DataAI National Summit’s Post

"Every breakthrough in AI is a step closer to making healthcare truly personalized, accessible, and patient-centric." Honored to be invited by Genentech, Roche, to join the AI in Clinical Trials panel at CTIS2024 hosted at Genentech's SSF Campus. I had the privilege of sharing the stage with distinguished leaders, including Paquita Chang (Moderator), Genentech, Shun Zhang, AstraZeneca, Mukul Virmani, Gilead Sciences and Katherine Wang, Palantir. Together, we explored AI's promise and challenges in streamlining clinical trials, improving patient engagement, and accelerating life-saving treatments. Today, AI is transforming clinical trials by making them smarter, faster, and more patient-focused. Here are the top 7 takeaways in ways AI is reshaping the clinical trial landscape: 1) Patient Recruitment and Matching AI algorithms scan large datasets, including health records and genetic data, to swiftly identify qualified trial participants, boosting enrollment rates while cutting screening times. 2) Protocol Design Optimization By analyzing data from thousands of past studies, AI helps design more targeted protocols, optimizing for the best-fit patients and enhancing trial success rates. 3) Real-time Data Analysis AI tools excel at real-time data analysis, revealing patterns in the increasing volume of trial data. This improves decision-making and reduces time to insight. 4) Patient Retention and Engagement AI-driven virtual assistants offer round-the-clock support, responding to participant questions and concerns, which builds trust and keeps engagement high. 5) Adaptive Trial Design AI enables adaptive protocols that adjust based on real-time data, allowing for optimized dosage levels and treatment durations, leading to better outcomes. 6) Predictive Analytics for Dropout Prevention Machine learning identifies patterns linked to early withdrawal, helping researchers implement strategies to reduce dropout and maintain trial continuity. 7) Personalized Communication AI customizes communication plans based on individual preferences, enhancing engagement and making participants feel valued and involved. Taken together, by harnessing these capabilities, AI is helping to make clinical trials more efficient, cost-effective, and patient-centric, paving the way for faster and more innovative therapies. Thank you to everyone who joined and to my fellow panelists for a vibrant and insightful discussion! Excited for what lies ahead as we continue innovating to bring precision, speed, and accessibility to healthcare. #AI #ClinicalTrials #Innovation #Healthcare #PatientCentric #CTIS2024 #FutureOfMedicine #HealthcareInnovation Paquita Chang, Genentech, Roche Shun Zhang, AstraZeneca, Mukul Virmani, Gilead Sciences Katherine Wang, Palantir Technologies #PrecisionMedicine #Genentech #Roche #GileadSciences #Palentir #AstraZeneca Agility Pharmaceuticals American Association for Precision Medicine (AAPM) #AAPM_Health #AAPMHealth #News