Future of Clinical Trials: Forging New Pathways with Artificial Intelligence  

Biocom California’s first annual Converge Summit, recently held in South San Francisco, brought together life science leaders and executives to exchange ideas, foster collaboration, strengthen relationships, and spark innovation. When we think of innovation for this industry, the topic of Artificial Intelligence (AI) in clinical trials has steadily gained momentum, particularly around the opportunities and precautions that accompany its advancement. 

April Purcell, Clinical Development and Operations Consultant at Halloran, joined the panel, “The Future of Clinical Trials: Forging New Pathways Through Regulatory,” alongside other industry experts: Charles Fisher, Founder and CEO of Unlearn.AI, Ryan Moog, Head of Life Sciences Solutions at Datavant, Tim Scott, President and CEO of AustinPx, and Scott Skellenger, VP, R&D Informatics and Global Infrastructure Services at Amgen. 

Listening to this panel, four key insights resonated with me, particularly because we often field similar questions from our clients at Halloran on how best to leverage Artificial Intelligence in the clinical development lifecycle.  

How Do You Get New Technologies, like AI, Approved for Use in a Clinical Trial by the FDA? 

The U.S. Food and Drug Administration (FDA) remains committed to ensuring that drugs are safe and effective as new innovations in clinical trial technology continue to develop. As with any innovation, AI and Machine Learning (ML) create opportunities for efficiency and improvement while also presenting new challenges and risks. As such, the FDA has accelerated its efforts to create an agile regulatory ecosystem to facilitate innovation with patient safety at the forefront. We’ve seen this in their collaboration with the Center for Drug Evaluation and Research (CDER), the Center for Biologics Evaluation and Research (CBER), and the Center for Devices and Radiological Health (CDRH), particularly in their recent white paper published in March 2024, providing greater transparency regarding how FDA’s medical product centers are safeguarding public health while still fostering responsible and ethical advances with Artificial Intelligence in clinical trials. There is support, and the FDA has shown itself to be a true partner in the industry. 

That’s the key, though – responsible and ethical innovation. The panelists at the Converge Summit underscored this sentiment, echoing the importance of responsible and ethical innovation. April emphasized, “Clinical trial sponsors must focus on their data integrity and validation approaches, as well as develop a risk-management plan with their use of AI. The sponsor must have transparent processes and plans in place.” 

How Do You Validate AI-Enabled Tools for Use in Clinical Trials? 

April stated, “The unknown with AI tends to be around the results from the model. As a result, the sponsor must go through all the essential and critical validation steps to provide clarity to the FDA, including transparency around their validation processes and assessments, transparency with the model, and the results must be reproduceable.” 

The FDA is pinpointing that you need to prove your algorithm is accurate and reliable and validated from a compliance and clinical perspective. When you have all those steps in place, that’s when you’re able to validate your trial. 

In What Ways Can Trials Benefit from the Use of AI Technology? 

• Shrink the time to market cycle for medications, ultimately getting drugs faster to patients. Ryan Moog at Unlearn.AI shared the example of removing the need for placebo control groups by generating digital twins for participants receiving investigational intervention, thereby reducing overall enrollment timelines and extent of recruitment efforts 
• Improve accuracy and specificity of patient medical history and identify eligible participants by enabling easier aggregation of extensive data sources (i.e. clinical data, claims data, and patient registries) 
• Identify trends in successful study design that encourage patient engagement and reduce barriers leading to dropout 

Can AI Really Assist with Inclusivity in Clinical Trials? 

Absolutely – the use of Artificial Intelligence in clinical trials has the proven ability to reach more diverse populations, enable targeted outreach for underserved communities, propel patient engagement, and even reduce bias in clinical trial design. The benefits are huge. 

One example is the use of Natural Language Processing (NLP) in the development of Informed Consent Forms (ICF) and other participant recruitment materials, which can help sponsors match the language and style to specific patient populations and remove barriers to reach a more diverse participant pool. This also works to the benefit of patients, increasing their access to clinical trials by offering a greater sense of trust and approachability.    

What is the Future of Clinical Trials with AI? 

“It’s certainly not possible to predict the future, but what I know is that everything and anything is possible in our industry. If we can dream it, we can make it happen,” shared April. The role of AI in drug development cannot be underestimated in the long term.  

If you are assessing your AI approach or don’t know where to begin, contact a member of our team today. We’re here to partner with you on your most pressing opportunities and challenges.