An adaptive two-stage dose-response design method for establishing proof of concept in drug development.

摘要

In clinical drug development, searching for the true dose-response curve is ethically and logistically challenging. Establishing evidence of dose-response or Proof of Concept (PoC) is the first step for both determining the best dose-response model and optimizing a treatment dose correctly for clinical use. To overcome these challenges, we employ an adaptive two-stage design where both adding and dropping treatment arms is possible between stages. In the first part of this dissertation, we develop a method extending the Multiple Comparison Procedures and Modeling (MCP-Mod) approach into this adaptive two-stage design. Our goal is to establish "global" PoC across the stages. Between stages, we propose using an Adding and/or Dropping Treatment Adaptation Rule (ADTAR). In the ADTAR method, dose specifications in the second stage depend on the first stage's results. Treating the unobserved doses and imbalanced aggregate sample sizes in the second stage as missing data, we derive weights and adjust the test statistics in the second stage. Specifically, we assume that the missing data mechanism caused by ADTAR is missing at random. At the end of the second stage, we perform the global PoC test combining the test results from both stages. To preserve the family-wise error rate, we use a Conditional Error Function. Using simulation studies, we evaluated our design method and compared it to a conventional (one-stage) study design and different fixed two-stage designs. Our method showed overall robust high power for detecting the global PoC across three forms of true dose-response curves. In the second part of this dissertation, we find constraints for choosing doses in the original and extended MCP-Mod methods. Specifically, we establish lower bounds of the number and levels of doses for each method using simulation studies. Our proposed method is a viable tool in searching for a dose-response relationship. In accordance with ICH guidelines, our method helps to provide optimal doses of drugs for treating or preventing different diseases. Since drugs are widely used in human populations, such methods have a great Public Health impact in appropriately treating or preventing many types of diseases.;Keywords: Adaptive Two-Stage Design, Adding and/or Dropping Treatment Adaptation Rule (ADTAR), Dose-Response Models, Proof of Concept (PoC), Multiple Comparison Procedures - Modeling Approach (MCP-Mod), Clinical Drug Development.