The AI Biotech
Ecosystem

AI-in-Bio advances agentic AI for drug discovery within a vibrant landscape of open-source initiatives, cross-industry consortia, and pioneering research organizations transforming biomedicine.

Industry Directories

Open-Source Protein Folding

Leading Biotechnology & AI Consortia

Cross-industry collaborations establishing standards, sharing pre-competitive data, and accelerating AI adoption in life sciences.

MELLODDY Project

Machine Learning Ledger Orchestration for Drug Discovery

Major cross-industry consortium using blockchain and federated learning, enabling multiple pharmaceutical companies to train AI models on combined proprietary data without sharing actual data with competitors.

The Pistoia Alliance

AI/ML Center of Excellence

Global not-for-profit members' organization focused on pre-competitive collaboration. Establishes best practices, data standards, and collaborative projects for AI in life sciences.

Alliance for AI in Healthcare

AAIH

Global advocacy organization dedicated to innovative healthcare solutions through AI. Unites pharmaceutical companies, tech giants, and academic institutions to standardize and advance AI in life sciences.

Atomwise AIMS Program

Academic Molecular Screening

Massive collaborative network providing AI-powered molecular screening to hundreds of academic researchers worldwide, democratizing access to advanced drug discovery tools.

ATOM Consortium

Accelerating Therapeutics for Opportunities in Medicine

Public-private partnership (GSK, Lawrence Livermore National Laboratory, NCI) transforming drug discovery from a slow, sequential process into a rapid, integrated AI-driven system.

IBM Data & AI Consulting

Enterprise AI Infrastructure

Enterprise-grade AI and data platforms powering life sciences innovation, from clinical trials to regulatory compliance and drug discovery workflows.

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Research & Publications

Peer-reviewed research demonstrating the power of AI in drug discovery, from structure prediction to virtual screening and academic partnerships.

Discovery of a cryptic pocket in the AI-predicted structure of PPM1D phosphatase explains the binding site and potency of its allosteric inhibitors

Nature Scientific Reports • 2024

Demonstrates how AI-predicted protein structures reveal hidden binding sites for drug design.

AI-Predicted Structures Enable Discovery of Allosteric Drug Targets

ACS Journal of Medicinal Chemistry • 2024

Advanced medicinal chemistry research using AI structure prediction for drug discovery.

An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries

Frontiers in Molecular Biosciences • 2023

Novel graph-based AI approaches for exploring massive chemical space in drug discovery.

AtomNet PoseRanker: Enriching Ligand Pose Quality for Dynamic Proteins in Virtual High-Throughput Screens

arXiv Preprint • 2022

Advanced pose prediction for protein-ligand interactions in large-scale virtual screening campaigns.

Machine Learning Methods in Computational Toxicology

ACS Journal of Chemical Information and Modeling • 2021

AI-driven approaches for predicting compound toxicity and safety profiles.

YC Partners With Atomwise to Fund More Bio Companies

Y Combinator Blog

Major startup accelerator partnership bringing AI drug discovery tools to emerging biotech companies.

Bringing the Power of AI Drug Discovery to Academic Partners

AUTM (Association of University Technology Managers) • Andreia Lee, PhD

Framework for academic-industry partnerships democratizing access to AI screening platforms.

MELLODDY: A 'co-opetitive' machine learning platform powered by Owkin

Owkin Case Study

Federated learning consortium enabling pharmaceutical companies to collaborate on AI models while preserving data privacy.

AI-in-Bio's Position

AI-in-Bio.com operates at the forefront of agentic AI for drug discovery, leveraging insights from the broader biotechnology ecosystem. While we chart our own path in LLM-driven proteomics and autonomous lab agents, we recognize the pioneering work of open-source initiatives, industry consortia, and collaborative networks advancing the field.

The organizations listed represent the cutting edge of AI biotechnology—from federated learning frameworks that preserve competitive advantages while enabling collective progress, to open-source protein folding models democratizing structural biology. This ecosystem accelerates innovation that ultimately benefits patients worldwide.