Adaptive Trials – A Reality of Clinical Trial Evolution

Adaptive trials will become a reality or even a necessity rather than just a concept. Regulatory agencies in the major markets have implemented evolving positions on adaptive clinical trial design, and information technology (IT) vendors are developing software to support adaptive designs. Adaptive design uses accumulating data to decide how to modify aspects of the study so that the right development questions can be answered more efficiently and accurately without undermining the validity and integrity of the trial. Adaptive design also provides patients participating in a trial with a greater probability of being allocated to treatment that works than in a traditionally designed trial. Much of the focus has been on statistical design of adaptive trials and impact on patient data capture, while very little has been done in terms of supporting adaptive trials from the trial management and operational perspectives. Traditionally, a study is set up when just about every step has been properly mapped out in as study protocol. Adaptive trials challenge the traditional model and call for greater flexibility on study set-up, site set-up, study design, and patient enrolment. Unfortunately, many current CTMS are built for the traditional clinical design, and only a very few CTMS vendors have started building functionalities that provide the flexibility for adaptive trial designs. One adaptive element that is not talked about in the context of adaptive trials is the ability to ‘Adapt’ and modify how trials should be ‘executed’ rather than ‘designed’ based on real-time information available on the study progress. Embedding analytics solutions in clinical applications transforms applications such as CTMS and clinical data management systems (CDMS) from being places where data are simply entered and stored to places where business intelligence is gained and actionable insights are generated by and for the end users. Embedded business intelligence will not only enhance the value of clinical systems, but also help drive end-user adoption.