title: Toxicity and Efficacy Probability Interval Design for Phase I Adoptive Cell Therapy Dose-Finding Clinical Trials.
abstract: Recent trials of adoptive cell therapy (ACT), such as the chimeric antigen receptor (CAR) T-cell therapy, have demonstrated promising therapeutic effects for cancer patients. A main issue in the product development is to determine the appropriate dose of ACT. Traditional phase I trial designs for cytotoxic agents explicitly assume that toxicity increases monotonically with dose levels and implicitly assume the same for efficacy to justify dose escalation. ACT usually induces rapid responses, and the monotonic dose-response assumption is unlikely to hold due to its immunobiologic activities. We propose a toxicity and efficacy probability interval (TEPI) design for dose finding in ACT trials. This approach incorporates efficacy outcomes to inform dosing decisions to optimize efficacy and safety simultaneously. Rather than finding the maximum tolerated dose (MTD), the TEPI design is aimed at finding the dose with the most desirable outcome for safety and efficacy. The key features of TEPI are its simplicity, flexibility, and transparency, because all decision rules can be prespecified prior to trial initiation. We conduct simulation studies to investigate the operating characteristics of the TEPI design and compare it to existing methods. In summary, the TEPI design is a novel method for ACT dose finding, which possesses superior performance and is easy to use, simple, and transparent. Clin Cancer Res; 23(1); 13-20. ©2016 AACR.
authors.affiliation: Juno Therapeutics, Seattle, Washington.
authors.forename: Daniel H
authors.initials: DH
authors.lastname: Li
authors.affiliation: Juno Therapeutics, Seattle, Washington.
authors.forename: James B
authors.initials: JB
authors.lastname: Whitmore
authors.affiliation: Laiya Consulting, Inc., Wilmette, Illinois.
authors.forename: Wentian
authors.initials: W
authors.lastname: Guo
authors.affiliation: NorthShore University HealthSystem, Chicago, Illinois. koaeraser@gmail.com.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Ji
mesh_terms: D000465:Algorithms; D064987:Cell- and Tissue-Based Therapy / Q000009:adverse effects* / Q000379:methods / Q000592:standards*; D017321:Clinical Trials, Phase I as Topic; D003198:Computer Simulation; D006801:Humans; D016219:Immunotherapy, Adoptive / Q000009:adverse effects* / Q000379:methods / Q000592:standards*; D015233:Models, Statistical; D009369:Neoplasms / Q000276:immunology / Q000378:metabolism / Q000628:therapy*; D011336:Probability; D012107:Research Design; D016896:Treatment Outcome