Join Drs. Nitin Baliga and Thomas Brown for an in-depth discussion on utilizing real-world data, machine learning, and systems biology for benefiting therapeutic development.
It’s estimated that less than 5% of adult cancer patients enroll in clinical trials. Due to clinical trial eligibility criteria and access barriers to clinical trials, it is assumed that trial populations differ greatly from real-world populations. Thus, it is assumed that clinical trial results and the derived clinical evidence have limited generalizability. This creates a gap in needed data and evidence for development of novel therapeutics that will benefit the greatest number of patients, and has most certainly contributed to health care disparities. This begs the question: how can we reduce this gap?
The next installment of “Real-World Dialogues” features Nitin Baliga, MSc, PhD, Senior Vice President, Director and Professor, at the Institute for Systems Biology, and Thomas Brown, MD, MBA, Chief Medical Officer, Syapse. This conversation focuses on leveraging real-world data, machine learning, and systems biology to enable drug target discovery, drug repurposing, combinatorial therapeutics, and, ultimately, creating evidence to power life-saving decisions for patients and their families.
Key Topics Include:
- Learn how fundamental principles from systems biology are used to develop a better understanding of mechanisms of disease, potentially leading to more effective strategies for risk assessment and therapeutic interventions
- Understand how machine learning and artificial intelligence can be applied to leverage insights from real-world data to advance developmental therapeutics research and patient care
- Discover how real-world data complements and supports classical prospective clinical trials as substantial evidence in the regulatory setting
Senior Vice President, Director and Professor
Institute for Systems Biology
Chief Medical Officer
Strategy, Research and Medicine