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An Adaptive Two-Stage Dose-Response Design Method for Establishing Proof of Concept in Drug Development

Tanaka, Yoko (2011) An Adaptive Two-Stage Dose-Response Design Method for Establishing Proof of Concept in Drug Development. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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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.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairAnderson, Stewartandersons@nsabp.pitt.eduSJA
Committee MemberWahed, AbdusWahedA@edc.pitt.eduWAHED
Committee MemberSampson, Allan Rasampson@pitt.eduASAMPSON
Committee MemberBertolet, Marniebertoletm@edc.pitt.eduMHB12
Date: 31 January 2011
Date Type: Completion
Defense Date: 17 September 2010
Approval Date: 31 January 2011
Submission Date: 14 October 2010
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Biostatistics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Clinical Drug Development; Dose-Response Models
Other ID:, etd-10142010-124612
Date Deposited: 10 Nov 2011 20:03
Last Modified: 15 Nov 2016 13:50


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