Why the minimum effective dose is unidentifiable - and how a DOR→OOD standard delivers label-ready dosing in oncology

Oncology dose optimization has moved beyond the maximum tolerated dose paradigm, yet many programs still implicitly target a threshold-style minimum effective dose (MED). In serious cancers, deliberately sub-therapeutic comparators are rarely ethical or approvable, so any sharp MED threshold is typically a fragile and only partially identifiable target. We propose a statistical and operational framework that reframes dose-finding as region-based optimization. First, we define a constraint-based Dose Optimization Region (DOR) where clinically meaningful benefit (potentially multi-endpoint and PD-informed) is credible, unacceptable toxicity is bounded, exposure targets are attainable within a prespecified window, and implementation is feasible. Second, within the DOR, we identify an Operational Optimal Dose (OOD) - a label-ready dosing strategy that integrates dose, schedule, exposure targets, and adjustmentrules - using comparative evidence across binary and time-to-eventendpoints, exposure - response (PK/PD) analyses, and time-to-event methods that account for delayed effects where follow-up allows. This approach turns regulatory evidence domains into region-definingconstraints and shifts the target from a single-point estimate to a strategy-level deliverable. It is intended to sit on top of conventional dose-finding designs and PK/PD modeling as a region-defining and reporting standard, rather than to replace existing methods. We illustrate its use with small-samplevisualizations based on pairwise superiority probabilities across in-region arms and with a real-world-inspired example to show how DOR→OOD can summarize the totality of evidence in practice. The framework provides statisticians and clinicians with practical design patterns and reporting checklists, aligning with contemporary regulatory expectations and supporting dose optimization in oncology, with potential adaptation to other therapeutic areas.