TEPI-2 and UBI: designs for optimal immuno-oncology and cell therapy dose finding with toxicity and efficacy

J Biopharm Stat. 2020 Nov 1;30(6):979-992. doi: 10.1080/10543406.2020.1814802. Epub 2020 Sep 20.

Abstract

Conventional dose finding designs in oncology drug development target on the identification of the maximum tolerated dose (MTD), with the assumption that the MTD has the most potential of clinical activity among those identified tolerable dose levels. However, immuno-oncology (I-O) and cell therapy area, may lack dose-efficacy monotonicity, posing significant challenges in the statistical designs for dose finding trials. A desirable design should empower the trial to identify the right dose level with tolerable toxicity and acceptable efficacy. Such dose is called as optimal biological dose (OBD), which is more appropriate to be considered as the primary objective of the first-in-human trial in I-O and cell therapy than MTD. We propose two model-assisted designs in this setting: the toxicity and efficacy probability interval-2 (TEPI-2) design and the utility-based interval (UBI) design that incorporate the toxicity and efficacy outcomes simultaneously and identify a dose that has high probability of acceptable efficacy with manageable toxicity. The proposed designs can generate decision tables before trial starts to facilitate practical and easy-to-implement applications. Through simulation studies, our proposed novel designs demonstrate superior performance in accuracy, efficiency, and safety. Additionally, they can reduce the number of patients and shorten clinical development timeline. We also illustrate the advantages of proposed methods by redesigning a CAR T-cell therapy phase I clinical trial for multiple myeloma and summarize our recommendations in the discussion section.

Keywords: Bayesian optimal interval; Immuno-oncology; cell therapy; optimal biological dose; toxicity efficacy probability interval; utility-based interval.

MeSH terms

  • Bayes Theorem
  • Cell- and Tissue-Based Therapy
  • Computer Simulation
  • Dose-Response Relationship, Drug
  • Humans
  • Maximum Tolerated Dose
  • Multiple Myeloma*
  • Research Design*