Title : Pharmacometrics: Evolution, current applications, and future horizons in drug development and personalized medicine
Abstract:
Pharmacometrics, defined as the quantitative science of analyzing, modeling, and interpreting pharmacological data, has undergone a remarkable transformation from its foundational roots in classical pharmacokinetics (PK) and pharmacodynamics (PD). Traditionally employed to describe drug concentration–time profiles and dose–response relationships, the discipline has evolved into a cornerstone of translational science and precision therapeutics. In contemporary drug development, pharmacometrics serves as an integrative framework that bridges preclinical findings, clinical trial data, and regulatory decision-making by enabling predictive, mechanism-based models. The application of pharmacometric approaches extends across the drug development continuum—from optimizing dose selection in first-in-human studies and adaptive clinical trial designs to informing benefit–risk assessments during regulatory submissions and post-marketing pharmacovigilance. Quantitative systems pharmacology (QSP), population pharmacokinetics (PopPK), and exposure–response modeling have further enhanced the ability to capture inter-individual variability, disease progression, and therapeutic outcomes in diverse patient populations. The advent of advanced computational technologies, including artificial intelligence (AI), machine learning (ML), and in silico simulations, has accelerated the predictive power of pharmacometrics and expanded its relevance to personalized and precision medicine. These tools, when integrated with systems biology, multi-omics data, and real-world evidence (RWE), are revolutionizing the rational design of therapeutic regimens and supporting the development of next-generation modalities such as biologics, biosimilars, and gene and cell-based therapies. This review highlights the historical trajectory, current landscape, and future directions of pharmacometrics, emphasizing its indispensable role in de-risking drug development, enhancing therapeutic efficacy, reducing attrition rates, and facilitating regulatory science. Furthermore, it underscores the emerging paradigm wherein pharmacometrics, synergized with AI-driven modeling and novel therapeutic platforms, is poised to transform global healthcare by delivering individualized, safe, and cost-effective treatment strategies.
