“The flagship research projects of the MIT-Takeda Program offer real promise to the ways we can impact human health. We are delighted to have the opportunity to collaborate with Takeda researchers on advances that leverage AI and aim to shape health care around the globe.”

— Jim Collins, MIT-Takeda Program faculty lead

AI – enabled, automated inspection of lyophilized products in sterile pharmaceutical

  • Linda Wildling, Head of Digital Innovation Success Management – Global GMSGQ DD&T
  • Antonio Burazer, Global Head Visual Inspection and Particle LCM – Analytical Services & Support
  • Duane Boning, Clarence J. LeBel Professor in Electrical Engineering and Computer Science
  • Sanjay Sama, Fred Fort Flowers (1941) and Daniel Fort Flowers (1941) Professor in Mechanical Engineering; Vice President, Open Learning
  • Luca Daniel, Professor, Electrical Engineering and Computer Science

AI for the Diagnosis of Autoimmune Gastrointestinal Disorders

  • Jeanne Jiang, Associate Director Patient Data Domain Expert-Data Strategy and Governance
  • Tao Fan, Director, Data Networks for External Partnerships-Data Services & Content Delivery
  • Peter Szolovits, Professor of Computer Science and Engineering
  • Rahul Mazumder, Associate Professor in the Operations Research and Statistics Group

Causal Inference and Optimization for Patient and HCP Engagement

  • Kyle Dillon, Sr Director, Quantitative Clinical Pharmacology, ONC-Quantitative Clinical Pharmacology
  • Jillian Berry Jaeker, Sr. Director, Statistics-Oncology Stats
  • Jonas Oddur Jonasson, Robert G. James Career Development Associate Professor in Operations Management
  • Vivek Farias, Patrick J. McGovern (1959) Professor

Machine learning for early identification and assessment of gross motor function deterioration in metachromatic leukodystrophy (MLD) (TAK-611)

  • Javier Gervas, Head of Digital & Industry 4.0 ad interim-GMS Digital & Data Analytics
  • Hermano Igo Krebs, Principal Research Scientist

Interpretable discovery of clinical features using transformer networks

  • Marco Vilela, Associate Director, Statistics-Quantitative Sciences
  • Jim Glass, Senior Research Scientist, MIT’s Computer Science and Artificial Intelligence Laboratory

Developing a framework and tools for machine-learning based disease identification and classification in administrative health data with application to narcolepsy diagnosis

  • Dana Teltsch, Director, GME Head, NS & Hematology-GMA Medical Evidence Generation

Predictive Modeling for Downstream Process Development for Biologics Manufacturing

  • George Parks, Sr Staff Engineer, Process Development-Mab Derived Biologics Development
  • Raghu Shivappa, Head, Biologics Process Development-Pharmaceutical Sciences
  • J. Christopher Love, Raymond A. (1921) and Helen E. St. Laurent Professor of Chemical Engineering
  • Connor W. Coley, Henri A. Slezynger (1957) Career Development Professor; Assistant Professor, Chemical Engineering and Electrical Engineering and Computer Science

Optimal treatment strategies and decision making in real-world with machine learning

  • Jianchang Lin, Sr Director, Statistics-Oncology Stats
  • Marzyeh Ghassemi, Herman L. F. von Helmholtz Career Development Professor
  • Ashia Wilson, Assistant Professor of Electrical Engineering and Computer Science

AI-enabled Transfer-Learning methods for video data analysis models for optimizing and controlling manufacturing process

  • Chris Mitchell, Sr Dir, Head Signal Management-Global Patient Safety Operations (GPSO)
  • Allan S. Myerson, Professor of the Practice, Chemical Engineering
  • Richard Braatz, Edwin R. Gilliland Professor; Professor, Chemical Engineering
  • George Barbastathis, Professor, Mechanical Engineering
  • Wojciech Matusik, Professor of Electrical Engineering and Computer Science at the Computer Science 

Predictive Signal Detection and Analyses – PRISM (Patients Really are first In Signal Management)

  • Dona M. Ely, Director, Health Economics and Outcomes Research-US Medical Outcomes Research – GI
  • Resef Levi, J. Spencer Standish (1945) Professor of Operations Management
  • Anthony Sinskey, Professor of Biology

AI automated diagnosis of Fabry disease using electrocardiogram (ECG)

  • Subir Roy, Global Medical Lead for Metachromatic Leukodystrophy-GMA LSD
  • Dina Katabi, Thuan and Nicole Pham Professor
  • Elazar Edelman, Edward J. Poitras Professor in Medical Engineering and Science
  • Piotr Indyk, Thomas D. and Virginia W. Cabot Professor

 

Improving multiple myeloma clinical trial design and identification of heterogeneous treatment effects using machine learning

  • Neeraj Gupta, Assoc. Dir. Quality Control-Analytical Services & Support
  • Guohui Liu, Senior Staff Engineer, Process Chemistry & Development-Process Chemistry