
At the AI in R&D Summit, we will be gathering dedicated leaders across the globe to share experiences and the latest AI and Machine Learning techniques to increase the effectiveness in risk-based quality management, improve patient recruitment and engagement, enhance patient monitoring and safety, improve site selection, and better overall study quality and operational efficiencies – and that’s just the tip of the iceberg.
AI and Machine Learning strategies are redefining the clinical development cycle like never before. As the industry leaps into new frontiers, digital transformation is leading the way to incredible advancements that will revolutionize the space forever. At this event, you have the unique opportunity to hear from other industry colleagues about how AI and ML offer the potential to improve the success and efficiency of clinical research, increasing its positive impact on all stakeholders.
Session Highlights
Expert Panel: Digital Transformation in Clinical Trials

Stephen Lutsch
LEO PHARMA

Jen Yip

Zhaoling Meng
SANOFI
Keynote Presentation: Reducing time to market

Shameer Khader, PhD, MPH
SANOFI
AI – Powered Insights

Shams Zaman
BMS
Artificial Intelligence: History and Future

Curren Katz
JOHNSON AND JOHNSON
Top Reasons to Purchase

Utilize Artificial Intelligence (AI) technology, combined with Big Data, to solve key clinical trial challenges

Harness the power of Artificial Intelligence and Machine learning to transform how clinical trials are conceived, designed, and conducted

Learn how AI/ML strategies help ensure data integrity to meet safety and efficacy standards and pass regulatory review

Understand the role of machine learning in clinical research to help improve the success, patient-centeredness, and efficiency of clinical trials

Applying artificial Intelligence to reduce clinical trial cycle times while improving the costs of productivity and outcomes of clinical development
Speaking Faculty
Who Should Purchase
This event is developed for professionals from pharmaceutical, biotechnology and medical device companies, CROs, academia, clinical service and technology providers who have responsibilities in any the following areas:
- Artificial Intelligence (AI)
- Machine Learning (ML)
- Drug Development
- Research & Development (R&D)
- Clinical Trials, Design and Development
- Data Science
- Data Management
- Strategic Data
- Regulatory Affairs
- Pharmacovigilance
- Clinical Operations
- Patient Recruitment