A comprehensive regulatory and industry review of modeling and simulation practices in oncology clinical drug development
Ana Ruiz-Garcı́a, Paul Baverel, Dean Bottino, Michael Dolton, Feng Yan, Ignacio Ferreira González, Jaeyeon Kim, Seth Robey, Indrajeet Singh, David C. Turner, Shu-Pei Wu, Donghua Yin, Di Zhou, Hao Zhu, Peter L. Bonate
Abstract
Exposure-response (E-R) analyses are an integral component in the development of oncology products. Characterizing the relationship between drug exposure metrics and response allows the sponsor to use modeling and simulation to address both internal and external drug development questions (e.g., optimal dose, frequency of administration, dose adjustments for special populations). This white paper is the output of an industry-government collaboration among scientists with broad experience in E-R modeling as part of regulatory submissions. The goal of this white paper is to provide guidance on what the preferred methods for E-R analysis in oncology clinical drug development are and what metrics of exposure should be considered.