Abstract Bayesian Optimal Interval (BOIN) designs are a class of model-assisted dose-
finding designs that can be used in oncology trials to determine the maximum tolerated dose …

One of the main purposes of a phase I dose‐finding trial in oncology is to identify an optimal
dose (OD) that is both tolerable and has an indication of therapeutic benefit for subjects in …

Bayesian optimal interval (BOIN) design is a model-assisted phase I dose-finding design to
find the maximum tolerated dose. The hallmark of the BOIN design is its concise decision …

One of the primary purposes of an oncology dose‐finding trial is to identify an optimal dose
(OD) that is both tolerable and has an indication of therapeutic benefit for subjects in …

In phase I trials, effectively treating patients and minimizing the chance of exposing them to
subtherapeutic and overly toxic doses are clinicians' top priority. Motived by this practical …

This article describes the R package BOIN, which implements a recently developed
methodology for designing single-agent and drug-combination dose-finding clinical trials …

Despite more than two decades of publications that offer more innovative model-based
designs, the classical 3+ 3 design remains the most dominant phase I trial design in …

Most phase I dose-finding trials are conducted based on a single binary toxicity outcome to
investigate the safety of new drugs. In many situations, however, it is important to distinguish …

One of the primary objectives of an oncology dose‐finding trial for novel therapies, such as
molecular targeted agents and immune‐oncology therapies, is to identify an optimal dose …

In the era of targeted therapy and immunotherapy, the objective of dose finding is often to
identify the optimal biological dose (OBD), rather than the maximum tolerated dose. We …