AIMI AI Happy Hour Episode 11: Pharma AI

AIMI YouTube Channel

Open to all

Hear perspectives from a diverse expert panel of AI clinicians, researchers, computer scientists, and industry leaders:

• Matthew Lungren, MD, MPH (Stanford): Dr. Lungren is an Associate Professor of Radiology and the Co-Director of the Stanford Center for Artificial Intelligence in Medicine and Imaging. His leading research interest is in the field of machine learning and deep learning in medical imaging and clinical informatics. He is primary or senior author on many medical imaging machine learning projects including work on deep learning techniques to classify clinical radiology images and report data. He holds an MPH which focuses on his primary interest in biostatistical modeling in epidemiology and health policy in the national healthcare landscape, and he has extensive applied experience in both statistical as well as machine learning applications to medical imaging problems. In his role as PI on several grant funded projects he has managed graduate students and postdoctoral fellows and collaborated with colleagues across disciplines and collaborators at other institutions to successfully complete the aims of his research. His record of accomplished and productive research projects in an area of high relevance and expertise and experience put him in position to support the proposed project with a strong team of collaborators.
• Andrea de Souza, Sr. Director, Research Data Sciences & Engineering (Eli Lilly and Company): A former neuroscience researcher, Andrea’s portfolio career has included leadership assignments at the intersection of science, technology and business development. She has built and led informatics and scientific teams across the entire pharmaceutical value chain. Most recently, Andrea focused on building the Pharma Artificial Intelligence market at NVIDIA. Through this experience she has travelled the world advising biopharmaceutical, academics, research institutes, and startups in the potential of machine learning and artificial intelligence across every discipline in our industry. Prior to her role at NVIDIA, Andrea held leadership positions at the Broad Institute of Harvard and MIT, Amgen, and Roche. In the last three years, Andrea’s work at Eli Lilly & Company has focused around empowering the LRL Research organization with greater computational, analytics-intense experimentation to raise the innovation of our scientists. As the Global Head of Data Sciences and Advanced Analytics, Andrea leads four organizations: The High-Performance Computing Team, the Data Engineering team, the AI/ML team and the Translational Informatics team for LRL. Additionally, Andrea serves as a strategic advisor for the NIH HubMap Advisory Team. She has a B.S. in Animal Physiology from UC Davis, a Master’s in Health Administration from University of San Francisco, and an MBA from MIT Sloan. Her leadership has gained her international recognition as a leader in Big Data, Artificial Intelligence and Data Sciences.
• Judy Gichoya, MD, MS (Emory): A multidisciplinary researcher, trained as both an informatician and a clinically active radiologist. She is an assistant professor at Emory University working on Interventional Radiology and Informatics. She has been funded through the Grand Challenges Canada and NSF ECCS. Her career focus is on validating machine learning models for health in real clinical settings, exploring explainability, fairness, and a specific focus on how algorithms fail. She has worked on the curation of datasets for the SIIM (Society for Imaging Informatics in Medicine) hackathon and ML committee. She volunteers on the ACR and RSNA machine learning committees to support the AI ecosystem to advance development and use of AI in medicine. She is currently working on the sociotechnical context for AI explainability for radiology, especially the dimensions of human factors that govern user perceptions and preferences of XAI systems.
• Anna Bauer-Mehren, PhD (Roche): Anna is a Bioinformatician by training with experience in pharmaceutical research and development and a strong academic background. She leads the Data Science Department in pRED Innovation Center Munich of Roche in Germany. Her team supports pre-clinical and clinical research teams through data management and data analysis, applying in particular Artificial Intelligence methods. We are analyzing high-dimensional data such as imaging data, genomic information, and data from electronic health records to better understand diseases and develop personalized therapies. Anna holds a PhD in Bioinformatics and Biomedical Informatics from the University of Pompeu Fabra in Barcelona and Master in Bioinformatics from the Ludwig-Maximilians-Universität and the Technische Universität München. She completed her postdoc education at the Faculty of Biomedical Informatics at Stanford University in the USA.
• Faisal M. Khan, PhD (AstraZeneca): is the Executive Director of Advanced Analytics and Artificial Intelligence at Astrazeneca. His team focuses on the applications of AI and data science throughout the drug discovery lifecycle, from target identification through Phase 3 trials and beyond.  His interests focus on the intersections of data science, digital health, biostatistics, bioimaging, personalized medicine, and healthcare delivery. His career has encompassed all aspects of healthcare and biomedical analytics, including diagnostics, devices, clinical trials/therapeutics, and payers/insurance. Dr. Khan has worked or consulted across academia and industry with both startups and Fortune-50 companies. He has over 90 published papers, abstracts, and patents on the applications of machine learning and artificial intelligence for healthcare and the life sciences.

• Maureen Hillenmeyer, PhD, Founder & CEO (Hexagon Bio): Maureen Hillenmeyer is a founder and CEO of Hexagon Bio, a drug discovery company using data science and synthetic biology to discover new medicines in the global metagenome. Maureen earned a PhD in Biomedical Informatics from Stanford University.

• Maliheh Poorfarhani, Director, Global Digital Health Sourcing (Bayer): Mali Poorfarhani has been with Bayer Pharma for 16 years and currently is the director of global Digital Health sourcing. This role spans from technology scouting to data acquisition, building digital health supply chain and periodic performance evaluation in Bayer. Mali holds Masters of Science in System Engineering from University of Maryland, Leadership and negotiation certificate from Carnegie Mellon and AI in Healthcare certificate from MIT. Mali throughout her career at Bayer, design and implemented multi-disciplinary complex software and hardware system applications deployed in healthcare environment. Her current focus is to enable the Digital Health solution businesses across Bayer Pharma by scouting external partnerships.

• Sharon Zhou, PhD Computer Science (ongoing/Stanford): CS PhD candidate at Stanford University, advised by Andrew Ng. Previously a machine learning product manager at Google and a few startups. She is a Harvard graduate in CS and Classics. She likes humans more than AI, though GANs occupy a special place in her heart.

This live panel discussion is part of the AI Happy Hour series, brought to you by Stanford AIMI and friends. We cover hot topics in AI in medicine as well as live questions & comments from attendees.

It's casual, insightful, and open to all!