Software-Enabled Clinical Trials

Software-Enabled Clinical Trials

Healthcare companies that support clinical trials have been famously slow to adopt technological innovations. Many research sites still use physical protocol binders, paper diaries, and decade-old software.

That tide is starting to turn as more companies across the clinical trial value-chain incorporate software into their product offering. A recent study found that 64% of researchers have used digital health tools in their clinical trials, and 97% plan to use these tools in the next 5 years.

The goal of this post is (1) to highlight new software tools that support clinical research across the value chain, and (2) to provide perspective for two emerging innovations: virtual trials and the rise of digital biomarkers.

Virtual or “siteless” trials are conducted outside of the site or clinic – and in the participant’s home. Digital biomarkers, as described by Rock Health, are consumer-generated digital tools that collect behavioral and physiological data (e.g., clinically-validated wearables and sensors).

Sponsors conducting virtual trials often reference four benefits:

  1. Cost. Virtual trials can cost half as much per participant compared to a site-based trial.
  2. Recruitment. They can increase recruitment rates and diversity by making it more convenient to participate in trials.
  3. Data. Using digital tools (e.g., digital surveys and sensors), a Sponsor has many more touch-points with the participant during the trial. For example, if a participant comes into a site a few times a month, the Sponsor can collect ~50 hours of data on the participant. However, if data can be collected passively at home, nearly 4000 hours of data can be collected – a 75x increase. Furthermore, the data collected from a participant’s natural environment are more “real-world” than site-collected data.
  4. Clinical-applicability. As we all know, more data doesn’t always mean better data – or improved outcomes. Nevertheless, in the past few years, new algorithms and approaches are assisting researchers to make sense of and use this data and apply the results clinically. For instance, AliveCor and Cardiogram take thousands of heart-rate measurements at home and can predict abnormal heart conditions like atrial fibrillation with 97% accuracy.

Of course, with any new technology, there are solvable challenges (e.g., data quality, ownership, security). With the rise of computing power and the FDA’s revised stance on digital tools, this software-enabled tide is rising. We are poised for a paradigm shift in clinical research.

You can read the rest of the blog post here.

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