificity challenges. Strategies to improve the selectivity of nanozymes and ensure the long-term stability of integrated sensors are particularly important.

Finally, the application of AI to MIP research holds transformative potential. AI could predict optimal monomers, simplifying MIP synthesis processes, and identify conditions to improve both sensor performance and production efficiency. Employing AI-based approaches could significantly accelerate the development of next-generation MIP sensors, bridging the gap between laboratory innovation and commercial viability.

By addressing these challenges, MIP-based colorimetric sensors can continue to evolve into powerful and versatile tools for real-world applications, unlocking their full potential for both research and industry.