{"id":6782,"date":"2026-05-08T18:08:40","date_gmt":"2026-05-08T16:08:40","guid":{"rendered":"https:\/\/mediconomics.com\/glossar\/modeling-and-simulation\/"},"modified":"2026-05-08T18:08:40","modified_gmt":"2026-05-08T16:08:40","slug":"modeling-and-simulation","status":"publish","type":"glossary","link":"https:\/\/mediconomics.com\/en\/glossar\/modeling-and-simulation\/","title":{"rendered":"Modeling and Simulation"},"content":{"rendered":"<p>Modeling and Simulation (M&#038;S) in pharmacological and clinical research refers to the use of mathematical models and computer-based simulations to predict the behavior of drugs in the human body, optimize study designs, and support regulatory decisions. M&#038;S is now an integral component of modern drug development and is recognized by the EMA and FDA as a regulatory tool for dose finding, extrapolation, and trial simulation. Through the targeted use of M&#038;S, costly clinical trials can be planned more efficiently, critical development risks can be identified early, and scarce resources can be deployed strategically. These advantages make M&#038;S indispensable, particularly in early clinical development and for rare diseases.   <\/p>\n<h2>Applications in Drug Development<\/h2>\n<p>Modeling and Simulation is applied across various phases of clinical development and covers a broad methodological spectrum:<\/p>\n<ul>\n<li><strong>Pharmacokinetic\/pharmacodynamic modeling (PK\/PD):<\/strong> Describes the temporal relationship between drug concentration (PK) and pharmacological effect (PD). Forms the basis for dose-finding studies and extrapolation from adult to pediatric populations as well as other special groups such as elderly patients or patients with organ impairment. <\/li>\n<li><strong>Population PK models:<\/strong> Analyze interindividual variability in pharmacokinetics according to age, body weight, renal function, genotype, and other covariates. Population PK models are standard in pediatric development programs and are explicitly required by the EMA for dose finding in children. <\/li>\n<li><strong>Clinical Trial Simulation (CTS):<\/strong> Simulates the course of a clinical trial before its execution to optimize sample size, stopping rules, patient selection, and study design. Particularly valuable for adaptive study designs, where interim analyses and adaptation rules must be tested in advance through simulations. <\/li>\n<li><strong>Disease progression models:<\/strong> Represent the natural course of disease without treatment and enable prediction of long-term therapeutic effects based on short-term study data. Particularly relevant for chronic diseases such as diabetes, Alzheimer&#8217;s disease, or multiple sclerosis, where long-term controlled trials are ethically or practically difficult to conduct. <\/li>\n<li><strong>Physiologically Based Pharmacokinetic Models (PBPK):<\/strong> Utilize physiological parameters (organ volumes, blood flow, enzyme activities) for mechanistic prediction of drug-drug interactions and behavior in special populations such as pregnant women or patients with renal impairment.<\/li>\n<\/ul>\n<h2>Regulatory Significance and Acceptance<\/h2>\n<p>Regulatory authorities increasingly accept M&#038;S as a basis for marketing authorization decisions, particularly when clinical data for certain populations are limited. The EMA has published several reflection papers and guidelines governing the use of M&#038;S in marketing authorization applications. M&#038;S has particular relevance in the following contexts:  <\/p>\n<ul>\n<li><strong>Pediatric extrapolation:<\/strong> When clinical trials in children are not feasible for ethical or practical reasons, M&#038;S can demonstrate the transferability of adult data to pediatric populations and provide regulatory support for a reduced clinical data package.<\/li>\n<li><strong>Rare diseases:<\/strong> In small patient populations, M&#038;S enables the use of historical data and external controls to support efficacy demonstration when fully randomized trials are not feasible.<\/li>\n<li><strong>Drug-drug interactions:<\/strong> PBPK models can replace or reduce clinical drug-drug interaction studies under certain conditions, provided the model is sufficiently calibrated and supported by in vitro data.<\/li>\n<li><strong>Dose adjustment in organ impairment:<\/strong> M&#038;S allows derivation of dosing recommendations for patients with impaired renal or hepatic function without requiring a separate clinical trial for each subpopulation.<\/li>\n<\/ul>\n<p>A prerequisite for regulatory acceptance is transparent model validation, comprehensive documentation of all model assumptions, and conservative assessment of model uncertainty (uncertainty analysis). The EMA recommends discussing M&#038;S plans early in scientific advice requests so that the authority can comment on the modeling strategy before final submission. <\/p>\n<h2>Relevance for clinical trials<\/h2>\n<p>M&#038;S reduces development risks and costs through early identification of ineffective dosages, inefficient study designs, and high-risk patient populations. Studies demonstrate that a significant proportion of Phase III failures can be attributed to suboptimal dose finding in Phase II\u2014a problem that can be addressed through early M&#038;S deployment in the Phase II\/III transition. Additionally, M&#038;S enables systematic evaluation of different dosing scenarios and patient subgroups before the first patient enters a confirmatory trial. Full-service CROs such as mediconomics support sponsors in preparing regulatory-compliant M&#038;S reports, developing modeling strategies for marketing authorization applications, and preparing M&#038;S results for scientific advice requests to the EMA or BfArM.   <\/p>\n<h2>Frequently Asked Questions (FAQ)<\/h2>\n<p><strong>Can M&#038;S completely replace a clinical trial?<\/strong><\/p>\n<p>Generally no. M&#038;S can supplement, extrapolate, or support clinical data, but not completely replace it. Exceptions exist in specific contexts such as pediatric extrapolation or drug-drug interaction studies, where regulatory authorities may accept M&#038;S-based submissions without an accompanying clinical trial, provided the model is sufficiently validated and transparently documented.  <\/p>\n<p><strong>What is the difference between PK\/PD models and PBPK models?<\/strong><\/p>\n<p>Classical PK\/PD models describe the behavior of a drug empirically based on concentration-time curves. PBPK models are based on physiological parameters of the organism and can mechanistically predict behavior in different populations or under altered physiological conditions. PBPK models are more complex but provide more informative results for regulatory questions concerning special patient groups such as pregnant women or patients with organ impairment.  <\/p>\n<p><strong>Which software tools are used for M&#038;S?<\/strong><\/p>\n<p>Common tools include NONMEM as the industry standard for population PK\/PD, Simcyp and GastroPlus for PBPK modeling, and R-based packages such as nlmixr2 and rxode2. For clinical trial simulations, customized R or Python scripts are frequently employed. The choice of software should be documented and justified in the modeling report, as regulators also assess the plausibility and validation of the tools used during review.  <\/p>\n<h2>Regulatory References<\/h2>\n<ul>\n<li>EMA Guideline on Reporting of Physiologically Based Pharmacokinetic (PBPK) Modelling and Simulation (EMA\/CHMP\/458101\/2016)<\/li>\n<li>ICH E9(R1) \u2013 Addendum on Estimands (2019): Relevance of simulation for sensitivity analyses<\/li>\n<li>EMA Reflection Paper on Extrapolation in Paediatric Development (2018)<\/li>\n<li>FDA Guidance: Population Pharmacokinetics (updated 2022)<\/li>\n<li>EMA Qualification Opinion on PBPK Modelling for Drug-Drug Interaction Assessments (2018)<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Modeling and Simulation (M&#038;S) in pharmacological and clinical research refers to the use of mathematical models and computer-based simulations to predict the behavior of drugs in the human body, optimize study designs, and support regulatory decisions. M&#038;S is now an integral component of modern drug development and is recognized by the EMA and FDA as [&hellip;]<\/p>\n","protected":false},"author":10,"featured_media":0,"parent":0,"template":"","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"glossary-cat":[],"class_list":["post-6782","glossary","type-glossary","status-publish","hentry"],"acf":[],"related_terms":"","external_url":"","internal_reference_id":"","_links":{"self":[{"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary\/6782","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary"}],"about":[{"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/types\/glossary"}],"author":[{"embeddable":true,"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/users\/10"}],"version-history":[{"count":0,"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary\/6782\/revisions"}],"wp:attachment":[{"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/media?parent=6782"}],"wp:term":[{"taxonomy":"glossary-cat","embeddable":true,"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary-cat?post=6782"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}