Innovative Clinical Pharmacology, Modeling, and Simulation Strategies for Accelerating Rare Disease Drug Development

Clinical drug development for rare diseases continues to face significant challenges due to disease heterogeneity, fewer available patients, and incomplete understanding of pathogenesis, resulting in trials with limited clinical data, thus constraining traditional development pathways. Clinical pharmacology, modeling, and simulation-based approaches can help address these challenges by informing decision-making, mitigating uncertainty, and guiding optimal dose and regimen selection for the appropriate patient population. These approaches help streamline trial designs by reducing the scope and number of clinical trial evaluations, using exposure-response analyses to optimize dosing, the use of mechanistic-physiologically based pharmacokinetics (M-PBPK)-based approaches for biopharmaceutical and formulation optimization, evaluations of drug-drug interactions, and organ impairment. These strategies increase development efficiency across all stages of drug development, thereby improving the probability of success. This review highlights case studies that applied innovative clinical and quantitative pharmacology approaches across early and late stages of drug development and regulatory decision-making in rare diseases. The specific examples illustrate the application of pharmacokinetics/pharmacodynamics (PK/PD) and model-informed drug development (MIDD) strategies to support dose and regimen selection, enabling efficient use of direct or adaptive trial designs, facilitating bridging across populations and indications, biopharmaceutics-based transitions, and generating integrated PK/PD evidence to support labeling. Examples include drug repurposing, characterizing PK/PD in early phase to inform late-phase development, population PK analysis to guide trial dosing and label recommendations, using phenotype-targeted study design to address disease heterogeneity, expanding dosing regimen across indications using MIDD, quantitatively evaluating immunogenicity to support mitigation strategies, biomarker bridging, and applying M-PBPK to predict clinical PK in organ impairment populations.