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NEWS
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Dr. Lai is named a 2024 Top Scholar by ScholarGPS in the specialty of Antibody Research (Prior 5 Years)!
The Lai group received funding titled "Next Generation Viscosity Prediction for Molecular Liability Reduction and Multi-parameter Optimization Development," $150,000, Janssen Research & Development.
Dr. Lai delivered a keynote presentation at AAPS NBC on predicting high-concentration antibody developability using machine learning.
Congrats, Lateefat, on publishing the DeepViscosity paper, our latest machine learning model for predicting high-concentration antibody viscosity.
The Lai group received funding titled "Hybrid data-driven and physics-based models for rapid prediction of antibody-antibody and antibody-excipient interactions," $90,000, University of Delaware/BITC.
Congrats, Ibrahim, on publishing his first paper as a high school student! Ibrahim developed machine learning models that can rapidly screen potential drugs targeting the TG2 protein for treating celiac diseases.
The Lai group received funding titled "Whole-body-level metabolic flux quantitation by machine learning," $191,321, NIH. This research is in collaboration with UCLA.
Stevens officially joins NIIMBL (https://www.niimbl.org/).
Dr. Lai will be the leading PI at Stevens.
The Lai group received funding titled "Toward Metagenome-Scale Metabolic Flux and Free-Energy Analysis via Deep Learning," $525K, DOE. This award is part of a $1.05M collaborative research grant with UCLA.
Malcolm Harrison, REU from County College of Morris won first place in the poster competition.
The Lai group received funding titled "Applying molecular dynamics simulations and machine learning to predict antibody-drug developability and bioavailability," $90,000, University of Delaware/BITC.
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