Abstract
Almost all pharmaceutical products are approved on the basis of their effect in patients representing the "average" of the population studied in registrational trials, with most drug labels allowing, at most, for empirical dose reduction in the case of toxicity. In this perspective article we explore some of the evidence that supports the use of personalised dosing in cancer treatment and show how we have been able to build on existing models linking dose, exposure and toxicity to demonstrate how dose optimisation, including increasing the dose, has the potential to significantly improve efficacy outcomes. We also explore, through the lens of our own experience of developing a personalised dosing platform, some of the hurdles that stand in the way of implementing a personalised approach to dosing in real world settings. In particular, our experience is illustrated by the application of a dosing platform for docetaxel treatment in prostate cancer.
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