Join the insightful session at RSNA 2023, featuring a critical discussion on the role of AI in oncology clinical trials, led by Divya Gupta, Chief Growth Officer at Qure.ai, and Dr. Asba Tasneem, Executive Director at Project Data Sphere. This conversation is set to delve into the advancements and challenges of integrating AI in oncology, focusing on how it can revolutionize clinical trials. Attendees will understand the current state and future potential of AI in oncology research, its impact on trial efficiency, patient selection, and the progression of cancer treatment methodologies.
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Introduction: In a fascinating conversation at RSNA 2023, the impact of AI on oncology clinical trials was explored by Divya Gupta, Chief Growth Officer at Qure.ai, and Asba Tasneem, PhD, Executive Director at Project Data Sphere. This discussion provided valuable insights into the integration of cutting-edge technology in clinical research.
Main Synopsis of Discussion: The conversation centered around Project Data Sphere's role in driving data-driven innovations in clinical oncology. They touched upon their public-private partnership with the FDA and collaborations with Pharma, Academia, and Tech partners. Key ongoing projects include data-driven analytics, external control arms, images and algorithms, and immune-related adverse events. A specific highlight was the autoRECIST initiative, aiming to develop an AI tool for aiding radiologists in image analysis and tumor growth assessment within clinical trials.
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- Data-Driven Innovations in Oncology: The importance of data-driven approaches, facilitated by AI, in enhancing oncology research was emphasized. This includes leveraging AI for analytics and project collaboration.
- AI in Clinical Trial Assessments: The discussion highlighted the development of AI tools which assist in tumor assessment and growth calculation, showing AI's potential in improving the accuracy and efficiency of clinical trial assessments.
- AI's Broader Impact on Healthcare and Clinical Research: The conversation acknowledged the growing centrality of AI in both healthcare and clinical research, noting its potential to make clinical trials faster and more efficient.
Conclusion: The session concluded with a positive outlook on the future collaboration of AI in oncology clinical trials. It stressed the potential of AI to speed up and enhance the efficiency of clinical trials, thereby advancing cancer treatment and research.
