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Immunotherapeutics have revolutionized the treatment of metastatic cancers and are expected to play an increasingly prominent role in the treatment of cancer patients. Recent advances in checkpoint inhibition show promising early results in a number of malignancies, and several treatments have been approved for use. However, the immunotherapeutic agents have been shown to have different mechanisms of antitumor activity from cytotoxic agents, and many limitations and challenges encountered in the traditional paradigm were recently pointed out for immunotherapy. I propose a desirability-based method to determine the optimal biological dose of immunotherapeutics by effectively using toxicity, immune response, and tumor response. Moreover, a new dose allocation algorithm of interval designs is proposed to incorporate immune response in addition to toxicity and tumor response. Simulation studies show that the proposed design has desirable operating characteristics compared to existing dose-finding designs. It also inherits the strengths of interval designs for dose-finding trials, yielding good performance with ease of implementation., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

Background: Phase I and/or I/II oncology trials are conducted to find the maximum tolerated dose (MTD) and/or optimal biological dose (OBD) of a new drug or treatment. In these trials, for cytotoxic agents, the primary aim of the single-agent or drug-combination is to find the MTD with a certain target toxicity rate, while for the cytostatic agents, a more appropriate target is the OBD, which is often defined by considering of toxicity and efficacy simultaneously. Accessible software packages to achieve both these aims are needed., Results: The objective of this study is to develop a software package that can provide tools for both MTD- and OBD-finding trials, which implements the Keyboard design for single-agent MTD-finding trials as reported by Yan et al. (2017), the Keyboard design for drug-combination MTD-finding trials by Pan et al. (2020), and a phase I/II OBD-finding method by Li et al. (2017) in a single R package, called Keyboard. For each of the designs, the Keyboard package provides corresponding functions such as get.boundary ( ⋯ ) for deriving the optimal dose escalation and de-escalation boundaries, select.mtd ( ⋯ ) for selecting the MTD when the trial is completed, select.obd ( ⋯ ) for selecting the OBD at the end of a trial, and get.oc ( ⋯ ) for generating the operating characteristics., Conclusion: The Keyboard R package developed herein provides convenient tools for designing, conducting and analyzing single-agent, drug-combination, phase I/II OBD-finding trials., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 Published by Elsevier Inc.)