The Technology Advancing Alzheimer’s Research

In this episode of Research Renaissance, host Deborah Westphal dives into a fascinating conversation with Dr. Sudeshna Das, Associate Professor of Neurology at Mass General Hospital and Harvard Medical School. Dr. Das is a pioneer in the field of biomedical informatics and a 2022 Toffler Scholar. Her work focuses on developing tools for multi-scale data integration from molecular to clinical data and applying data science approaches to study neurodegenerative diseases, particularly Alzheimer’s disease.

Guest Introduction: Dr. Sudeshna Das

Dr. Sudeshna Das is an Associate Professor of Neurology at Mass General Hospital and Harvard Medical School. She specializes in biomedical informatics and has a keen interest in developing tools for integrating diverse data sets, from molecular to clinical, to understand complex diseases like Alzheimer’s. Dr. Das has a rich background in engineering and computational biology, making significant contributions to the field of drug discovery and neurodegenerative disease research.

Key Discussion Points

1   Career Motivation and Journey:
◦   Dr. Das shares her early inspiration to cure cancer, driven by personal experiences with family members who had the disease.
◦   Her transition from engineering to biomedical informatics and the unique challenges and opportunities she faced as a female engineer in India.
2   Biomedical Informatics and Data Integration:
◦   Explanation of biomedical informatics, bioinformatics, and computational biology.
◦   The importance of integrating large, high-dimensional data sets and real-world data for research.
◦   Challenges in managing and analyzing big data and high-velocity data.
3   Alzheimer’s Disease Research:
◦   The focus on understanding the roles of different cell types in Alzheimer's disease, particularly astrocytes, and their progression from protective to exhausted states.
◦   The significance of recent findings on the role of T cells in Alzheimer’s disease and their potential as therapeutic targets.
4   Future of Alzheimer’s Research:
◦   The promise of new technologies like spatial transcriptomics and artificial intelligence in advancing Alzheimer’s research.
◦   The potential of AI tools, such as graph neural nets, to model disease pathways and predict effective treatments for individual patients.
◦   The long-term goal of developing personalized treatments for Alzheimer’s disease.
5   Mentoring and Funding:
◦   Dr. Das’s commitment to mentoring young researchers and her approach to guiding students through complex research landscapes.
◦ The role of foundations like the Karen Toffler Charitable Trust in providing crucial funding for preliminary research.

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