A new concept may help us at last abandon one-size-fits-all dosing of cancer treatment drugs


April 16, 2019

This is a lay explainer for my F1000Research paper, Dose Titration Algorithm Tuning (DTAT) should supersede ‘the’ Maximum Tolerated Dose (MTD) in oncology dose-finding trials.

What is it about?

With many medicines, it is obvious to doctors and patients alike that different people require different doses, and that we cannot predict exactly the right dose for each person before giving the first dose. Thus, a process of gradual dose adjustment over time is needed to learn what dose strikes the best balance between the good and bad effects of the medicine in each individual. Many people who take drugs for high blood pressure, low thyroid or epilepsy will recall having to adjust their dose one or more times when they first started. Certainly, many people with diabetes who inject insulin are experts in this concept, since they are actively involved with dose titration every day of their lives.

My DTAT paper is about applying this very same principle to cancer treatment drugs. Currently, a ‘one-size-fits-all’ mentality dominates dosing in oncology, and this approach gets established very early in the drug development process. The first use of most cancer drugs in humans occurs in people with cancer who have not been doing well despite having tried all standard therapies. People in this situation are often willing to try an experimental drug, even when doctors have no experience to guide them in choosing a dose. The aim of these early ‘Phase 1’ studies is conceived of as finding ‘the’ Maximum Tolerated Dose (MTD)—as if there were a single right dose for everyone. Despite its obvious flaws, this fallacy persists because statistical methods have not been available to help us see past it. The aim of this paper is to provide such methods, and to put them in a conceptual context that makes them feasible to implement in clinical trials and in clinical practice.

Why is it important?

For 2 decades, evidence has been accumulating that patients who have adverse effects from their chemotherapy actually tend to get better results from it. (Please see this public Zotero library, where I have collected a list of dozens of journal articles underscoring this point.) This is not surprising, of course, since the adverse effects experienced by these patients would also have ‘hurt’ their cancer cells—which is the whole point of chemotherapy. What this means, however, is that better ways of safely finding the strongest acceptable dose for each patient will give people with cancer their best chance to benefit from treatment. This is obviously directly important to each individual person with cancer, but it is also indirectly important for society because inadequate dosing in Phase 2 and Phase 3 clinical trials might stop good drugs from getting approved by regulatory agencies.