Model‐Informed Decision Making from Drug Discovery to Reimbursement: A Roadmap for Clinical Pharmacology in Value‐Based Healthcare

Abstract

The transition to value‐based healthcare demands more efficient, evidence‐driven approaches to drug discovery, development and medical use. Clinical pharmacology is uniquely positioned to support this shift through model‐informed drug development (MIDD) decision‐making, integrating quantitative methods across the product lifecycle. This commentary outlines a roadmap for embedding MIDD from early drug discovery through regulatory evaluation and ultimately into reimbursement and real‐world use. We highlight how pharmacokinetic/pharmacodynamic modeling, mechanistic modeling, disease progression models, patient‐relevant endpoints, and real‐world data will inform dose selection, optimize trial design, and reduce uncertainty in benefit–risk and cost‐effectiveness assessments. Emphasis is placed on cross‐stakeholder alignment, including regulators, payers, clinicians, and industry, to ensure that model‐informed evidence translates into demonstrable patient and economic value. Key challenges, such as data integration, model transparency, and acceptance by decision‐makers, are discussed alongside practical solutions. By advancing a lifecycle‐based, quantitatively informed framework, clinical pharmacology can play a central role in delivering therapies that are not only safe and effective but also aligned with the principles of value‐based healthcare.