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Activity Number: 416 - Clinical Trial Design- 4
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract #329394 Presentation
Title: Dose Finding Model Selection in Oncology Combination Therapy
Author(s): Lixia Pei* and Yichen Guo and Kevin Liu
Companies: Janssen Pharmaceuticals and Harvard University and Janssen Pharmaceuticals
Keywords: dose finding; CRM; Bayesian; drug-drug interaction; Phase I clinical trial

In Oncology First-in-Human (FIH) single drug dose finding trials, the model-based approach Continuous Reassessed Method (CRM) is often used due to its efficiency and flexibility. A combination therapy is a therapy that uses more than one medication. In a combination dose finding trial, CRM Bayesian model allows an easy incorporation of the prior single drug dose finding trial information in the combination dose finding model, but the potential drug-drug interaction may also need to be considered in the model. The pre-information of interaction effect is usually quite limited prior to a phase I trial. Therefore, we aim to investigate whether the interaction effect can be ignored in the statistical model, under a variety of interaction and dose-response scenarios. We find that the interaction effect can be ignored in most of the realistic settings. But when the interaction effect is extremely high, a complicated model with interaction parameter works much better. In the presentation, we will also advise the run-in approach, which pre-specify the dose escalation path. Before observing any dose limiting toxicity (DLT), this rule-based run-in path is suggested to be used.

Authors who are presenting talks have a * after their name.

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