iNDICA NEWS BUREAU-
Two Indian American students of the School of Engineering at the Massachusetts Institute of Technology have been chosen with 11 other graduate student fellows as Takeda fellows for the 2023-24 school year.
“The School of Engineering has selected 13 new Takeda Fellows for the 2023-24 academic year. With support from Takeda, the graduate students will conduct pathbreaking research ranging from remote health monitoring for virtual clinical trials to ingestible devices for at-home, long-term diagnostics,” said a release from MIT. The Takeda Fellows include Vivek Gopalakrishnan and Priyanka Raghavan.
The MIT-Takeda Program, now in its fourth year, is a collaboration between MIT’s School of Engineering and Takeda that fuels the development and application of artificial intelligence capabilities to benefit human health and drug development. Part of the Abdul Latif Jameel Clinic for Machine Learning in Health, the program coalesces disparate disciplines, merges theory and practical implementation, combines algorithm and hardware innovations, and creates multidimensional collaborations between academia and industry.
Vivek Gopalakrishnan is a PhD candidate in the Harvard-MIT Program in Health Sciences and Technology. Gopalakrishnan’s goal is to develop biomedical machine-learning methods to improve the study and treatment of human disease. He employs computational modeling to advance new approaches for minimally invasive, image-guided neurosurgery, offering a safe alternative to open brain and spinal procedures.
With the support of a Takeda Fellowship, Gopalakrishnan will develop real-time computer vision algorithms that deliver high-quality, 3D intraoperative image guidance by extracting and fusing information from multimodal neuroimaging data. These algorithms could allow surgeons to reconstruct 3D neurovasculature from X-ray angiography, thereby enhancing the precision of device deployment and enabling more accurate localization of healthy versus pathologic anatomy.
Priyanka Raghavan is a PhD candidate in the Department of Chemical Engineering. Raghavan’s research interests lie at the frontier of predictive chemistry, integrating computational and experimental approaches to build powerful new predictive tools for societally important applications, including drug discovery.
Raghavan is developing novel models to predict small-molecule substrate reactivity and compatibility in regimes where little data is available. A Takeda Fellowship will enable Raghavan to push the boundaries of her research, making innovative use of low-data and multi-task machine learning approaches, synthetic chemistry, and robotic laboratory automation to create an autonomous, closed-loop system for the discovery of high-yielding organic small molecules in the context of underexplored reactions.
Raghavan aims to identify new, versatile reactions to broaden a chemist’s synthetic toolbox with novel scaffolds and substrates that could form the basis of essential drugs. Her work has the potential for far-reaching impacts in early-stage, small-molecule discovery and could help make the lengthy drug-discovery process significantly faster and cheaper.