Consider the problem of finding the dose that is as high as possible subjec
t to having a controlled rate of toxicity. The problem is commonplace in on
cology Phase I clinical trials. Such a dose is often called the maximum tol
erated dose (MTD) since it represents a necessary trade-off between efficac
y and toxicity. The continual reassessment method (CRM) is an improvement o
ver traditional up-and-down schemes for estimating the MTD. It is based on
a Bayesian approach and on the assumption that the dose-toxicity relationsh
ip follows a specific response curve, e.g., the logistic or power curve. Th
e purpose of this paper is to illustrate how the assumption of a specific c
urve used in the CRM is not necessary and can actually hinder the efficient
use of prior inputs. An alternative curve-free method in which the probabi
lities of toxicity are modeled directly as an unknown multidimensional para
meter is presented. To that purpose, a product-of-beta prior (PBP) is intro
duced and shown to bring about logical improvements. Practical improvements
are illustrated by simulation results.