Company / Competitor

Schrodinger

Mentioned in 9 AI use cases across 3 industries

Use Cases Mentioning Schrodinger

pharmaceuticalsBiotechEnd-to-End NN

Beyond AlphaFold 2: The next frontier in macromolecular modeling

Think of AlphaFold 2 as a revolutionary microscope that predicts how single proteins fold in 3D. The “next frontier” the article discusses is like upgrading from looking at a single Lego brick to understanding whole Lego machines: how multiple proteins, RNAs, DNA, and small molecules interact, move, and change shape in real time inside a cell.

pharmaceuticalsBiotechEnd-to-End NN

Artificial Intelligence in Drug Discovery Platforms

Think of AI in drug discovery as a super-fast, never-tired lab assistant that can read millions of scientific papers, simulate how molecules behave in the body, and shortlist the most promising drug candidates long before a human team could finish the first pass.

pharmaceuticalsBiotechEnd-to-End NN

AI-Driven Drug Discovery and Development Transformation

Think of AI as a super-fast, tireless scientist that can read every paper ever written, simulate thousands of experiments in a day, and flag the most promising drug ideas long before humans could. Instead of running blind, drug companies use AI as a GPS that suggests the best routes, warns about dead ends, and helps them reach new medicines faster and cheaper.

healthcareEnd-to-End NN

AI and Automation in Drug Discovery

Think of this as putting a super-fast robot scientist and a tireless data analyst together in your lab. The robot runs thousands of chemistry and biology experiments automatically, while the AI watches the data, spots patterns humans would miss, and suggests the next best experiments to run to find promising new drugs much sooner.

healthcareClassical-Supervised

Computer-Aided Drug Design for Drug Development

This is like using extremely smart microscopes and calculators on a computer to design new medicines before you ever mix chemicals in a lab. The software predicts which molecules are most likely to work, so scientists test 100 promising ideas instead of 10,000 random ones.

healthcareClassical-Supervised

Machine learning for human-centric drug toxicity prediction

Think of this like a super-smart safety inspector for new medicines. Instead of testing every drug only in animals or long, expensive lab studies, a machine learning system studies lots of past data about how drugs affect human cells and then predicts which new drug candidates are likely to be toxic to people—before they ever reach clinical trials.

pharmaceuticalsBiotechEnd-to-End NN

Recursion Pharmaceuticals AI-Based Drug Discovery Platform

This is like giving a superpowered microscope and a pattern-spotting robot to a drug lab. The system runs huge numbers of biological experiments, turns the images and data into a “map” of how cells react, and then uses AI to quickly suggest which molecules could become medicines, instead of scientists guessing and testing one-by-one over many years.

pharmaceuticalsBiotechEnd-to-End NN

AlphaFold Protein Structure Prediction for Biology and Drug Discovery

Imagine trying to build a complex piece of IKEA furniture with only a list of parts and no picture of the finished product. AlphaFold is like an AI that can instantly show you what the finished furniture looks like—and how every piece fits together—just from reading the parts list. In biology, the “parts list” is a protein’s amino acid sequence, and the “picture” is its 3D shape.

miningEnd-to-End NN

AlphaFold Protein Structure Prediction

AlphaFold is like an AI-powered microscope that can "see" the 3D shape of proteins just from their genetic recipe, without having to grow crystals or run long lab experiments.