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Shifting a paradigm: highlights of model informed drug development in dosage selection and optimization for oncology
Ye Xiong1, Robyn Konicki1, Jeanne Fourie Zirkelbach2
1Division of Pharmacometrics, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD 20993, United States.
Abstract:
Applying model-based approaches to leverage clinical and non-clinical data can support the identification of optimized dosage(s) for oncology products and allow for a better benefit-risk balance. In oncology, conventional dose-finding studies may lead to the selection of a poorly optimized dosage into subsequent studies, including those designed to demonstrate safety and efficacy in support of a marketing application. As a result, the clinical data obtained may be insufficient to optimize the benefit-risk profile of the drug without postmarketing studies. Model-informed drug development (MIDD), which includes modeling and simulation (eg, quantitative system pharmacology, empirical or mechanistic pharmacokinetic/pharmacodynamic models), and integrative exposure-response analysis, can significantly enhance dosage selection and optimization. This review provides an update on the recent utilization and unique challenges of MIDD for dosage optimization in oncology drug development.
Insights
Model-informed drug development (MIDD) optimizes oncology drug dosage by integrating diverse data, improving benefit-risk balance. This approach enhances early dosage selection, potentially reducing the need for postmarketing studies.
Area of Science:
- Oncology
- Pharmacometrics
- Drug Development
Background:
- Conventional oncology dose-finding studies may result in suboptimal dosages, leading to insufficient data for optimal benefit-risk profiles.
- This necessitates postmarketing studies to refine drug efficacy and safety, increasing development costs and timelines.
Purpose of the Study:
- To review the recent utilization of Model-Informed Drug Development (MIDD) for optimizing oncology drug dosages.
- To highlight the unique challenges associated with applying MIDD in oncology drug development.
Main Methods:
- Leveraging model-based approaches with clinical and non-clinical data.
- Utilizing modeling and simulation techniques, including quantitative systems pharmacology and pharmacokinetic/pharmacodynamic models.
- Employing integrative exposure-response analysis.
Main Results:
- MIDD significantly enhances dosage selection and optimization in oncology.
- MIDD facilitates a better understanding of the benefit-risk balance for oncology products.
- The review synthesizes current applications and challenges of MIDD in this field.
Conclusions:
- Model-based approaches, particularly MIDD, are crucial for optimizing oncology drug development.
- Effective implementation of MIDD can lead to improved patient outcomes and more efficient drug development pathways.
- Addressing the unique challenges of MIDD in oncology is key to maximizing its potential.
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