Search Results (23)

Introduction: Drug development has traditionally used mathematical models to predict formulation behavior. Objective: Building artificial neural networks for the drug release evaluation of drug delivery systems using sustained-release metronidazole-coated colonic hydrophilic matrices as a model. Methods: The technological factors associated with the biopharmaceutical performance of hydrophilic metronidazole matrices were evaluated using a quality by design approach (QbD). The developed neural network includes variables related to the technological process for producing the matrices. These are related to the materials used, such as the type and viscosity of core polymers, the type of coating agent, or the matrix production process, such as the mixing time of core materials or the percentage of the coating agent. The output variables of the neural network were the percentages of drug released in vitro at 1, 6, 12, and 24 h and the mean dissolution time of the matrix. An iterative quasi-Newton method was used to train the artificial neural network. Results: A neural network with excellent prediction capacity allows selecting the technological variables with the greatest influence on the % of drug dissolved: the type of coating agent used and the percentage of the total weight increase after coating for 1 h and 6 h of drug release and also the viscosity of the HPMC for 12 and 24 h. Conclusions: The optimized neural network demonstrated an excellent predictive capacity for in vitro drug dissolution profiles, allowing the use of this type of methodology based on artificial intelligence methods in the optimization of drug delivery systems. Full article

The design and development of a robust and consistent manufacturing process for monoclonal antibodies (mAbs), augmented by advanced process analytics capabilities, is a key current focus area in the pharmaceutical industry. In this work, we describe the development and operationalization of multivariate statistical process monitoring (MSPM), a data-driven modelling approach, to monitor biopharmaceutical manufacturing processes. This approach helps in understanding the correlations between the various variables and is used for the detection of the deviations and anomalies that may indicate abnormalities or changes in the process compared to the historical dataspace. Therefore, MSPM enables early fault detection with a scope for preventative intervention and corrective actions. In this work, we will additionally cover the value of in silico data in the development of MSPM models, principal component analysis (PCA), and batch modelling methods, as well as refining and validating the models in real time. Full article

Lipopolysaccharides (LPS) from Gram-negative bacteria represent a significant challenge across various industries due to their prevalence and pathogenicity and the limitations of existing detection methods. Traditional approaches, such as the rabbit pyrogen test (RPT) and the Limulus Amebocyte Lysate (LAL) assay, have served as gold standards for endotoxin detection. However, these methods are constrained by high costs, lengthy processing times, environmental concerns, and the need for significant reagent volumes, which limit their scalability and application in resource-limited settings. In this study, we introduce an innovative microfluidic platform that integrates the LAL assay within microdroplets, addressing the critical limitations of traditional techniques. By leveraging the precise fluid control and reaction isolation offered by microdroplet technology, the system reduces reagent consumption, enhances sensitivity, and enables high-throughput analysis. Calibration tests were performed to validate the platform’s ability to detect LPS, using colorimetric measurements. Results demonstrated comparable or improved performance relative to traditional systems, achieving lower detection limits and greater accuracy. This work demonstrates a proof-of-concept miniaturisation of the pharmacopoeial LAL assay. The method yielded low intra-assay variability (σ ≈ 0.002 OD; CV ≈ 0.9% over n = 50 droplets per point) and a LOD estimated from calibration statistics after path-length normalisation. Broader adoption will require additional comparative validation and standardisation. This scalable, cost-effective, and environmentally sustainable approach offers a practical solution for endotoxin detection in clinical diagnostics, biopharmaceutical production, and environmental monitoring. The proposed technology paves the way for advanced LPS detection methods that meet stringent safety standards while improving efficiency, affordability, and adaptability for diverse applications. Full article

The agro-industrial sector is a key pillar of the global economy, playing a central role in the supply of food, energy, and industrial inputs. However, its production chain generates significant amounts of residues and by-products, which, if not properly managed, may cause considerable environmental impacts. In this context, the search for alternatives to reuse these materials is essential, particularly when they can be converted into high-value products. One promising application is their use as a nutrient source for microorganisms in high-value biotechnological processes, such as the production of L-Asparaginase, an important enzyme used both in mitigating acrylamide formation in foods and as a biopharmaceutical in Acute Lymphoblastic Leukemia therapy. This approach offers a sustainable and competitive pathway, combining robust, scalable, and economical enzyme production with waste valorization and circular economy benefits. Although interest in developing more sustainable processes is growing, supported by international agreements and strategies for the valorization of agricultural residues, important challenges remain. The variability and impurity of residues pose significant challenges for producing biological products for the pharmaceutical and food industries. In addition, meeting regulatory requirements is essential to ensure product safety and traceability, while achieving high yields is crucial to maintain production viability compared to conventional media. Overcoming these barriers is critical to enable industrial-scale application of this approach. This review provides a residue-centered revision of the most relevant agro-industrial by-products used as substrates for L-asparaginase production, systematically comparing their compositional characteristics, fermentation strategies, and reported yields. Additionally, we present a novel SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis that critically examines the technical, regulatory, and economic challenges of implementing residue-based processes on an industrial scale. Full article

Background: Poloxamers are promising biomaterials for drug delivery applications due to their ability to enhance biopharmaceutical properties. Methods: This study focused on designing solid dispersions of ivermectin using poloxamer 407 by the fusion method and evaluating how variables of synthesis affect the polymer’s behavior and the resulting biopharmaceutical properties of ivermectin. Poloxamer 407 was selected based on a solubility test of preformulation studies. Initially, eight formulations were developed using different synthesis conditions, including polymer proportion, cooling gradient, and final process temperature. These were assessed by several characterization studies. Finally, saturation solubility dissolution profiles and in vitro drug release were also evaluated. Results: A combination of techniques confirmed the compatibility between poloxamer 407 and ivermectin in the solid dispersions. The rate of temperature in the cooling process of synthesis showed a significant impact on the polymer self-assembly, affecting their ability to entrap ivermectin. The optimized solid dispersion comprised ivermectin and poloxamer 407 in a 1:1 w/w ratio prepared by rapid cooling. This decrease in the crystallinity index and the nanometric size of particles of the solid dispersions could explain their ability to improve 1600-fold the aqueous solubility, as well as enhance the drug dissolution and in vitro drug release compared to pure ivermectin. Conclusions: Therefore, it follows that these poloxamer-based solid dispersions are promising alternatives to improve the bioavailability of ivermectin. Full article

Saccharomyces cerevisiae var. boulardii is a probiotic yeast widely recognized for its ability to enhance gut health and modulate a host’s microbiome. However, there are limited data on its large-scale cultivation in stirred tank bioreactors and subsequent downstream processing into a functional probiotic product. Different recipe formulations were evaluated and the recipe with the highest biomass yield and lowest process time was selected. Once the optimised batch was validated in the replicate batches, the statistical analysis indicated a high level of reproducibility, with low variability across key performance indicators such as biomass concentration (unit), CFU production (CFU.mL⁻¹), and substrate utilization efficiency (g.g⁻¹). The mean growth age in the bioreactor was 25.33 ± 1.16 h, with a CV of 4.56%, indicating minimal deviation between batches. Similarly, the final viable concentration exhibited a mean of 1.46 × 10⁸ CFU.mL⁻¹ with a CV of 11.68%, remaining within an acceptable range for biological processes, while the final biomass concentration had the lowest variability (CV of 3.94%) and a 95% CI of 12.134–13.266 g.L⁻¹, highlighting the accuracy and consistency of the process. Productivity indicators, including cell productivity (growth time—biomass) and YPP (biomass), maintained low CV values (3.933% and 3.389%, respectively), reinforcing process efficiency and stability. The overlapping 95% confidence intervals across batches further confirmed that no statistically significant deviations existed, ensuring minimal batch-to-batch variability, and validating the scalability and robustness of the fermentation process. These findings provide strong evidence for the feasibility of large-scale probiotic yeast production that meets industrial production standards. The final freeze-dried product retained an 81% viability post-exposure to simulated gastrointestinal conditions, meeting WHO probiotic viability standards. These findings establish a scalable, optimized process for probiotic yeast production, with potential applications in biopharmaceutical manufacturing and functional food development, as confirmed by the techno-economic evaluations performed using SuperPro Designer^®. Full article

Determining process variances in biopharmaceutical manufacturing is challenging due to limited data availability. To address this, we introduce a Bayesian hierarchical model designed for meta-analysis of process variance. This approach can improve process variance estimation by integrating data from multiple products, providing more reliable estimates of critical quality attributes in cases of data scarcity. Additionally, our model aids in evaluating process models, ensuring quality in process development. The paper demonstrates the new method using a simulation study, showcasing its potential to leverage historical data for both upstream and downstream phases of future CMC drug development. The new statistical model has great potential to expedite the market introduction of therapies while ensuring patient safety, allowing new treatments to reach patients more quickly without compromising quality or efficacy. Full article

The creation of products with personalized or innovative features in the pharmaceutical sector by using innovative technologies such as three-dimensional (3D) printing is particularly noteworthy, especially in the realm of compounding pharmacies. In this work, 3D printed capsule devices (CDs) with different wall thicknesses (0.2, 0.3, 0.4, 0.6, and 0.9 mm) and sizes were designed and successfully fabricated varying printing parameters such as extrusion temperature, printing speed, material flow percent, and nozzle diameter. The physicochemical, pharmaceutical, and biopharmaceutical performance of these CDs was evaluated with the aim of achieving an immediate drug release profile comparable to hard gelatin capsules (HGC) for use in magistral compounding. It was observed that the disintegration time of the CDs increased with wall thickness, which correlated with a slower drug release rate. CDs with configurations presenting 0.4 mm wall thickness and sizes comparable to HGC n° 0, 1, and 2 demonstrated satisfactory weight uniformity, short disintegration times, and immediate drug release, indicating their potential as effective devices in future compounding pharmacy applications. In addition, a modified Weibull-type model was proposed that incorporates wall thickness as a new variable in predicting dissolution profiles. This model improves the process of selecting a specific wall thickness to achieve the desired dissolution rate within a specified time frame. Full article

This research aimed to develop miconazole-based microemulsions using oleic acid as a natural lipophilic phase and a stabilizer mixture comprising Tween 20 and PEG 400 to solubilize miconazole as an antifungal agent known for its activity in oral candidiasis and to improve its bioavailability. The formulation and preparation process was combined with a mathematical approach using a 2³-full factorial plan. Fluid and gel-like microemulsions were obtained and analyzed considering pH, conductivity, and refractive index, followed by extensive analyses focused on droplet size, zeta potential, rheological behavior, and goniometry. In vitro release tests were performed to assess their biopharmaceutical characteristics. Independent variables coded X₁-Oleic acid (%, w/w), X₂-Tween 20 (%, w/w), and X₃-PEG 400 (%, w/w) were analyzed in relationship with three main outputs like mean droplet size, work of adhesion, and diffusion coefficient by combining statistical tools with response surface methodology. The microemulsion containing miconazole base–2%, oleic acid–5%, Tween 20–40%, PEG 400–20%, and water–33% exhibited a mean droplet size of 119.6 nm, a work of adhesion of 71.98 mN/m, a diffusion coefficient of 2.11·10⁻⁵ cm²/s, and together with remarked attributes of two gel-like systems formulated with higher oil concentrations, modeled the final optimization step of microemulsions as potential systems for buccal delivery. Full article

In the evolving landscape of sustainable biopharmaceutical process development, the utilization of bacteria in the production of various compounds via fermentation has attracted extensive attention from scientists. A successful fermentation process and the release of its associated products hinge on the synergy between an efficient bacterial strain and the formulation of a suitable growth medium. Balancing all nutrient levels of a growth medium to maximize microbial growth and the product quality is quite an intricate task. In this context, significant advancements have been achieved via the strategic implementation of design-of-experiment (DOE) methodologies and the utilization of parallel microbioreactor systems. This work presents a case study of the fermentation growth medium optimization of a Gram-negative bacterium of the Neisseriaceae family that releases outer membrane vesicles (OMVs), which represent a potential vaccine platform. To achieve this, the ability of Sartorius MODDE^®13 DOE software to explore multiple variables and their interactions was combined with the functionality of a Sartorius Ambr^® 15F parallel microbioreactor system. The findings reported in this study have led to the design of a well-suited fermentation medium for a Gram-negative bacterium and an improvement in the quality of the OMVs produced from it. Full article

The freeze-drying of biopharmaceuticals is a common strategy to extend their shelf-life and facilitate the distribution of therapeutics. The drying phase is the most demanding one in terms of energy consumption and determines the overall process time. Our previous work showed how the loading configuration can impact freezing. This paper focuses on primary drying by comparing the thermal behaviour of vials loaded in direct contact with the shelf or nested in a rack system. The overall heat transfer coefficient from the apparatus to the product was evaluated at different chamber pressures (5–30 Pa) and shelf temperatures (from −10 °C to +30 °C), and in the case of various vial positions (central, semi-border, and border vials). Because of the suspended configuration, the heat transfer coefficient was less affected by chamber pressure in vials nested in a rack system. The two loading configurations displayed comparable heat transfer efficiency below 10 Pa. For higher chamber pressure, the heat transfer coefficients of nested vials were lower than those of vials in direct contact with the shelf. Nevertheless, the rack system was beneficial for reducing the inter-vial variability as it promoted higher uniformity in the heat transfer coefficients of central vials. Eventually, thermal image analyses highlighted limited temperature differences between the vials and the rack system. Full article

There is an increasing demand to improve the overall sustainability of the biopharmaceutical industry. A barrier to improvement has been the limited research undertaken in the area of environmental impact of key design decisions. The aim of this study was to perform a comprehensive evaluation of the impact of buffer management strategy and technology selection on overall process efficiency using process mass intensity (PMI) as a metric for comparison. The environmental impact of buffer management has yet to be fully understood, despite buffers being one of the most resource-intensive aspects of biopharmaceutical manufacturing. A detailed process model was used to evaluate the impact of buffer management on a monoclonal antibody (MAB) process at the 2000 L scale. This was achieved by means of a non-replicated full factorial design composed of six variables: product titre, quantity of unique buffers, preparation frequency, single-use threshold and equipment cleaning duration with two levels and buffer preparation strategy type with four levels. The study identified that buffer management has a critical impact on overall process mass intensity, demonstrating a possibility to achieve a reduction in PMI of up to 90% for the best scenario compared to the worst. The findings also indicated that single-use systems are greatly superior to stainless-steel systems in terms of overall process efficiency, which is consistent with established thinking. The results from this research represent a further significant step towards achieving a more sustainable biopharmaceutical industry, establishing buffer management as a critical focus area, quantifying the influence of key variables on process mass intensity and highlighting the benefits of using a process mass intensity metric as part of routine biopharmaceutical design. Full article

Piroxicam is a Biopharmaceutical Classification System (BCS) Class II drug having poor aqueous solubility and a short half-life. The rationale behind the present research was to develop a Piroxicam nanosuspension to enhance the solubility and thereby the in vitro bioavailability of the drug. Piroxicam nanosuspension (PRX NS) was prepared by an anti-solvent precipitation technique and optimized using a full-factorial design. Herein, the nanosuspension was prepared using polymer polyvinylpyrrolidone (PVP) K30^® and Poloxamer 188^® as a stabilizer to improve the solubility and in vitro bioavailability of the drug. Nine formulations were prepared based on 3² full-factorial experimental designs to study the effect of the formulation variables such as concentration of poloxamer 188 (%) (X₁) and stirring speed (rpm) (X₂) as a process variable on the response of particle size (nm) and solubility (µg/mL). The prepared NS was characterized by phase solubility, Fourier-transform infrared (FT-IR), differential scanning calorimetry (DSC), X-ray powder diffraction (XRPD), transmission electron microscopy (TEM), particle size, zeta potential, entrapment efficiency, and percent drug release. DSC and XRPD analysis of freeze-dried NS formulation showed conversion of PRX into a less crystalline form. NS formulations showed a reduction in the size from 443 nm to 228 nm with −22.5 to −30.5 mV zeta potential and % drug entrapment of 89.76 ± 0.76. TEM analysis confirmed the size reduction at the nano level. The solubility was increased from 44 μg/mL to 87 μg/mL by altering the independent variables. The solubility of PRX NS in water was augmented by 14- to 15-fold (87.28 μg/mL) than pure PRX (6.6 μg/mL). The optimized formulation (NS9) at drug-to-stabilizer concentration exhibited a greater drug release of approximately 96.07% after 120 min as compared to the other NS formulations and pure PRX (36.78%). Thus, all these results revealed that the prepared NS formulations have improved the solubility and in vitro dissolution compared to the pure drug. Furthermore, an increase in the drug release was observed from the NS than that of the pure PRX. All these outcomes signified that the prepared PRX NS showed an increase in solubility and in vitro dissolution behavior; which subsequently would aid in attainment of enhanced bioavailability. Full article

Optical density (OD) is a critical process parameter during fermentation, this being directly related to cell density, which provides valuable information regarding the state of the process. However, to measure OD, sampling of the fermentation broth is required. This is particularly challenging for high-throughput-microbioreactor (HT-MBR) systems, which require robotic liquid-handling (LiHa) systems for process control tasks, such as pH regulation or carbon feed additions. Bioreactor volume is limited and automated at-line sampling occupies the resources of LiHa systems; this affects their ability to carry out the aforementioned pipetting operations. Minimizing the number of physical OD measurements is therefore of significant interest. However, fewer measurements also result in less process information. This resource conflict has previously represented a challenge. We present an artificial neural-network-based soft sensor developed for the real-time estimation of the OD in an MBR system. This sensor was able to estimate the OD to a high degree of accuracy (>95%), even without informative process variables stemming from, e.g., off-gas analysis only available at larger scales. Furthermore, we investigated and demonstrated scaling of the soft sensor’s generalization capabilities with the data from different antibody fragments expressing Escherichia coli strains. This study contributes to accelerated biopharmaceutical process development. Full article

Development and optimization of biopharmaceutical production processes with cell cultures is cost- and time-consuming and often performed rather empirically. Efficient optimization of multiple objectives such as process time, viable cell density, number of operating steps & cultivation scales, required medium, amount of product as well as product quality depicts a promising approach. This contribution presents a workflow which couples uncertainty-based upstream simulation and Bayes optimization using Gaussian processes. Its application is demonstrated in a simulation case study for a relevant industrial task in process development, the design of a robust cell culture expansion process (seed train), meaning that despite uncertainties and variabilities concerning cell growth, low variations of viable cell density during the seed train are obtained. Compared to a non-optimized reference seed train, the optimized process showed much lower deviation rates regarding viable cell densities (<10% instead of 41.7%) using five or four shake flask scales and seed train duration could be reduced by 56 h from 576 h to 520 h. Overall, it is shown that applying Bayes optimization allows for optimization of a multi-objective optimization function with several optimizable input variables and under a considerable amount of constraints with a low computational effort. This approach provides the potential to be used in the form of a decision tool, e.g., for the choice of an optimal and robust seed train design or for further optimization tasks within process development. Full article