Can you give an overview of AiCure and its core products?
For 10 years, AiCure has been delivering AI to the life sciences industry to help guide data-driven decision-making for more meaningful clinical trials, optimized drug development, and improved business operations. We specialize in a deep understanding of patient behavior using phone-based video and audio. The company recently passed one million doses observed globally by our system, and we work in a variety of therapeutic areas including the central nervous system and psychiatry, infectious disease, internal medicine, and oncology.
AiCure’s history is rooted in one of our core applications, Patient Connect, which is a platform for measuring adherence to medications. Patients receive an alarm through a phone app reminding them to take their medication, then our computer vision technology confirms when they have ingested it. This not only provides insight into patient behavior but also connects the patient to the clinical trial site, enabling the clinician to support the patient however necessary. AiCure’s other product, Data Intelligence, mines this data to extract insights that help sponsors manage their clinical trial sites in progressing the drug.
How does Patient Connect assist an industry-wide shift towards precision medicine?
The collection of audio and video from a patient’s own home gives insight beyond simply how people take their medicine. As such, we developed an entire arm of work around digital biomarkers. Our digital biomarker solution tracks facial expressivity, voice and speech, and general movement, then applies quantitative measures to gain insights that are more comprehensive than the data one would get from infrequent clinic visits.
We designed our digital biomarkers to be easy to use, enabling researchers to shift towards using objective quantification of behavior in their analyses through digital phenotyping. This ability to structure data collection and analyzation in a secure, compliant, and appropriate manner for clinical trials will help provide insight into how people respond to their medication over long periods of time.
What are the limitations and advantages of this AI-based approach to tracking patient engagement?
AiCure’s technology allows us to approach problems in a previously unthinkable manner, bringing you into the patient’s home to experience the disease in their own environment. The technology is intuitive and can capture even more than what a doctor observes and hears when sitting across from a patient.
One challenge inherent with AI, however, is the element of bias. Diversity is at our core, and we built this in from the beginning by ensuring our data training sets mirrored the potential diversity of clinical trials, from skin tone to facial hair, fingernails, and glasses. We continue to explore our model’s performance to understand where we need to adapt to better serve the entire population.
Where is AiCure currently focusing its innovation?
We are exploring the extent to which our data can be used to develop predictive models. AiCure has already taken these steps with its dosing platform and is at a point where the platform can not only understand who is taking their medication, but also who will continue to take their medication or drop out of the trial. We are interested in expanding this towards other digital biomarkers.
Where do you see areas of growth for AI within the life sciences space more broadly?
AI is becoming extremely relevant in pre-clinical discovery work – being able to leverage genomic and pre-clinical data to improve the efficiency of the entire process of finding a molecule and testing it. AI is also relevant in real-world applications – understanding who is taking their medication and how they are actually responding. In this sense, we can use the power of AI to understand the real-world value of a drug and establish a strong foundation for personalized medication.
What is AiCure’s outlook for 2022 and beyond?
We are focused on progressing our predictive platform and seeing how far we can push the ability of making our data forward-looking, both in the domain of dosing and response.
More broadly, AiCure anticipates increased adoption of its platforms. The company has noticed heightened willingness, openness, and reliance on technology to underscore participant engagement in clinical trials, and the pandemic created the need to remain in touch virtually with trial participants while making sure they are appropriately supported. AiCure’s technology works perfectly to meet this need, and we anticipate that the increased adoption of our technology over the past two years will only continue to accelerate.