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, and applying M‐PBPK to predict clinical PK in organ impairment populations.
Abstract
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.
This review outlines the historical development and conceptual foundations of QSP and summarizes representative clinical applications spanning early, mid, and late development, and considers emerging challenges and opportunities for QSP adoption.
Wei-Rong Wang, Alexander V. Ratushny, Steven C. Chang et al.· Journal of clinical pharmaco...· 0 citations
ABSTRACT Oncology drug development continues to have a high attrition rate despite major advances in therapeutic modalities such as antibody‐drug conjugates, bispecific antibodies, cell therapies, and cancer vaccines. Critical development decisions are often made under substantial uncertainty, creating a need for quant...
Benjamin Wu, Kenta Yoshida, P. Chanu et al.· Clinical and Translational S...· 0 citations
It is demonstrated that improving oncology drug development requires refinement of preclinical models through pharmacological humanization and biologically relevant experimental design and that accurate exposure matching between species is essential for predictive preclinical research.
Quantitative dose optimization in early phase clinical trials for investigational new drugs has been expanding across drug modalities and disease indications in response to the limitations of non‐quantitative or algorithmic methods of dose progression. In the context of the FDA's Project Optimus Initiative, which empha...
Kevin Roberts, Jeffrey Palmer, Jessica Volpe et al.· Pharmaceutical statistics· 0 citations
The convergence of medicinal chemistry and pharmacogenomics may offer a promising framework to enhance safety and precision in off-label prescribing in populations insufficiently represented in clinical trials.
Mariana Meira Scudeler, Isadora Renck Scherer, Gabriel Vaisam Castro et al.· Mini-Reviews in Medical Chem...· 0 citations
Population heterogeneity in disease biology, drug exposure and treatment response is often addressed only after development has progressed, limiting generalizability and increasing late-stage risk. We propose an anticipate-verify-influence framework to integrate clinically relevant variability from research through dev...
T. Lavé, Bruno Jolain, Ken Wang et al.· Drug Discovery Today· 0 citations
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