Expert Weights in On Reinventing Clinical Trials through AI Implementation

Gaurav Josan is a transformative leader with more than two decades of experience in the Life Sciences industry leading strategic technology initiatives. She leads the Research & Development team at Clario as Sr. Vice President focused on innovation and next-generation technology solutions. She is passionate about utilizing AI in a responsible and meaningful way to accelerate clinical trials, with a focus on improving patient outcomes. She is a strong advocate for women in leadership and is committed to promoting diversity to tap into the best talent across the globe.

In an insightful interaction with Global Woman Leader Magazine, Gaurav shares her insights on the future of AI in healthcare, exploring its transformative potential in clinical trials, regulatory challenges, and the leadership qualities needed to drive innovation across global, AI-focused teams.

As the industry embraces AI-first solutions in clinical trials, how do you envision AI transforming healthcare and technology? What key barriers could impede this transformation?

AI has huge potential to accelerate clinical trials and impact healthcare and patient lives over the next 3-5 years. To ensure a new drug is effective and safe, multiple data endpoints must be analyzed before a drug can be submitted for regulatory approval. Over the last decade, trials have grown more complex with an average of 3.6 million data points per Phase III trial. With so much data to analyze, AI can streamline key steps, enhance data quality, and accelerate clinical trials.

Key barriers remain: AI is only as good as the data it’s trained on. Access to appropriate training data, and willingness to share fully deidentified data, is critical to advancing AI solutions. The regulatory landscape for AI is also evolving rapidly. As part of this evolution, regulators must balance oversight with supporting responsible innovation, ensuring regulations increase confidence and empower progress.

Accelerating clinical trials with AI often requires navigating strict regulatory frameworks. How do you strike a balance between fostering innovation and meeting these requirements?

The life sciences industry is governed by regulatory frameworks for a good reason. The global AI regulatory landscape is evolving rapidly, and it is crucial to continue to monitor changes in regulations closely and comply with existing regulations as well as new regulations as they come into effect. I am a big promoter of the responsible and ethical use of AI in clinical trials. At Clario, we have worked closely with our Legal and Science teams to develop “AI Responsible Use Principles.” We follow these principles while developing and utilizing our proprietary AI models. They guide us in minimizing bias, ensuring accountability, upholding patient privacy, and integrating human oversight into development and use of our AI solutions.

Implementing AI in clinical trials on a global scale involves diverse teams with varied cultural and geographical perspectives. How do you turn these differences into strengths to drive AI innovation?

In today’s world, we have access to global talent, which is a boon to driving innovation and AI. Diverse cultures and geographic perspectives lend complimentary skills to projects and propel innovation when utilized as part of an effective team. I have teams based in North America, Europe, and Asia, and over the years, I have learned that it’s the multi-regional teams that are most successful and productive. I have also found that if goals are clearly defined, having a global team increases productivity, reduces resolution time for any issues that arise, provides effective support, and increases quality of deliverables. The key isa flow of effective communication throughout the team to ensure strong collaboration and a commitment to common goals.

With your experience in domains like Cardiac, Imaging, and Respiratory, how has AI contributed to optimizing the global rollout of clinical trial technologies?

AI models can be deployed to run automatically at a global scale. We integrate AI at various steps in the clinical trial process for Cardiac, Imaging, Respiratory, and eCOA to ensure the quality of the data. AI helps analyze that data directly at the acquisition site with near real time feedback, allowing for corrections before being sent to the central core lab. This reduces the burden on sites and patients, and further streamlines the trial process by significantly reducing the back and forth between the site and the central lab. For example, the accuracy of spirometry data is dependent on patient effort during testing.AI delivers real time feedback on data quality, enabling immediate retesting if needed. This ensures more accurate endpoints.

What leadership qualities are essential for building and scaling global teams to reinvent clinical trials with AI?
Implementing meaningful AIto streamline clinical trials requires cross-functional teams to work in concert.AI differs from typical software development since its accuracy depends on training data available for a specific use case. A proof of concept is key to deciding whether AI is the best solution by weighing accuracy, feasibility, and cost. Based on the dynamic nature of development with AI, cross functional collaboration, open mindedness, fast decision making, promoting innovation and adaptability, and pivoting quickly are key factors for success in building and scaling global teams.

How do you cultivate a culture of innovation and adaptability across geographically dispersed teams working on transformative AI initiatives?

Innovation and adaptability are cornerstones for achieving success in deploying meaningful AI. As leaders, we must embed these key elements into the team culture. Fostering strong communication and collaboration is vital, but building trust and psychological safety matters most.  AI development is unlike typical software development, requiring more experimentation and open communication without the fear of organizational hierarchy. Establishing clear processes and guidelines and empowering teams with autonomy to make decisions and manage their own work is key. Aligning a global team to a shared vision is critical along with celebrating successes and milestones. I see geographically dispersed teams as an advantage and by encouraging diverse perspectives, we fuel innovation.