As the name would imply, Real World Data, embodies the ability to capture treatment effectiveness as an extension to the efficacy data that is produced in RCTs. The distinction between efficacy and effectiveness is an important one as efficacy can be seen as a necessary, but not sufficient, condition for real world effectiveness of medicines. Once controlled trial conditions have been relaxed in real world settings in favor of the myriad expressions of the patient disease profile, often with incumbent comorbidities, and spanning the disease severity spectrum, a somewhat different treatment response may emerge.

The increasing availability of electronic medical records and other sources of Real World Data have transformed the ability to assess usage of marketed products, and sequela of practical applications. It also provides opportunities to assess the use and effectivenss of products in rare diseases. Especially modern targeted agents may have applications in areas not initially targeted. For example, in oncology, many malignancies have low incidence rates making classical or adaptive RCT practically infeasible. Yet, many such rare diseases have bad prognosis.

While Real World Data allow tracking of clinical practice experience with safety and effectiveness in rare diseases, the availability of clinical experience with Real World Data is still far from a labeled efficacy claim. The landscape of regulatory decision involves intricacies that Real World Data may not provide satisfactorily, or not provide at all. While regulatory hurdles may be satisfied with randomized (or non-randomized) clinical trials, the complexity of such trials in rare diseases, with few or no treatment options, may prevent its timely and efficient execution.

In this round table discussion, we would like to discuss elements of Real World Data, opportunities and challenges for use of Real World Data in regulatory submission, biggest hurdles for Real World Data, other uses of these data.

Coen Bernaards and Gillis Carrigan, Genentech, Inc.