Flexible Phase I–II Design for Partially Ordered Regimens with Application to Therapeutic Cancer Vaccines

Abstract

Existing methodology for the design of Phase I–II studies has been intended to search for the optimal regimen, based on a tradeoff between toxicity and efficacy, from a set of regimens comprised of doses of a new agent. The underlying assumptions guiding allocation are that the dose–toxicity curve is monotonically increasing, and that the dose–efficacy curve either plateaus or decreases beyond an intermediate dose. This article considers the problem of designing Phase I—II studies that violate these assumptions for both outcomes. The motivating application studies regimens that are not defined by doses of a new agent, but rather a peptide vaccine plus novel adjuvants for the treatment of melanoma. All doses of each adjuvant are fixed, and the regimens vary by the number and selection of adjuvants. This structure produces regimen–toxicity curves that are partially ordered, and regimen–efficacy curves that may deviate from a plateau or unimodal shape. Application of a Bayesian model-based design is described in determining the optimal biologic regimen, based on bivariate binary measures of toxicity and biologic activity. A simulation study of the design’s operating characteristics is conducted, and its versatility in handling other Phase I–II problems is discussed.