Keywords: dose optimization, oncology
Dose-finding in oncology is often focused on the maximum tolerated dose(MTD) which is usually defined based on the rate of dose limiting toxicities observed during the first one or two months of exposure. Various designs (e.g. BLRM, continual re-assessment) are used to optimally define the MTD. A dose close to the MTD or maximum administered dose is subsequently expanded to achieve proof-of-concept. Once proof-of-concept has been achieved, registration studies are often designed to study one dose-regimen; patients start at the selected dose-regimen with adjustments based on tolerability. Thus one dose near the MTD is characterized extensively across different indications and combinations with very limited data available for other starting doses. Dose justification frequently relies on dose-exposure-response modeling. The selection of a dose near the MTD favors selection of a steep region of the exposure-safety curve for events leading to dose limiting toxicities. Efficacy may be impressive but the relatively narrow range of exposures studied may make it difficult to demonstrate an exposure-efficacy relationship. With therapies that are truly breakthrough, rapid delivery to patients can transform lives. How can we marry the urgency in oncology drug development with the need to explore a broader range of doses and regimens? Are there alternative strategies (development, study design, modeling) that can allow us to more efficiently characterize dose-exposure-response relationships to more effectively select dose and regimens? When should dose optimization occur?