We are super excited to highlight Jim Collins, Termeer Professor of Medical Engineering and Science at Massachusetts Institute of Technology (MIT) as a featured speaker Massachusetts Institute of Technology (MIT)AidmConf 🗣️ For additional information about the @MIT AI-powered Drug Discovery and Manufacturing Conference visit: aidm.mit.edu

Checkout our recent cell paper "A deep learning approach for antibiotic discovery" authors.elsevier.com/c/1ac2dL7PXcIR… news.mit.edu/2020/artificia…

Severely ill patients with COVID-19 can succumb to bacterial pneumonia as a secondary infection. We are announcing an open task for predicting activity against the bacteria Pseudomonas aeruginosa, which causes nasty lung infections. Learn more here: aicures.mit.edu/tasks

What does data tell us about policies used to combat the global COVID-19 spread? To understand the role of quarantine in halting infection spread, MIT researchers are combining ML with traditional epidemiological models. Read more: bit.ly/2w7pw0m #COVID19 #SARSCoV2 #AI

Prof. Bertsimas and his team are developing powerful analytics to confront COVID-19. Projects include predicting effective resource allocation, a disease progression calculator, and developing a new convenient test. Learn more here: bit.ly/2JEt7pR #SARSCoV2 #AI #ML

What can wastewater tell us about the COVID-19 spread? Prof. Eric Alm develops wastewater based epidemiology to estimate where, when, and for how long we need to intervene in order to protect lives. Read more: bit.ly/2xfPOhI #SARSCoV2 #Covid19

Interested in learning about how Chemprop, the neural network that discovered a new powerful antibiotic, was developed? Andy Favell highlights how the neural network was trained, refined, and its potential to find drugs for COVID-19. Read it here: bit.ly/2RLyWGC

Is there a way to predict heart damage in patients with #COVID19? J-Clinic PI Collin Stultz is currently working on creating an algorithm that uses readily available data to catch impending heart problems before lasting damage is done. Read more here: bit.ly/3bs4MzG

Today, over 300 clinical trials are focusing on #COVID19 antivirals. How much science is behind these trials? Below we compare two statistics for each drug: its relative frequency in trials vs the number of research papers that study it in the context of COVID-19.

Recent research identified 200+ drugs with efficacy against SARS-COV-2, in addition to 100+ others already in clinical trials. We analyzed multiple screening results, and found significant divergences. How can AI models utilize this data? Read more here: bit.ly/3dodKPm

Event Alert 📢📢 Broad Institute Machine Learning in Drug Discovery (#BroadMLinDD) symposium, to highlight recent progress in applying #MachineLearning techniques to #drugdiscovery, is coming up on Oct 24! The event will feature a keynote from Andrew Hopkins Exscientia and 1/3

A great opportunity for all early career scientists using #MachineLearning in #drugdiscovery to present in front a terrific line of speakers and audience from academia, industry, and research institutions! Broad Institute #BroadMLinDD

Do you want to see yourself in this incredible line of speakers 👇 at the #machinelearning in #drugdiscovery symposium at Broad Institute? Don't forget to submit an abstract today (deadline: Sep15) or register to submit! Link to register: broad.io/mldd

📣 We're thrilled to announce the date of our 2023 MIT-MGB AI Cures Conference: April 24th! 🌟 Mark your calendars for this exciting event where we'll be sharing cutting-edge clinical AI research & how to deploy these tools in hospital settings. REGISTER: mitmgb.ai

1/3 🎙 Trainees and students in the #MachineLearning for #DrugDiscovery field — have you submitted an abstract for the Broad Institute MachineLearning for DrugDiscovery Symposium (broad.io/mldd)? There is still time and space for you to achieve many recognitions!