Clario harnesses the power of AI with robust data sets and predictive analytics that truly mirror the diverse tapestry of our society.

In recent years, artificial intelligence (AI) has emerged as a powerhouse with the potential to revolutionize the collection and interpretation of endpoint data in clinical trials. Its capacity to manage vast amounts of data — from medical records to diagnostic images — while identifying underlying patterns is fundamentally transformative for the development of new therapies.

Yet, with the rapid proliferation of AI technologies in healthcare, a critical eye must be cast on health risks and potential biases that might emerge. At Clario, we are committed to helping our partners unlock richer data in their clinical trials, but gathering evidence must be accomplished in the right way. We recognize that the road to leveraging the full potential of AI is promising but it is also paved with complexities that require careful navigation as we integrate it into our technologies and solutions.

Power and Responsibility in AI

Today's medical applications of AI are primarily focused on enhancing the accuracy and efficiency of diagnoses and tailoring treatment plans. The heart of these AI tools lies in the data — more precisely, the accuracy and comprehensive nature of the data used in training the models. Predictive analytics, powered by AI, takes this a step further, analyzing past and current data trends to make future predictions about patient outcomes and trial successes.

AI is also impacting the urgent need for enhancing diversity in the recruitment and retention of clinical trial participants, to ensure trial populations match the epidemiology of the target diseases. Both inclusivity and strengthening the predictive accuracy of AI tools are essential to improving trial and patient outcomes. A comprehensive, diverse dataset ensures that AI algorithms can discern health indicators across varied demographics, marking a shift towards a universally beneficial healthcare standard.

Committing to Technologically Diverse Strategies

Collection and analysis of clinical trial data have benefited from a slew of remarkable AI-driven innovations over the past five years. In that short period of time, our scientists at Clario have developed and applied more than 30 AI-enabled solutions across our technology platform. These advancements include deploying innovative tools for real-time evaluation of radiologic images, providing quality assessments and preliminary interpretations to reduce errors, improve data quality and streamline operations. We have also formed strategic collaborations, such as a recent partnership with ArtiQ, which has enabled us to offer real-time, automated evaluations of flow-volume loop quality for improved data accuracy.

What’s more, a crucial component of our AI strategy is the emphasis on developing predictive analytics. Our data scientists are innovating powerful new models that incorporate relevant imaging and clinical data that is processed to predict population outcomes within clinical studies. By training our AI models on robust datasets, we can better predict patient responses, anticipate specific study events and help sponsors strategize enrollment, maximizing the value of each study supported.

“Our commitment to using robust datasets that mirror the diversity of the disease population helps mitigate bias, fostering trust and reliability in the AI-enabled tools we develop.”

— Todd Rudo, Chief Medical Officer, Clario