PHARMACOKINETIC–PHARMACODYNAMICS MODELING IN MODERN DRUG DEVELOPMENT

Pharmacokinetic–pharmacodynamic (PK–PD) modelling is now a foundational tool in modern drug development, linking drug exposure to pharmacologic response to aid dose optimisation, efficacy, and safety. By integrating pharmacokinetics (absorption, distribution, metabolism, excretion) with pharmacodynamics (receptor-binding, dose–response, mechanistic signalling), PK–PD models enable data-driven decision-making in preclinical and clinical phases. Mechanism-based and population PK–PD approaches—including physiologically based (PBPK) and target‐mediated disposition models—allow prediction across species, disease states, and subpopulations. Regulatory agencies such as the U.S. FDA and EMA recognize model-informed drug development (MIDD) as key to trial design, dose selection and approval. Emerging advances—including artificial intelligence, quantitative systems pharmacology (QSP), and real-world data integration—are enhancing model predictive power and supporting precision medicine. This review discusses current methodologies, applications, regulatory perspectives, and future directions in PK–PD modelling, underlining its role in accelerating efficient, patient-centered drug development.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-16
DOI
https://doi.org/10.5281/zenodo.19049672
Primary Topic
Statistical Methods in Clinical Trials
Type
article
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article

PHARMACOKINETIC–PHARMACODYNAMICS MODELING IN MODERN DRUG DEVELOPMENT

Anshika Patel, Aman Singh Patel*, Aditi Srivastava, Asmit Sinha
Zenodo (CERN European Organization for Nuclear Research)
Statistical Methods in Clinical Trials
article

PHARMACOKINETIC–PHARMACODYNAMICS MODELING IN MODERN DRUG DEVELOPMENT

Anshika Patel, Aman Singh Patel*, Aditi Srivastava, Asmit Sinha
article en

Abstract

Pharmacokinetic–pharmacodynamic (PK–PD) modelling is now a foundational tool in modern drug development, linking drug exposure to pharmacologic response to aid dose optimisation, efficacy, and safety. By integrating pharmacokinetics (absorption, distribution, metabolism, excretion) with pharmacodynamics (receptor-binding, dose–response, mechanistic signalling), PK–PD models enable data-driven decision-making in preclinical and clinical phases. Mechanism-based and population PK–PD approaches—including physiologically based (PBPK) and target‐mediated disposition models—allow prediction across species, disease states, and subpopulations. Regulatory agencies such as the U.S. FDA and EMA recognize model-informed drug development (MIDD) as key to trial design, dose selection and approval. Emerging advances—including artificial intelligence, quantitative systems pharmacology (QSP), and real-world data integration—are enhancing model predictive power and supporting precision medicine. This review discusses current methodologies, applications, regulatory perspectives, and future directions in PK–PD modelling, underlining its role in accelerating efficient, patient-centered drug development.

Zenodo (CERN European Organization for Nuclear Research)
Government Medical College (IN), Rama University (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 25%
Statistical Methods in Clinical Trials
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