I’ve worked in clinical operations for decades. For decades, the transformational changes we’ve been excited about have been either incremental or cosmetic. Early in my career, for example, we transitioned from paper case report forms (CRFs) to electronic data capture (EDC). Modern studies are capturing more and more data directly from other sources, like laboratories, imaging centers or devices, avoiding time-consuming and error-prone transcription. In 2020, Tufts Center for Studies in Drug Development reported that more than 85% of sponsors are using or piloting data collection directly from non-CRF sources, including directly from electronic health records (Tufts Impact Report. 2020 Mar-Apr; 22:3).
In retrospect, the fact that these changes took as long as they did is probably something our industry should be embarrassed about. Compared to other industries, drug development and healthcare in general have been slow to adopt new technology due to risk aversion, regulatory and privacy concerns, and a general lack of incentives.
Things are different now.
The changes we’re hearing about now, however, feel quite different. Whether it’s decentralized clinical trials (DCTs), the use of “real world data” in drug submissions, or the use of electronic measurements from more patient-friendly devices including wearable digital health technologies (DHTs), the momentum and traction seem to be making real progress. Why is that?
We are finally having the whole conversation.
Past transitions to things like EDC and direct data uploads were more-or-less point solutions that solved only one aspect of the challenge. They aimed to digitize just one process or sub-process.
The clinical research enterprise has finally begun to understand the different types of data that will be needed to enable personalized medicine, DCTs or trial “matching” based on disease genetics. Connecting those different types of data, including data from DHTs, will be needed to unlock the potential of patient-focused drug development and modern study designs.
This is very well described in a Nature Medicine article, The next generation of evidence-based medicine (Jan 2023; 29(1): 49-58). The author does a great job explaining how connecting data streams across the ecosystem will be necessary to enable new study designs, and to put the patient at the center (see Fig. 3 in this article).
Collaboration has become the norm, rather than a special exception.
From my vantage point, having worked on TransCelerate’s Digital Data Flow initiative, Precision Cancer Consortium’s clinical trial matching workstream, protocol digitization and the reuse and automation of clinical documents, it’s striking that everyone is now speaking the language of interoperability and the need to make connections amongst the different data domains.
What’s also impressive is that speaking across sponsors, service providers, software vendors and patient advocacy has become a normal way of working. That was certainly not the case several years ago. Now it’s become clear that there are many things we need to collaborate on and solve together as an industry, if we are going to efficiently address the complex challenges that lie ahead.
What’s next?
I am excited and proud to work at the intersection of clinical trial protocols, digital endpoints, personalized medicine, information models, and patient centricity.
The challenges that lie ahead are about continuing to deepen the connections among these domains with an appreciation of the technical detail and the health research domain. Connecting people, concepts and organizations is something I can do well. I will continue to do that and to share my lessons and thoughts here.
Please let me know if I have raised your curiosity, or if you would like to know more.
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