The use of real world data for the research, development and evaluation of oncology precision medicines

Abstract

Although randomized controlled trials remain the scientific ideal for determining the efficacy and safety of new treatments, they are sometimes insufficient to address the evidentiary requirements of regulators and payers. This is particularly the case when it comes to precision medicines because trials are often small, deliver incomplete insights into outcomes of most interest to policymakers (e.g. overall survival) and may fail to address other complex diagnostic and treatment related questions. Additional methods—both experimental and observational—are increasingly being used to fill critical evidentiary gaps. A number of modified early and late phase trial designs have been proposed to better support earlier biomarker validation, patient identification and selection for regulatory studies but there is still a need for confirmatory evidence from real world data sources. These data are usually provided through observational, post approval Phase 3b and 4 studies, which rely heavily on registries and other electronic data sets—most notably obtained data from electronic health records (EHRs). It is, therefore, crucial to understand what ethical, practical and scientific challenges are raised by the use of EHRs to generate evidence about precision medicines.