I was proud to author our “Principles for the Responsible Use of AI.” They commit us to using AI equitably, being transparent about how and when we use AI, respecting privacy rights, monitoring our use of AI to detect and mitigate risks, and monitoring the regulatory landscape in an effort to stay compliant with evolving AI laws and regulations.

Clario is one of the leading providers of endpoint data solutions to the clinical trials industry. The company develops science-driven technologies and solutions that enable pharmaceutical and biotechnology companies to collect and make sense of the high-quality data that is needed to support their drug approval submissions to regulators all over the world. Since its founding, Clario has supported clinical trials over 26,000 times. Since 2012, our clinical trial data solutions supported over 60% of all new U.S. Food and Drug Administration (FDA) drug approvals.

How are you integrating AI into your existing digital health solutions, and what benefits are you seeing?

We’ve fully integrated more than 30 AI solutions into our technology platforms and deployed them across more than 800 active trials. One simple example of what that looks like is a cardiac solution that provides AI-supported quality assessments for continuous 12-lead ECG recordings. This “quality score” tool allows for the rapid identification of poor-quality recordings. If an ECG recording is flagged, it can be addressed quickly and directly at the site while the patient is still there.

Integrating AI into our technologies is key to meeting the needs of our customers. Doing so in the right way is equally important to us. Clario follows the highest ethical principles when developing and implementing AI models. Last year I was proud to author our “Principles for the Responsible Use of AI.” These guidelines were developed with cross-functional input from numerous stakeholders across the company, including our R&D team, technology and science leaders, and quality assurance and regulatory functions. These principles guide us in all our work related to AI. They commit us to using AI equitably, being transparent about how and when we use AI, respecting privacy rights, monitoring our use of AI to detect and mitigate risks, and monitoring the regulatory landscape in an effort to stay compliant with evolving AI laws and regulations.

Can you talk about any strategic partnerships you have formed, and how they are helping to advance your goals in digital health?

A good example is our relationship with a Belgian company called ArtiQ, which leverages AI to improve the ways respiratory data is collected in clinical trials and healthcare settings.

We joined forces with ArtiQ in early 2023 and began integrating its algorithms into our spirometry devices. These devices are used to help diagnose and monitor lung conditions by measuring how much air a patient can breathe out in a single forced breath. By using the power of ArtiQ’s algorithms, we are able to provide our customers with an instant evaluation of the quality of the data generated from a patient’s exhalation. This real-time feedback improves on-the-spot analysis of the data, which in turn improves the overall efficiency of the clinical trial and improves the patient experience.

Our partnership with ArtiQ was so successful that we acquired the company earlier this year. Its founder is now our Chief AI Officer. He is already developing strategies that will help Clario to further leverage and develop innovative uses of AI across our different service lines, which include cardiac and respiratory, eClinical Outcomes Assessment (eCOA), and medical imaging.

What strategies are you using to engage patients and healthcare providers in using your digital health solutions?

We are always looking for ways to reduce the burden on patients and help our customers make their clinical trials more efficient. Our application of ArtiQ’s algorithms illustrates this nicely: If the exhalation data isn’t being analyzed in real time, and it ultimately shows an anomaly, the patient has to return to the clinic later to test again. That burdens the sick patient, who has to return to the clinic for a follow up appointment. It is also problematic for the trial’s sponsor because it can cause delays, increase costs, and cause a number of other adverse operational issues for the clinical trial. Our spirometry devices now solve for this problem by providing real-time overreads. If there is an issue with the data, the patient can be retested while still at the clinic.

Another great example of this is a medical imaging solution we offer which uses AI to automatically deidentify sensitive patient identifiers in videos, photos, and PDFs. Technicians do not have to do this scrubbing manually, it is done exponentially faster than if it were done by hand, and the use of AI more effectively protects the privacy of patients.

What are the most significant technology trends you see shaping the industry over the next few years?

At Clario, we are increasingly deploying AI models in innovative ways to advance the adoption of new and more impactful clinical trial endpoints. For example, we have built an AI-enabled algorithm to analyze full-length video recordings of colonoscopies frame-by-frame to assess the severity of inflammatory disease. Humans cannot provide the same level of accuracy and consistency at the same speed on their own.

Radiomics is also an exciting trend. Radiomics involves several steps, including image acquisition of tumors, image preprocessing, feature extraction, and model development, followed by validation and clinical application. We are exploring ways to use AI and our in-house experts to predict overall patient treatment using radiomics. These predictive tools have the potential to shorten trial duration and accelerate patient enrolment while removing patients from any therapy from which they may not benefit.

What changes/improvements would you like to see in the regulatory space to support the growth/sustainability of the industry?

I would like to see increased incentives to collaborate on data use to support innovative and ethical use of AI in the clinical trial context as well as improved confidence regarding IP protections where the development of AI algorithms is concerned.