Analogous to how a geologist surveys the “lay of the land” to determine if oil lies underneath, or an investment advisor strives to understand the “lay of the land” to decide how to invest in a turbulent market, sponsors and regulators also need to determine how to best utilize and report modeling and simulation results as part of new drug applications. Modeling and simulation (M&S) plays an increasingly vital role in the development of safe and efficacious drugs. Quantitative M&S tools including population PK (PopPK), Pop PK/PD, and physiologically-based pharmacokinetics (PBPK), leveraged across drug development programs, are universally recognized for their value in optimizing key decisions related to safety, efficacy, dosing, special populations, predicting drug-drug interactions (DDIs), and others. Indeed, major global regulatory agencies, eg, US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and Japan’s Pharmaceuticals and Medical Devices Agency (PMDA), are encouraging the use of M&S.
Many analyses are conducted to support key decision-making during drug development. Prior to electronic guidelines being established by regulatory agencies for submission of M&S reports, there was uncertainty on what data should be included and how to submit it as part of the application, possibly resulting in an incomplete submission. With a growing number of regulatory submissions that include M&S to support a regulatory decision, and the need to elucidate expectations for reporting data, regulatory agencies recognize the importance of developing M&S reporting guidelines in electronic submissions of new drug applications.1,2 This is particularly important when specialized modeling software platforms are used. For example, IND submissions to the FDA require sufficient information and rationalization to substantiate dosing and dosing regimen, population and trial design, safety signals and concerns, and other parameters.3
Regulatory harmonization of M&S reporting
To understand the utility of M&S reports submitted for regulatory reviews and to harmonize practices and activities, the FDA, EMA, PMDA, and Health Canada hold regular teleconferences to exchange information and viewpoints on quantitative M&S through guidelines, workshops, and publications. In particular, use of PBPK models for predicting pharmacokinetics in clinically untested scenarios for drug applications (NDAs, BLAs, ANDAs), regulatory reviews, and post-marketing has escalated in the past several years. In 2016, this led the FDA and EMA to draft guidelines for PBPK reporting.4,5 The guidelines advised sponsors on what to include in a PBPK modeling report to allow reviewers to adequately assess the predictive performance of the drug model. As outlined in the EMA Draft Guideline Qualification and Reporting of Physiologically-Based Pharmacokinetic (PBPK) Modeling and Simulation, if PBPK modeling is intended to support a regulatory decision, the PBPK platform “needs to be qualified for the intended use and the predictive performance of the specific drug models needs to be evaluated.” Recently, the PMDA is creating a guideline on PopPK and PD analyses in Japan.6 The guideline will provide “general guidance based on current scientific knowledge to ensure that evaluations based on population analyses in drug development are appropriately conducted.”
How is PBPK being used by sponsors?
An analysis of PBPK utilization since 2014 indicates that PBPK modeling is predominantly being used to predict drug-drug interactions. This observation is consistent in reports submitted to the FDA (60%) and the PMDA (48%). Submissions to the FDA ranks pediatrics second most prevalent (16%), followed by oral absorption, organ impairment, pharmacogenetics, and others. Most notable is the increased prevalence of PBPK modeling in oncology studies.7
Good practice recommendations for model-informed drug discovery and development (MID3)
The pharmaceutical industry has also created a working group, comprised of scientists from major global pharma companies, to develop “good practice” recommendations to enable greater consistency in the practice, application, and documentation of MID3.8 The goals of the recommendations are to “inform company decision-makers how the strategic integration of MID3 can benefit R&D efficiency; provide MID3 analysts with sufficient material to enhance the planning, rigor, and consistency of the application of MID3; and provide regulatory authorities with substrate to develop MID3 related and/or MID3 enabled guidelines.”
Looking to the future—best practices in M&S reporting for regulatory reviews
The increased use of quantitative M&S across the drug development continuum by sponsors has led sponsors and regulators to develop guidelines and recommendations for more efficient reporting of model results for regulatory submissions. The adoption of these harmonized practices will result in better decision-making, ultimately leading to improved patient outcomes with the development of safe and efficacious drugs.
 US Department of Health and Human Services, Food and Drug Administration. (2014, December). Providing Regulatory Submissions In Electronic Format—Standardized Study Data Guidance for Industry. US Department of Health and Human Services Food and Drug Administration. Silver Spring, MD: Author.
 US Department of Health and Human Services, Food and Drug Administration. (2017, April). Providing Regulatory Submissions in Electronic Format—Certain Human Pharmaceutical Product Applications and Related Submissions Using the eCTD Specifications Guidance for Industry. Silver Spring, MD: Author.
 Florian J. (2017, August 3). Electronic submission of pharmacometrics data sets and reports for regulatory submissions. Presented at the Joint Statistical Meeting, Baltimore, MD.
 US Department of Health and Human Services, Food and Drug Administration. (2016, December). Physiologically Based Pharmacokinetic Analyses—Format and Content Guidance for Industry. Silver Spring, MD: Author.
 European Medicines Agency. (2016, July 21). Guideline on the Qualification and Reporting of Physiologically Based Pharmacokinetic (PBPK) Modelling and Simulation. London, UK: Author.
 Sato M, et al. (2017). Quantitative modeling and simulation in PMDA: A Japanese regulatory perspective. CPT Pharmacometrics Syst. Pharmacol. 6, 413-415.
 Yoshida K, Budha N, & Jin JY. (2017). Impact of physiologically based pharmacokinetic models on regulatory reviews and product labels: Frequent utilization in the field of oncology. Cpt-journal.com 101(5), 597–602.
 Marshall SF, et al. (2016). Good practices in model-informed drug discovery and development: Practice, application, and documentation. CPT Pharmacometrics Syst. Pharmacol. 5, 93–122.
To learn more about how modeling and simulation in drug development has evolved from being a research nicety to a regulatory necessity, read this white paper on Best Practices in Drug Development Modeling and Simulation.