How AI helps us with patient insights

Interview with Dooti Roy

Everybody talks about AI, but where are the actual use cases? In the episode today, I’m talking with Dooti Roy about AiCure.

AiCure uses an easy-to-use, proprietary AI platform to directly engage and provide support to patients via smartphones to deliver meaningful, high-quality data around patient behavior.

Real-time patient data facilitates better decision-making.
Real-time access to patient data helps inform safety and efficacy results.

Through the ePro features and functionality within the Patient Connect app, AiCure makes it simple for patients to chronicle their symptoms, providing insight beyond adherence alone. 

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Adherence Data – Importance Beyond Efficacy and Safety

Patient medication adherence is extremely important for ensuring the high quality of data throughout the course of a clinical trial. AiCure’s customers rely on an adherence solution through the Patient Connect app to collect dosing data, but the value doesn’t end there. Not only does the app, via it’s reminders and easy to follow dosing guidance, help to increase patient adherence, it also provides 24/7 visibility for the study team, giving them clear insights into what’s happening with their patients in between clinic visits.

This round-the-clock data collection produces other benefits. Through the proprietary AI, AiCure offer sponsors predictive analytics that can be shared with potential customers following the study. These analytics can show a range of potential patient benefits, such as:

  • Performance of the therapy over time
  • Likelihood of side-effects

AiCures Digital Biomarkers use facial and voice recognition, collected with a smartphone or similar device, to help flag symptom changes – many of which can be extremely subtle. Ranging from the obvious, like detecting jaundice, to nearly imperceptible changes in facial or voice affect, characteristics picked up by the app tell us a lot about how patients are being affected by the therapy. By utilizing these biomarkers, data is collected that can show (among other things):

  • Improvements in pain
  • Changes in mobility
  • Occurrence and changes to tremors and other neurological responses

In this episode, Dooti and I talk about the following:

  • How do you see the role of smartphone apps in clinical studies developing?
  • What additional features become possible with such applications?
  • Where does this impact studies?
  • How will this change the way we analyse studies?

Dooti Roy, PhD

Dooti is a global product owner and a principal methodology statistician who enjoys developing/deploying innovative clinical research and statistical visualization tools with expertise in creating dynamic cross-functional collaborations to efficiently solve complex problems. She is currently focused on research and methodological applications of Bayesian statistics, artificial intelligence and machine learning on clinical efficacy analyses, patient adherence, and dose-finding. She is passionate about promoting diversity and inclusion, mentoring, cross-cultural collaborations, and competent leadership development. She unwinds with painting, reading, traveling and heavy metal.

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