Most oncology teams are working feverishly to deliver medicines to patients quickly and safely, yet numerous inefficiencies slow them down. Advances in oncology need to be matched by advances in the clinical systems supporting those trials.
Immuno-therapies have advantages over traditional chemotherapy. They are less toxic, can address hard-to-treat cancers, and provide a durable response that in some cases lasts years after treatment ends.1 They are also complicated to study as their efficacy varies in different settings, combinations, and treatment lines.
Research to maximize the efficacy of a treatment requires testing different combinations of drugs and different dosages, across different biomarkers. The resulting study designs are increasingly complicated, and the trend will continue.
Adaptive trial designs, such as dose-finding, biomarker-adaptive, and treatment switching designs, are not new, however they present logistical and programming challenges that serve as an impediment to adopting these more efficient study designs.
For years, EDC technologies haven’t kept pace with innovations in trial designs. Companies end up programming complex and fragile work-arounds because traditional EDC systems are unable to support their requirements.
This paper outlines common challenges when building databases for oncology studies and how a modern EDC equips you to build the studies you want, without limitations from technology.