In this episode, Tommaso Mansi, Vice President, AI/ML and Digital Health, R&D, The Janssen Pharmaceutical Companies of Johnson & Johnson talks about the development of AI approaches to the development of medications and treatments for specific diseases with the help of digitized biomedical data.
He discusses how data and AI can help in clinical trial accessibility, drug efficacy prediction, site selection, and patient identification, which can significantly help healthcare when facing struggles from within. Tommaso shares the importance of having proper data governance in the research lab and why humans will always be necessary to produce breakthroughs in partnership with AI.
Tune in and learn more about AI’s role in data in R&D!
Artificial intelligence, machine learning, and data science’s positive impact on the Pharma industry and patients are astounding.
About Tommaso Mansi:
Dr. Tommaso Mansi is VP of Artificial Intelligence (AI) and Digital Health, Data Science, at Janssen R&D. He holds a Ph.D. in biomedical engineering from INRIA Sophia Antipolis, France. Afterward graduating, Dr. Mansi worked at Siemens Healthineers, Digital Technology, and Innovation, where he took roles of increasing responsibility and eventually led a team focusing on the development and translation of AI solutions for image-guided therapy and robotics. He then joined Janssen R&D, Data Science, in 2021. In his current position, Dr. Mansi focuses on the research and development of AI approaches spanning digital health, computer vision, and biology, to derive advanced insights from multimodal, biomedical data and accelerate drug discovery and development. Throughout his career, Dr. Mansi and the teams he worked with received several awards and gave multiple keynotes at international conferences. He holds 70+ granted US patents, co-edited 1 monograph, and co-authored 100+ scientific publications.
Things You’ll Learn:
- Janssen leverages large biobank data sets to identify subtypes of diseases and accelerate the development and efficacy of drugs.
- When developing a drug or therapy, AI can help with diversity, equity, and inclusion.
- People in LabOps work to ensure that the data coming from the lab can be trusted.
- The annotation means you assign a label to the data you have, which is used to train the AI system.
- When it comes to training an AI system to develop an algorithm that can process different qualities of data input, it’s more important to have good data annotations than good data.
- The value of AI insights comes from the synergy between human ingenuity and protocol with the AI’s automation and algorithm.
- Sometimes a problem has already been solved in other fields, so research is vital.