Company / Competitor

Recursion Pharmaceuticals

Mentioned in 10 AI use cases across 5 industries

Use Cases Mentioning Recursion Pharmaceuticals

pharmaceuticalsBiotechEnd-to-End NN

RosettaFold3 biomolecular modeling via Azure AI Foundry

This is like an ultra-detailed 3D CAD tool for molecules, powered by AI. Instead of engineers designing car parts, RosettaFold3 designs and predicts how proteins, DNA, and small‑molecule drugs fit and move together inside the body.

advertisingEnd-to-End NN

NVIDIA BioNeMo for Generative AI in Drug Discovery

Think of NVIDIA BioNeMo as a set of very smart chemistry and biology "co-pilots" that can read and write molecules and proteins the way ChatGPT reads and writes text. Instead of scientists manually trying out millions of possibilities in the lab, BioNeMo helps them design and screen promising drug candidates on a computer first, massively narrowing the search space.

pharmaceuticalsBiotechClassical-Supervised

Artificial Intelligence in Pharmaceutical Industry: Revolutionizing Drug Development and Delivery

Think of this as giving the pharma industry a super-smart assistant that can rapidly scan mountains of scientific data, predict which molecules might become good medicines, design clinical trials more efficiently, and help get the right drug to the right patient faster and more safely.

aerospace-defenseEnd-to-End NN

Hybrid AI/physics pipeline for miniprotein binder prioritization

This is like a super-smart screening funnel for drug-like mini-proteins. Instead of testing millions of molecules in the lab, it uses a combination of AI predictions and physics-based simulations to quickly sort through candidates and highlight the handful most likely to stick to a disease target.

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.

healthcareRAG-Standard

AI in Drug Discovery Workflows

This is about using AI as an ultra-fast research assistant that reads mountains of scientific data, suggests promising drug ideas, and helps scientists decide what to test next, so the slow, trial‑and‑error parts of drug discovery move much faster.

sportsEnd-to-End NN

AI-Driven Protein Engineering and Design

This is like giving scientists an AI-powered CAD tool for proteins: instead of slowly guessing and checking what shape a protein will fold into or how to tweak it, the AI can rapidly predict structures and suggest new protein designs on a computer before they’re ever made in a lab.

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.