Use of Modeling and Simulation to Inform the Development of Monoclonal Antibodies to Treat Moderate‐to‐Severe Asthma: A Retrospective Review of EMA Centralized Procedure From 2014 to 2024

ABSTRACT

We present here a repository of key regulatory questions answered in centralized procedures and evaluate the place of modeling and simulation in marketing authorization process for biologics approved for the treatment of moderate‐to‐severe asthma from 2014 to 2024. This was done consistently with the ICH M15 recommendations and the ERAMET project that consistently aim to define the framework for assessment of model informed drug development evidence to inform decision‐making. We carried out a search for marketing authorization applications for the five approved monoclonal antibodies in the treatment of asthma from 2014 to 2024. We translated the information into essential regulatory questions and classified the questions based on the level of the questions and their granularity. Credibility activities were performed by applying the credibility framework of the ICH M15 guidelines to questions answered by modeling and simulation methods. A total of 190 questions were extracted including 74 questions related to efficacy, 86 to safety, and 30 questions related to pharmacokinetics. The proportion of questions answered oscillated between 51% and 65% for each drug. Modeling and simulation methods were used to answer 25% of the questions. These methods are predominantly used to address pharmacokinetics questions, with 60% of these questions answered in at least one marketing authorization application using these methods. Credibility matrices were fulfilled for questions answered by modeling and simulation methods. We identified the types and roles of modeling and simulation approaches used in the development of monoclonal antibodies for treat moderate‐to‐severe asthma approved from 2014 to 2024.

Study Highlights

• What is the current knowledge on the topic?

  • ○
    The current pathway for development and approval of effective and safe drugs for pediatric and rare disease is not optimal. To overcome challenges in pediatric drug development, model informed drug development and related extrapolation offers powerful tools that can address some of the current limitations. However, these tools are still not always optimally used as part of an integrated drug development strategy, nor always systematically endorsed by regulators.
• What question did this study address?

  • ○
    This article describes a repository of key regulatory questions built using the question‐centric approach for monoclonal antibodies approved for asthma treatment. This repository relies on adequate question identification, use of appropriate data and methods and optimal method credibility assessment and benchmarking. An analysis of the repository locates the use of M&S methods and benchmarks these innovative methods versus standard methods.
• What does this study add to our knowledge?

  • ○
    The analysis of the repository indicates that despite their potential multidimensional role, modeling and simulation approaches were predominantly used to characterize the pharmacokinetic and the efficacy of the product at population level. Only common modeling and simulation approaches have been used, whereas the more recent and emerging additional modeling techniques were not used. The repository analysis also showed heterogeneity in the use of modeling and simulation across products.
• How might this change drug discovery, development, and/or therapeutics?

  • ○
    This repository aims to provide drug developers and regulators with an integrated tool to support the decision‐making process, learn across process and therefore, contribute to adoption of alternative data types and innovative analytical methods. This could accelerate the effective development of monoclonal antibodies for asthma treatment, especially for the pediatric population.

1. Introduction

Asthma is among the most common chronic respiratory conditions, affecting 300 million people worldwide and affecting both adults and pediatric patients [1]. Asthma is more prevalent in children and adolescents than in adults, with reported prevalence estimates in pediatric populations generally ranging from approximately 3500–5500 per 100,000 individuals [2, 3]. More than 10% of patients overall have severe asthma, a complex and heterogenous airway condition defined by the need for high doses of inhaled corticosteroids in combination with an additional controller medication [4]. In children, severe asthma represents a smaller proportion of cases, affecting up to approximately 5% of pediatric patients with asthma [5]. Two asthma endotypes have been widely recognized, based on the presence or absence of type 2 airway inflammation [1]. Over the last few decades, drugs targeting type 2 inflammation have been developed and have demonstrated their effectiveness in controlling symptoms. However, there remains a need for more targeted and effective therapies, particularly for patients with severe forms of the disease [1].

Moreover, drug development in the pediatric population is more challenging due to practical and ethical limitations in collecting experimental evidence (mostly data from randomized controlled trials) in this group of patients. Pediatric trials are particularly challenging and suffer from enrolment difficulties due to reluctance of parents and/or caregivers to enroll pediatric patients in experimental trials, small number of patients, variability in physiological characteristics, uncertainties in dose selection and ethical complexities [6, 7].

The current pathway for development and approval of effective and safe drugs for pediatric diseases is not optimal, even if progress was achieved by combining requirements and incentives for pediatric drug development [8]. As a consequence, there is a lack of licensed drugs for all pediatric age groups and in dosage forms that are suitable, which led to a high rate of off‐label use of respiratory medicines among children [9]. On average, approximately a decade gap exists between the product's approval for use in adults until incorporation of pediatric information in the label [6]. For the specific case of asthma, a study showed that the use of inhaled corticosteroids and long‐acting β‐agonists in 18.8% were off‐label prescriptions [10].

To overcome challenges in pediatric drug development, modeling and simulation (M&S) and related extrapolation represent powerful approaches that can address some of the current limitations by complementing or replacing clinical trials. By using quantitative models to integrate and leverage existing knowledge, gaps can be bridged, and drug development can be facilitated, as well as the decision‐making process [6]. Furthermore, M&S strategies can contribute to minimizing the number of patients required in clinical trials [7].

Model‐informed drug development (MIDD) provides a structured framework that integrates M&S to inform drug development and regulatory decisions. In pediatric settings, MIDD is particularly valuable for extrapolating efficacy data from adults [7]. This approach is possible under conditions, including adequate characterization of similarity and differences in the disease progression course between adults and pediatrics, anticipation of a comparable response to the treatment, and similarity in exposure‐response relationship between adults and pediatrics. Modeling and simulation methods within the MIDD framework are also instrumental for optimizing clinical trial design and refining dosing regimens [7]. For example, pediatric trial design can be optimized by simulating study scenarios using PK or PK/PD models, which helps refine the number of participants, the sampling schedule, and the number of samples [11].

One of the advantages of this exercise is that it allows to map the current use of modeling and simulation across drug development programs, thereby highlighting existing gaps and the need for further development and broader use of innovative M&S methods to address key regulatory questions. While M&S and extrapolation play an increasingly important role in pediatric medicine research and development and have been proposed to address some of the current limitations by complementing or replacing randomized controlled trials, these methods are still not always optimally used as part of an integrated drug development strategy, nor always systematically endorsed by regulators [12]. Current regulatory procedures and assessors' training are largely tailored to traditional data types and analytical methods and to their sequential and compartmentalized assessment. There is currently no systematic and integrated approach within the European regulatory framework to assess and establish the acceptability of alternative methods such as M&S and related data sources.

There is currently an unmet need for acceptability criteria related to the assessment of M&S approaches when applied to drug development and assessment in pediatric diseases to improve consistency and efficiency in pediatric drug development.

The use of the question‐centric approach [12] in the context of drug development and regulatory decision‐making permits to effectively use different types of methods (including M&S) and data to address a particular question in an integrative and objective manner. The implementation of this approach is populated in the ICH M15 as well as the ERAMET project (Horizon Europe grant 101137141) aiming at implementing a framework for assessment of MIDD evidence to inform decision‐making [13]. The ERAMET project aims to deliver an integrated ecosystem that supports regulatory submissions, and the assessment of model‐informed approaches applied to pediatric and orphan drug development. This approach relies on the principle that better‐framed questions receive better answers and that the key questions in drug development should be explicitly formulated and clearly linked to the data and (analytical) methods used to address them in order to contribute to the overall benefit/risk assessment. For each combination of question, method and data, the credibility assessment can be implemented to facilitate the regulatory assessment.

The present work illustrates how drug development and assessment can be structured using the previously published question‐centric framework and describes the development of a question‐centric repository connecting key regulatory questions with data and methods used to support market access or to enable bridging across conditions of use. In this context, “bridging across conditions of use” refers to leveraging existing evidence to extend conclusions from one use setting (e.g., indication, dosing regimen, or formulation) to another. The repository was populated using case studies of monoclonal antibodies approved for the treatment of severe asthma, illustrating how MIDD evidence has been positioned and assessed in the centralized marketing authorization process. To explore the credibility and regulatory acceptance of such evidence, a comparative analysis of M&S methods versus traditional evidence‐generation approaches was conducted. As the full potential of alternative data types and innovative methods can only be realized when appropriate tools for evaluating their credibility exist, a benchmarking of M&S methods was also performed. Finally, the table for assessment of MIDD evidence, a communication tool between applicant and regulatory authorities proposed in the ICH M15 guideline, was applied to evaluate the credibility requirements of M&S evidence in this context [13].

2. Data and Methods

2.1. Data Extraction/Searching

We carried out a retrospective systematic review of marketing authorization applications (MAAs) and related European public assessment reports (EPARs) for the five monoclonal antibodies approved for the treatment of moderate‐to‐severe asthma from 2014 to 2024. All these mAbs have been approved as add‐on therapy for moderate‐to‐severe asthma (Appendix S1). Mepolizumab, reslizumab, and benralizumab target interleukin‐5 (IL‐5) signaling; dupilumab targets the IL‐4 receptor alpha, and tezepelumab targets the thymic stromal lymphopoietin. All are approved for use in both adults and adolescents, except for reslizumab, which is approved for adults only. Additionally, mepolizumab and dupilumab have received EMA approval for use in children aged 6 to 11 years.

2.2. Data Extraction From Regulatory Submissions and Repository Structure

We comprehensively reviewed information related to quality, primary pharmacodynamics, toxicology, clinical efficacy, clinical safety and clinical pharmacology of the drugs included in the MAA dossiers and EPARs for the 5 approved drugs. This information was subsequently translated by the authors into essential regulatory questions (e.g., “What is the PK profile of a typical individual at population level?”) (Figure 1). We also extracted data and analytical methods used to address these questions for each approved drug.

FIGURE 1.

Flow diagram of the methodology used for repository building.

The general structure of the repository was developed based on a broader retrospective review of regulatory documents (i.e., scientific advice and pediatric investigation plan) to enrich the repository with multi‐faceted insights and to enhance its relevance and applicability. The structure of the repository relies on the benefit–risk assessment (BRA), which is supported by the characterization of efficacy, safety and PK, organized in a hierarchical manner, i.e., at population, individual, tissular, cellular and molecular levels and according to their granularity. Characterization of efficacy, safety and PK thus constitutes successive sublayers for BRA for a particular combination of dose, formulation and indication for a particular drug (see Figure 2, overall structure of the repository) [14, 15, 16]. The three elements (dose/regimen, formulation and indication) will be called “the conditions of use”. Questions, data and methods related to bridging across conditions of use are presented on top of the BRA, after the initial positive benefit/risk establishment. In this case some extrapolation of efficacy and safety or some borrowing of information pertaining to the initial program is permitted.

FIGURE 2.

General structure of the repository harmonized based on regulatory review applied to different use‐cases.

After the first layers constituted by the highest levels of questions and sub‐questions related to efficacy, safety or PK characterization as shown in Figure 2, methods and data used to inform the answer to those questions can be seen as triggering a subsequent set of sub‐questions, leading to and generating loops of knowledge flow spanning across data types and fields of expertise (Appendix S2). The results were presented using the question‐centric approach and related the repository (i.e., type the questions and hierarchical level).

2.3. Positioning the Use of M&S in Marketing Authorization Applications: Credibility Assessment and Method Benchmarking

Descriptive statistics were generated to characterize the place of M&S methods and MIDD approaches in the concerned development programs. Statistics were presented both for the initial marketing authorization and for bridging across conditions of use (i.e., questions answered after the initial positive benefit/risk assessment to bridge from one combination of conditions of use to another). The results related to MIDD approaches were first the results across products and subsequently broken down per product, MIDD approach and regulatory decision points (clinical development phase).

To benchmark M&S methods versus other traditional methods, credibility assessment was implemented by filling the tables of assessment of MIDD evidence of the ICH M15 guidelines for questions answered by M&S methods.

3. Results

3.1. Repository of Key Regulatory Questions

Overall, a total of 190 different regulatory (sub‐)questions were formulated based on the retrieved information. Majority of questions were related to characterization of PK, efficacy and safety characterization either for initial MAA or for bridging across conditions of use. There were also sub‐questions related to the methodology used for data collection and analysis and sub‐questions related to data quality and informativeness. 166 and 42 questions were formulated from the initial MAAs and bridging across modalities, respectively. For the initial MAA, in total 64, 76, and 26 different questions were related to the characterization of efficacy, safety, and PK of the product, respectively (Figure 3). These numbers were very variable per product: when considered separately for each product, the percentage of repository questions covered varied between 51% and 65%. Appendix S3 summarizes the questions that were answered for each drug.

FIGURE 3.

Overview of the repository of key regulatory and methodology questions built using the question‐centric approach that have been answered in centralized marketing authorization applications for monoclonal antibodies approved for asthma treatment. The blue bars indicate the number of questions answered exclusively with non‐modeling and simulation methods. The orange bars indicate the number of questions answered with at least one using modeling and simulation methods. M&S, modeling and simulation; PK, pharmacokinetic.

For bridging across conditions of use (including bridging across indications, dosing regimen and/or formulations), a total of 42 individual questions were overall additionally formulated, including 26 questions related to the bridging from adults to the pediatric population. This number varied from 0 to 37 per product.

3.2. Positioning the Use of M&S in Marketing Authorization Applications

Modeling and simulation methods were used to answer 25% of the questions. In the initial MAA, they were predominantly used to characterize the PK of the products, with 78% of PK questions answered in at least one MAA at the population level using these methods (Figure 3). Additionally, M&S approaches were mainly used to characterize efficacy at the population level, with 38% of the efficacy questions at the population level answered by M&S methods. Modeling and simulation were not used to address efficacy and safety‐related questions at the molecular or individual level. The use of M&S to address safety characterization was limited (3%). For bridging across conditions of use, M&S approaches were applied to answer 22 questions out of 42 (52%). These approaches were most frequently used to bridge across indications, with 21 questions addressed using M&S methods, representing 58% of all bridging‐related questions. For the specific bridging across age groups, 16 questions were addressed using M&S methods (62%).

3.2.1. Analysis Per Type of MIDD Approach

As far as specific methodologies are concerned, Pharmacometrics as well as more empirical data driven models were used. Modeling and simulation approaches used included population pharmacokinetic (popPK) models, exposure‐response (E‐R) models, mixed models for repeated measures, pharmacokinetic pharmacodynamic (PK/PD) models, negative binomial models, power‐law dose models, popPK meta‐analysis, popPK/PD models and proportional odds models (Table 1). The popPK modeling was used to address the highest number of questions, with 16 questions answered at least once with this approach to characterize the PK of the product (Appendix S4). This model was consistently used across all initial MAAs, addressing between 7 and 10 questions for each treatment (Table 1). E‐R model, PK/PD model and mixed models for repeated measures (MMRM) were used to answer 12, 7 and 6 questions respectively at least once to characterize the efficacy (Appendix S2). However, these models were used less consistently across initial MAAs (Table 1). Each remaining model type was used to address five different questions or less (Appendix S4).

TABLE 1.

Number of questions answered by drug and by model type for initial MAA.

Model type	Drug 1	Drug 2	Drug 3	Drug 4	Drug 5	Total
PopPK	9	9	7	9	10	44
E‐R	7	7	0	1	0	15
NBR	2	1	4	1	3	11
MMRM	2	0	2	4	1	9
PK/PD	0	0	0	7	0	7
Power‐law	0	0	4	0	0	4
PopPK MA	0	0	3	0	0	3
Compartmental PK	0	0	3	0	0	3
POR	0	0	2	0	0	2
popPK/PD	0	0	2	0	0	2

Abbreviations: E‐R, exposure–response; MA, meta‐analysis; MMRM, mixed models for repeated measures; NBR, negative binomial regression; PopPK, population pharmacokinetic; POR, proportional odds model; PK/PD, pharmacokinetic pharmacodynamic.

3.2.2. Analysis by Regulatory Decision Point

Modeling and simulation models were increasingly used throughout the drug development program, with a limited number of questions addressed with M&S methods for entering in Phase 1 clinical development (2%) and more extensive use after data from confirmatory trials are available for the initial MAA (Figure 4) or when bridging across indications, formulations, or dosing regimens after the initial MA.

FIGURE 4.

Successful use of M&S methods across drug development for the approved mAbs in asthma. Graphs represent the number of questions answered by regulatory decision points in initial marketing authorization application. The blue bars indicate the number of questions answered exclusively with non‐modeling and simulation methods. The orange bars indicate the number of questions answered at least one using modeling and simulation methods. The tables indicate the models used to answer these questions and the number of times a model has been used per regulatory decision points. E‐R, Exposure‐response; M&S, modeling and simulation; MA, meta‐analysis; MAA, marketing authorization application; MMRM, mixed models for repeated measures; NBR, negative binomial regression; PopPK, population pharmacokinetic; POR, proportional odds model; PK/PD, pharmacokinetic pharmacodynamic.

3.3. Credibility Assessment and Method Benchmarking

Overall, 43 different questions were (at least partially) addressed using M&S approaches in initial MAA (Table 2; Appendix S5). When M&S methods were used, they complemented traditional statistical analyses in 75% of cases. Only three questions were consistently answered using M&S methods for all the concerned drugs (Appendix S5), complemented or not with other traditional approaches such as non‐compartmental PK, descriptive, and inferential statistics. Two of these three questions consistently addressed with MIDD approaches were related to the PK characterization.

TABLE 2.

Regulatory questions commonly addressed with M&S during drug development for the five monoclonal antibodies approved for asthma treatment from 2014 to 2024.

Question	Type	Level	Drug 1	Drug 2	Drug 3	Drug 4	Drug 5	Total
What are the sources of variability in the PK exposure at population level?	PK	Population	popPK + non‐M&S a	PopPK	popPK_MA+ non‐M&S a	popPK	PopPK						5/5
What are the PK exposure metrics (AUC, Cmax, Cmin)?	PK	Population	popPK + non‐M&S a	PopPK + non‐M&S a	Comp PK + power‐law + non‐M&S a	popPK + non‐M&S a	PopPK + non‐M&S a						5/5
What is the impact of concomittant medications on the PK of the drug?	PK	Population	popPK	NA	PopPK	popPK	PopPK						4/5
What is the impact of body weight on the PK of the drug?	PK	Population	popPK + non‐M&S a	PopPK + non‐M&S a	PopPK_MA+ non‐M&S a	popPK	NA						4/5
What is the impact of disease characteristics on the PK of the drug?	PK	Population	Non‐M&S a	popPK	NA	NA	PopPK						2/5
What are the sources of variability for safety at population level?	Efficacy	Population	NA	E‐R+ non‐M&S a	Non‐M&S a	PK/PD+ non‐M&S a	Non‐M&S a						2/5
What is the dose‐response relationship at cellular level?	Efficacy	Cellular	NA	NA	PopPKPD+ non‐M&S a	Non‐M&S a	Non‐M&S a						1/5
What is the impact of body weight on the product efficacy?	Efficacy	Population	Non‐M&S a	E‐R+ non‐M&S a	Non‐M&S a	NA	Non‐M&S a						1/5

Note: Dark green boxes represent exclusive use of M&S to address the question. Light green boxes represent a combination of M&S and non‐M&S approach. Dark gray indicates that the question has been answered by non‐M&S method. Blank background indicates that the question has not been answered in the marketing authorization application.

Abbreviations: Comp, compartmental; E‐R, exposure‐response model; MA, meta‐analysis; M&S, Modeling and simulation; NA, not answered; PK/PD, pharmacokinetic‐pharmacodynamic model; popPK, population pharmacokinetic model.

^a Non‐M&S approaches include standard statistics methods such as descriptive and inferential statistics.

The use of the question‐centric approach and the related credibility assessment allowed to identify the regulatory questions alternatively addressed by MIDD and non‐MIDD approaches as exemplified in Figure 5 with the question related to efficacy characterization in adolescents. Credibility assessments per ICH M15 were implemented for questions addressed by modeling and simulation methods. To exemplify this, we selected the case of an exposure‐response model used to characterize clinical efficacy (here decrease in exacerbation rates) for the concerned mAb in adolescents (aged 12–17 years old). This model has a medium influence on regulatory decision‐making as the projection of the exacerbation rate from this model was complementary to data from two phase 3 clinical trials performed powered for efficacy characterization in adults, with much more limited data collected in adolescents. The consequence of wrong decisions is rated as high considering the disease severity as a wrong decision could lead to uncontrolled asthma. Here the regulatory impact at the time of MA was considered high for adolescents due to the lack of a fully powered confirmatory study in adolescents.

FIGURE 5.

Example of method benchmarking including credibility assessment through the ICH M15 table for assessment of MIDD evidence.

For models with medium or high regulatory impact, credibility assessment reveals various levels of maturity and therefore the regulatory acceptance was also variable across the dossiers.

4. Discussion

This article describes a critical analysis of regulatory assessment in centralized procedures through the development of a repository of key regulatory (sub‐)questions based on data‐driven interrogation of MAA including MAA related to bridging across conditions of use. This repository is built on data‐driven interrogation of scientific information and aims to provide drug developers and regulators with an integrated tool to support the decision‐making process, learn across process and therefore, contribute to adoption of alternative data types and innovative analytical methods. This approach is intended to complement the existing regulatory structures and aims to enhance transparency by providing a powerful engine for learning and promoting consistency across procedures and medicinal products. By searching the repository, regulatory assessors and drug sponsors will be able to identify data and methods used to address specific questions on previous use cases. This could therefore accelerate the effective development of monoclonal antibodies for asthma treatment, particularly in the pediatric population by reducing the current three‐year gap that often exists between approval for adults/adolescents and the subsequent approval for children aged 6–12 years, allowing earlier incorporation of pediatric information into the label. While the case study focuses on monoclonal antibodies for asthma, the repository and underlying approach are expected to be relevant to future biologics, including next‐generation monoclonal antibodies, emerging innovations such as novel delivery systems and biosimilars.

4.1. Current and Future Use of MIDD in Asthma Monoclonal Antibodies Drug Development

An analysis of the repository allows to position M&S as a method in the regulatory decision‐making landscape during development of the approved mAbs for the treatment of moderate‐to‐severe asthma. M&S methods were used to answer 39% of the questions in our repository, and hence, complementing or replacing other traditional approaches. Despite their potential multidimensional role, M&S methods were predominantly used to characterize the PK and the efficacy of the product at population level, whereas the product safety profile was mostly characterized using other traditional methods and data. A potential exists for using M&S approaches for characterizing the safety of mAbs, particularly for evaluating the risk of immunogenicity, an important concern in mAb drug development [17]. Different M&S approaches has been developed to address this concern including a quantitative system pharmacology platform and machine learning approaches [18, 19, 20, 21, 22, 23, 24, 25].

Our analysis also indicates that the M&S methods used in the drug development of monoclonal antibodies are only common approaches such as popPK, E‐R and PK‐PD models. The more recent and emerging modeling approaches, including physiologically‐based PK modeling, quantitative system pharmacology modeling, and artificial intelligence and machine learning modeling, were not applied during the development of the five drugs investigated. Notably, several researchers have already proposed physiologically‐based PK models to predict mAb PK, including mAb used in asthma treatment. In addition, Gadkar et al. developed quantitative system pharmacology model to evaluate potential treatments for severe asthma [26]. These additional modeling techniques can help at various stages of pediatric disease drug development.

4.2. Credibility Assessment and Benchmarking

Interestingly, the analysis of the repository showed heterogeneity in the use of M&S across products, with various methods and data supporting the answer to similar key regulatory questions. The underpinning assumption of the question‐centric approach is that, similarly to established data and methods, the full potential of alternative (new) data types and innovative methods can only be reached when appropriate tools for contextualizing their credibility exist and are used by drug developers and regulators. There is a need to show that the relevance and adequacy of alternative data types and innovative analytical approaches in addressing the question of interest is demonstrated. In the proposed question‐centric model, the credibility‐based assessment framework is introduced into the regulatory workflow to structure and standardize the evaluation method and the data attributes [12].

One of the objectives of this repository is to shift from current partitioned evidence generation (quality, preclinical, clinical) to a more integrated approach and support drug sponsors and regulatory assessors in drug development and assessment. Using a more integrated approach would offer the possibility to combine different types of data in an integrated assessment approach and open up more possibilities for the acceptability of alternative data types and analytical methods. However, this cannot be performed at the expense of the quality of evidence supporting benefit–risk assessment, and this is crucial to benchmark M&S approaches versus previously accepted, established or standard methods that can alternatively be used to address similar questions, based on the context of use. Therefore, key assessment elements of the table of assessment of MIDD evidence per the ICH M15 guidelines were filled for questions answered by M&S methods [27]. Subsequently, the proposed MIDD approaches were compared to alternative approaches proposed for the exact same question. One of the lessons learned by performing M&S credibility assessment is the heterogeneity of methods used and their maturity. Of note, a similar benchmarking process could also be applied between traditional methods and data and is not restricted to M&S methods.

5. Conclusions

This article describes a repository of key regulatory questions built using the question‐centric approach, centered on pediatric drug development questions relying on adequate question identification, use of appropriate data and methods and optimal method credibility assessment and benchmarking. An analysis of the repository locates the use of M&S methods and benchmark these innovative methods versus standard methods for mAbs used to treat moderate‐to‐severe asthma approved from 2014 to 2024.

Author Contributions

F.T.M., H.H. and J.‐M.D. designed the research. H.H. performed the research. F.T.M. and H.H. analyzed the data. F.T.M., H.H. and J.‐M.D. wrote the manuscript.

Funding

This work was supported by the ERAMET project, funded by the European Health and Digital Executive Agency through grant number 101137141.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1: psp470222‐sup‐0001‐Supinfo.docx.

Haguet H., Dogné J.‐M., and Musuamba F. T., “Use of Modeling and Simulation to Inform the Development of Monoclonal Antibodies to Treat Moderate‐to‐Severe Asthma: A Retrospective Review of EMA Centralized Procedure From 2014 to 2024,” CPT: Pharmacometrics & Systems Pharmacology 15, no. 4 (2026): e70222, 10.1002/psp4.70222.