Quantifying Innovation: Intellectual Property Data as Indicators of Technology Maturity of Metal–Organic-Frameworks and Inorganic Nanoparticles

Abstract

The increasing significance of intellectual property (IP) in recent decades highlights its crucial role in driving innovation and shaping competitive strategies. While many studies have attempted to evaluate the technological level of specific sectors or companies, few offer a standardized and scalable approach for cross-domain comparison. This study proposes a patent-based framework to comparatively evaluate technological maturity across different fields using a concise set of intellectual property (IP) indicators. The selected metrics, renewal trends, family size, grant rate, and citation patterns, capture legal, economic, and technological dimensions of innovation without requiring field-specific calibration. We apply this approach to two representative nanomedical technologies, Metal–Organic Frameworks (MOFs) and inorganic nanoparticles (iNPs), within the domain of cancer therapy. Our analysis highlights distinct trajectories: MOFs show increasing patent activity and sustained short-term citation growth, consistent with an emerging field; iNPs exhibit signs of stabilization and declining citation intensity, suggesting greater maturity. These findings demonstrate the utility of standardized IP indicators for mapping innovation dynamics across domains. The proposed framework offers a replicable tool for strategic technology assessment, with potential applications in research prioritization, technology forecasting, and early-stage investment analysis.

1. Introduction

In a world increasingly driven by technological innovation, the ability to strategically manage and assess intellectual property (IP) has become essential for guiding investment, policy, and innovation strategies. Companies and investors face mounting pressure to identify promising technologies early, optimize R&D allocation, and maintain a competitive edge. However, existing evaluation tools, such as expert reviews, technology readiness levels (TRLs), or bibliometrics, are often limited by subjectivity, sector-dependence, or lack of early-stage coverage [1,2,3]. Despite the proliferation of sector-specific metrics and innovation dashboards, there is still no accessible, standardized methodology for comparing the technological maturity of emerging fields in a consistent and cross-domain fashion. Many existing models are data-intensive, rely on static indicators, or require detailed knowledge of the application context, making them less viable in fast-evolving or resource-constrained settings. In this complex context, intellectual property (IP) valuation has emerged as a strategic tool for assessing technological innovation, guiding investment and policy decisions, and informing competitive positioning and technology forecasting. Patent indicators, in particular, offer actionable insights into innovation dynamics, R&D strategy, and market potential, making them increasingly valuable across corporate, academic, and policy domains [4,5,6,7,8,9,10,11,12,13,14,15]. Firm-level evidence shows that the economic value of a firm’s early patents predicts multiple dimensions of its subsequent research success; moreover, a subset of ‘hidden gem’ firms can be detected through the technological value of their early patents, underscoring the strategic utility of early IP signals for scouting and policy [16]. However, existing approaches often remain fragmented, targeting individual sectors, companies, or isolated indicators, without providing a unified, comparative framework for assessing the maturity of different technologies. Moreover, most studies adopt a static perspective, lacking the temporal and geographical resolution needed to interpret the dynamic evolution of emerging technologies. As a result, there is still a lack of accessible, cross-sectoral methodologies capable of comparing technological trajectories with standardized, interpretable, and low-input indicators. In response, this paper introduces a minimal, scalable, and domain-independent framework to assess the maturity of emerging technologies based solely on patent-derived indicators. This methodology is tested through a comparative case study in cancer nanomedicine. Unlike existing approaches that focus on specific domains, require heavy data preprocessing, or rely on static metrics, our contribution introduces a streamlined IP-based framework that operates entirely on publicly available data, enabling consistent comparison across fields. While we acknowledge that patent value does not have a precise or universal definition, and is highly context-dependent, we argue that a carefully selected set of IP indicators can provide meaningful insights into the relative maturity and strategic positioning of a technology. Our approach does not aim to quantify absolute value, but to offer a comparative lens for analyzing how technologies evolve over time and space. As a first step in our comparative analysis, we construct a technological landscape that captures the legal, economic, and strategic dimensions of the two fields. This landscape does not aim to assign value per se, but to contextualize the technologies through fundamental patent-derived signals. Among these, the renewal history of patents serves as a proxy for the sustained economic interest in the protected inventions: longer maintenance periods typically indicate higher perceived utility and long-term commitment from the assignee. We also consider the size of patent families, which reflects the geographical scope of protection. A broader territorial coverage often points to greater market ambition and higher investment in IP strategy. Lastly, the grant rate, calculated as the ratio of granted to filed patents, offers insight into the inventive step and legal robustness of the technological outputs, as acknowledged by patent offices. Beyond this descriptive layer, our methodological contribution centers on two synthetic indicators that enable a systematic comparison between technologies based on their maturity, persistence, and influence within the innovation ecosystem. While the landscape offers essential descriptive grounding, the core of our analytical framework is built on two synthetic indicators that capture the temporal, spatial, and relational dynamics of innovation. The first is the Scope–Year (SY) index, a composite metric that combines the duration of patent protection with the geographical breadth of coverage [17]. It reflects not only how long a piece of technology remains protected, but also how widely it is deployed across international markets. To account for market relevance, the geographical component can be optionally weighted by GDP, linking technological persistence to potential economic impact. This index enables a systematic comparison of how technologies evolve and persist in global innovation environments. The second indicator draws on patent citation analysis, widely recognized as a proxy for technological influence. We consider both applicant-driven citations, analogous to references in scientific literature, and examiner-added citations, which emerge from prior art searches. Forward citations indicate how much a technology informs subsequent developments, while backward citations reveal its foundational knowledge base. Further, large-scale evidence using machine learning shows that family size and early-citation signals (e.g., first-citation speed) rank among the most informative predictors of patent value [18]. Taken together, these two indicators provide a robust and interpretable lens through which to compare the maturity and positioning of emerging technologies, revealing dynamic trends that can support strategic decisions in innovation policy and investment. To validate this approach, we selected two representative nanomedical technologies in the field of cancer therapy: Metal–Organic Frameworks (MOFs) and inorganic nanoparticles (iNPs), including plasmonic and magnetic variants. MOFs are highly tunable drug delivery systems with favorable biocompatibility and controlled release properties, while iNPs provide externally triggered drug release and multifunctional features such as imaging and phototherapy [19,20,21,22,23]. By applying our methodology to MOFs and iNPs within a consistent application domain, cancer nanomedicine, we minimize domain-specific biases and isolate key innovation dynamics. This study thus offers a replicable and lightweight strategy for assessing technological trajectories using only IP data, with potential applications in research prioritization, strategic investment, and innovation policy. Through this comparative framework, we aim to assess whether a selected set of IP indicators can effectively distinguish between technologies at different stages of maturity.

2. Materials and Methods

Patent families were retrieved from Orbit Intelligence (queries and filters in Appendix A) by searching title, abstract and claims with a biomedical filter and an application-date cutoff. Inventions were analyzed at the earliest-priority family level (to avoid multiple counting across jurisdictions) and time series were aggregated by priority year.

In order to evaluate priority filings, applications, and grants, we proceeded as follows: for each patent family we kept the Earliest Priority Date (EPD) as a proxy for one invention across jurisdictions; for each family member we used its Application Date and, when available, its Grant Date (per jurisdiction). We then built three yearly time series by simple aggregation.

To summarize the temporal (lifespan) and geographical (territorial coverage) extent of protection at the family level, we use an explicit formulation of the SY index that distinguishes between (i) the unweighted version and (ii) an optional GDP-weighted version for market-relevance adjustment.

$$SY\left(t\right)={\sum }_f^{F\left(t\right)}{\sum }_c^{C_f}{\sum }_l^{L_c}{g}_c\left(t+l\right)$$

(1)

where F(t) is the number of total families borne in the year t, $C_f$ represents the countries where the family f extends the patent application, $L_c$ is the life expressed in years of the patent applied in the country c, l is a natural number from 0 to $L_c$, $g_c(t+l)$ is a coefficient that is 1 for the unweighted SY index, while for the weighed one it is:

$$g_c\left(t\right)= {\displaystyle \frac{{GDP}_c\left(t\right)}{{GDP}_{USA}\left(t\right)}}$$

(2)

where ${GDP}_c\left(t\right)$ and ${GDP}_{USA}\left(t\right)$ are, respectively, the Gross Domestic Product of the country c and USA evaluated in the year t. This formulation allows the SY to account not only for how long and where a technology is protected, but also for how strategically valuable those jurisdictions are from an economic standpoint.

In this study, we use the unweighted specification throughout to maximize interpretability and cross-field comparability.

3. Results

3.1. Technological Landscape

We begin by assessing the inventive activity in the MOFs and iNPs technology domains (see

Table A1. Query for the search of the patent families sets analyzed for MOFs and iNPs (“*” indicates truncation, allowing retrieval of all terms beginning with the specified root.).

Technology	Query
Metal–organic frameworks (MOFs)	Title abstract claims = ((MOF) or (MOFs)) or (metal–organic-framework *)
	AND
	Title abstract claims = (bio * or medic * or therap * or (in vivo) or (in vitro) or pharma * or cure *)
	AND
	Application date ≤ 2020
Inorganic Nanoparticles (iNPs)	Title abstract claims = (magnetic * nanoparticle *) or (plasmonic * nanoparticle *) or (iron oxide nanoparticle *)
	AND
	Title abstract claims = (bio * or medic * or therap * or (in vivo) or (in vitro) or pharma * or cure * or Diagnostic * or diagnosi * or theranostic)
	AND
	Application date ≤ 2020

in the Appendix A for the query used). To ensure a consistent representation of inventive activity, we use the earliest priority application of each patent family as a proxy for a single invention, allowing clearer temporal tracking across technologies despite variability in how ‘invention’ is defined. To compare the innovation capacity of these fields, we analyze the yearly frequency of earliest priority filings as a proxy for inventive output. Figure 1 provides an insightful overview of the patent production from 1990 to 2020, including the number of applications, granted patents, and priority filings. We observe a total amount of 2035 and 3862 patent families for, respectively, MOFs and iNPs with markedly different growth patterns. The two technologies follow distinct innovation trajectories: iNPs exhibit steady growth throughout the early 2000s, followed by a noticeable slowdown around 2013. In contrast, MOFs show slower initial activity, with a sharp acceleration in patent filings beginning in 2015. These trends may reflect the relative maturity of scientific research in each domain (Figure 2). In fact, the fields of MOFs and iNPs have seen a notable increase in scientific publications, with a peak in 2020, contributing approximately 28% and 12% of the total, respectively. This growth trend closely mirrors the patent activity depicted in Figure 1, highlighting the strong link between R&D investments and IP production.

Patent volume alone does not convey information on the quality or strength of the protected inventions. To complement this picture, we analyze the grant rate of patent families. The volume of granted patents within a family serves as a metric conveying insight into application quality, the robustness of innovative ideas, and the technological relevance in the market. Granted applications represent inventions that are acknowledged as novel and inventive in comparison to the existing state of the art, with the accumulation of grants within a family reflecting acknowledgment by different patent offices globally. Moreover, granted patents confer exclusive rights to assignees, wielding the potential to exert a tangible influence on the market, even though the pending applications may also bear influence.

Looking deeper into the granted applications, the grant rate for the patent families in each technology field Figure 3 shows an initial period marked by considerable noise, which is primarily due to the limited data availability in the early years. After this period, the grant rates for both technologies exhibit fluctuations within a range roughly spanning from 60 to 70%. Notably, in recent years, it seems to be a decreasing tendency in the proportion of granted patents, down to 50% in both cases. This reduction is likely attributed to ongoing examination processes. It is important to bear in mind that this process typically extends over a period of a few years. Patent family size (Figure 3b) further complements this analysis, providing insight into global protection strategies and potential market reach [17,25]. For instance, a larger family size often indicates: (i) a broader geographical protection, as each member of the family may correspond to a patent application filed in a different country; (ii) higher fees to sustain for the assignee, and thus, a higher bottom line for the economic value of the technology; and (iii) strong innovation impact and relevance across multiple jurisdictions, showing the adaptability and applicability in diverse regulatory environments of the protected invention. In contrast, the average family size for both MOFs and iNPs has significantly declined. Even accounting for early-period fluctuations due to low filing volumes, family size starts stabilizing after 2000 or 2010, and getting closer to 1 (the minimum size) until 2010 or 2020 for iNPs or MOFs, respectively. Note here the different timeline between the technologies, particularly post-2000. In the initial decades of the 21st century, the general family size of iNPs is roughly half compared to MOFs. However, as they approach the year 2020, the two technologies converge toward a similar family size. Part of this recent decline may be explained by the fact that some families have not yet entered the national phase of the international filing process (under the Patent Cooperation Treaty (PCT), applicants can delay national phase entry for up to 30–31 months from the earliest priority date). Nonetheless, the decrease in size is also evident in the past (after 2010 for MOFs, and after 2000 for iNPs), for which the period of extension is already expired. This suggests that the observed decline may partly reflect a more targeted protection strategy or a lower commercial valuation of recent inventions.

3.2. Patents Lifespan and Scope Year Index

An additional insight comes from analyzing the evolution of the average patent lifespan Figure 4, which reflects the duration of legal protection over time. The observed trends exhibit striking similarity in both scenarios, with the average patent lifespan steadily declining to 2.5 years by the year 2020. As we approach the data collection year (2023), many patents have not had time to reach full term, making lifespan estimates unreliable after 2003. As in previous analyses, the early years are affected by significant statistical noise due to the limited number of patent filings. Nevertheless, we can still consistently discuss the last decade if we consider the deviation from the line that represents the possible maximum lifespan in time (represented as a red line). After the initial fluctuations, the gap between the average and maximum lifespan narrows. This suggests that newer patents are maintained longer, likely reflecting greater confidence in their market potential. This behavior is expected, as assignees often monitor a patent’s commercial viability during its early years. A larger gap may indicate lower perceived value or strategic relevance by the assignee. In fact, in cases where the market is not receptive, it is already saturated, or the invention fails to capture a substantial market share, the assignee may opt to let the patent go abandoned and allow for its withdrawal. This pattern may reflect rapid market testing or fast technological turnover in competitive fields such as iNPs and MOFs. This trend may indicate the need for companies to quickly ascertain the commercial viability of their innovations in competitive and rapidly evolving markets. As patents approach closer to their maximum potential lifespan, it reflects increased confidence in the market potential and value of these technologies. However, the short lifespan also highlights the challenges faced by innovators in sustaining long-term intellectual property protection amidst shifting market dynamics and technological advancements. A central element of this study is the Scope–Year (SY) index, which integrates the temporal duration and geographical extension of patent families into a single synthetic metric. It provides a dynamic measure of how technologies evolve over time and across jurisdictions. The SY index is calculated by summing the lifespan of all patent members within a family, from their grant to expiration or withdrawal. This value is then aggregated per priority year to show yearly trends. We also compute an average SY per family to assess the typical extent of protection. Finally, we introduce a GDP-weighted version of the index, accounting for the economic relevance of each jurisdiction. The detailed formulation of the SY index is provided in the Materials and Methods section. The temporal evolution of the SY index is shown in Figure 5a. In the early years, MOF patents display significant fluctuations, likely due to ow filing volumes and data sparsity. A clear peak appears in 2007, followed by a gradual decline and stabilization in the most recent period. In contrast, iNPs show a more consistent growth pattern in the early phase, supported by a broader patent base, before entering a sharp downward trend after 2010. For iNPs, the SY index begins to decline after 2010, eventually reaching near-minimal values by 2020. This drop, especially in recent years, is partly explained by the limited observation window: patents filed close to the data collection year (2023) have not yet had sufficient time to accumulate full lifespan and coverage.

We also examine the average SY index per patent family over the last 30 years (Figure 5). As expected, the early period is marked by strong fluctuations in both technologies. However, from 2000 to 2010, the trajectories diverge: iNPs show a steady decline in average SY, while MOFs maintain relatively high and stable values throughout the decade. This suggests a stronger international and temporal footprint for MOFs during that period. Moreover, this observation is reinforced by the subsequent surge in MOF patent filings after 2015, contrasting with the plateau observed for iNPs. It is important to note that the most reliable SY data corresponds to patents filed at least 15–20 years before the data collection year (2023), due to delays introduced by procedures like the PCT and the natural accumulation of patent lifespan. As we approach more recent years, the index is naturally biased downward by design. Despite this limitation, combining SY trends with additional signals, such as average patent lifespan (Figure 4), can still yield useful comparative insights.

3.3. Citations

Citations capture how inventions build upon each other and signal a technology’s influence on subsequent developments. Analyzing citation trends thus provides insight into a technology’s immediate impact, long-term relevance, and position within the broader innovation landscape. Thus, Figure 6 illustrates the citation patterns for the patent families in both fields, with a focus on 3- or 5-year citations (that is the citations received by the family 3 or 5 years after the first priority, respectively) and total citations. Consistent with our choice of fixed 3–5-year windows, dynamic models of patent citation networks indicate that trajectories are shaped by temporal phenomena, supporting the use of early-impact windows as a robust proxy [26]. While total citations are still evolving, short-term citations (fixed at 3- or 5-years post-priority) offer a stable measure of early technological impact, at least up to 2017–2019. This immutability in short-term citation trends provides a relatively robust indicator of the immediate impact and recognition of patent families within those timeframes. In the case of MOFs, we observe a notable outlier in 1991: a single patent family that has accumulated over 1700 citations, suggesting substantial but delayed recognition of its technological relevance. Excluding this outlier, the trend in short-term citations (3- and 5-year windows) shows a gradual increase over time, while total citations tend to decline as we approach 2020, due to the limited time for citation accumulation. The narrowing gap between short-term and total citations is consistent with this observation. Several factors might explain the rise in early citations: (i) improved patent quality, meaning newer patents are more influential and thus cited more often; (ii) citation inflation, whereby newer patents include more references due to changing examination practices or strategic behavior by applicants; (iii) growth in patent volume, where the general increase in filings leads to more opportunities for cross-citation across technologies. To account for yearly variations in patent volume, citations were normalized by the number of families filed each year. When examining average citations per family, the outlier from 1991 stands out with over 1700 citations attributed to a single MOF-related family; an anomaly that suggests delayed but substantial recognition. Excluding this case, the average citations per family over the last 20 years show a downward trend, stabilizing around 4–5 citations per family, with occasional spikes. Notably, 3- and 5-year citation windows show a milder decrease and a more stable trajectory, suggesting a sustained short-term impact despite overall citation fatigue. Several factors could contribute to this pattern: diminished interest in the field, a reduced number of citing patents, or a tendency for newer patents to cite prior art less frequently.

Regarding iNPs, citation activity is more concentrated in an earlier time window and begins a marked decline around 2013, across all three citation categories (total, 3-year, and 5-year). This pattern supports the notion, already suggested by patent volume and SY trends, that iNPs have passed their peak period of development and entered a more mature phase. The decline is especially evident when looking at average citations per family, which drop below 5 in recent years even for short-term citations. This could be attributed to a narrowing technological focus, with fewer cross-domain applications, or simply to a lower relevance of more recent patents. Comparing the two technologies, iNPs display traits of maturity and stabilization, whereas MOFs exhibit sustained and possibly increasing short-term influence. This contrast reinforces the broader narrative emerging from the analysis: while iNPs appear to have plateaued, MOFs are still on a rising trajectory, potentially approaching their innovation peak. These diverging paths highlight the heterogeneous lifecycles that technologies can follow, even within the same application domain.

4. Discussion

This study proposes a lightweight and replicable framework to compare the maturity of emerging technologies using only patent-derived indicators. While it does not aim to estimate absolute technological value, the approach proves useful in highlighting relative differences when applied to comparable domains. Through a case study on Metal–Organic Frameworks (MOFs) and inorganic nanoparticles (iNPs) in the field of cancer nanomedicine, we show how selected IP metrics, particularly the Scope–Year index and citation trends, can reflect key innovation dynamics. The analysis of patent production, combined with these indicators, highlights notable differences in the maturity trajectories of MOFs and iNPs. Specifically: (i) patent filings for iNPs exhibit a clear deceleration starting around 2013, while MOFs show a sharp increase after 2015; (ii) the Scope–Year (SY) index is consistently higher for MOFs throughout the 2010–2020 decade, indicating broader and more sustained protection; (iii) citation trends diverge, with MOFs maintaining relatively stable short-term impact, while iNPs show a progressive decline. We interpret these patterns through established IP-based maturity proxies. In particular, renewal/family-scope measures, captured by the SY index, and forward citations have been linked to patent value and commercialization likelihood in prior work. In this lens, iNPs’ post-2013 filing slowdown and declining 3–5-year citations are consistent with a consolidation stage and increasingly targeted territorial strategies, whereas MOFs’ sustained early-window citations and comparatively broader SY footprint (2010–2020) indicate an expansion stage with wider and longer protection. A plausible reading is that iNPs face demand/regulation-driven saturation that compresses incremental filings, while MOFs retain higher design plasticity that supports faster inventive recombination. In practical terms, this results in a lead–lag dynamic, with iNPs consolidating while MOFs continue to explore. The proposed framework offers a practical tool for comparing the technological maturity of emerging domains. In the context of nanomedicine, MOF–iNP hybrids/composites (e.g., MOF shells on magnetic/plasmonic cores) represent a promising direction in which the mature iNP platform can pull MOFs via manufacturing/regulatory know-how, while MOFs refresh iNPs through introducing tunable porosity and functional adaptability via targeting and controlled release. Within our indicators, such convergence would likely appear as cross-citations, co-assignments, and stabilized short-term citation impact within the hybrid sub-space. By capturing differences in persistence, global diffusion, and innovation visibility, it can inform decision-making in research prioritization, technology scouting, and investment planning. Its simplicity and reliance on public data make it particularly suitable for early-stage evaluation, especially in dynamic or resource-constrained contexts. Moreover, trend analysis through standardized patent indicators may help identify collaboration opportunities and anticipate shifts in technological positioning. These patent-based indicators are decision aids and are sensitive to time-censoring and Scope–Year weighting; nevertheless, the directional conclusions remain stable under simple. Accordingly, we interpret late-period signals cautiously and recommend triangulation with market or clinical evidence, when available. Future research could extend this approach to broader sectors, examining multiple technologies within the same application domain. As an avenue for extension, our framework could integrate multi-dimensional, diffusion-oriented metrics of technological value, capturing lifetime, strength, breadth, and geographic dispersion, alongside SY to test robustness across measurement families [27]. Combining IP indicators with market performance and regulatory data could reveal correlations between innovation maturity and commercial impact, thus refining forecasting capabilities and investment strategies.

5. Conclusions

This work introduces a simple, patent-based framework to assess the maturity of emerging technologies using open data. In a cancer–nanomedicine case study, Scope–Year and short-window citations reveal divergent paths: iNPs show post-2013 consolidation, whereas MOFs continue to expand with broader and longer protection. The approach is replicable and decision-oriented, supporting early prioritization and technology scouting. Despite inherent time-censoring, the observed trends remain robust. Future work will explore MOF–iNP convergence (composites) by tracking co-assignments, cross-citations and aligning IP signals with market or clinical data.