AI Models — Ivy Biosciences

Full inventory of AI models and computational biology tools available on the .bloom* platform.

Protein Structure

• AI structure prediction — fast single-sequence folding
• Protein language models — structure, function, and sequence analysis
• Binding site detection — ML-based druggability scoring

Molecular Docking

• AI-powered docking — state-of-the-art pose prediction
• Physics-based docking — classical and ML-enhanced approaches

ADMET & Safety

• Multi-endpoint ADMET prediction with confidence scores
• Pharmacokinetic property prediction
• Toxicity classification and organ toxicity prediction

Generative & Design

• De novo molecular design — generative AI for novel candidates
• Retrosynthetic route planning with commercial starting materials

Genomics & NLP

• Single-cell RNA-seq analysis, clustering, and trajectory
• Biomedical NER for genes, proteins, drugs, and diseases

Ivy Biosciences — AI-Powered Drug Discovery Platform

Platform Capabilities

• Protein structure prediction and analysis
• Molecular docking and pose generation
• ADMET and toxicity screening
• De novo molecular generation and design
• Retrosynthetic route planning
• Fragment-based drug design and scaffold decoration
• Binding site detection and druggability scoring
• Genomics, proteomics, and single-cell RNA analysis
• Biomedical literature mining
• Compound and target passport reports

Pricing

Free Seed tier with 500 credits per month. Paid plans (Grow, Flourish) for teams needing higher throughput. Student plan with free enhanced access for verified .edu emails. Enterprise plans with dedicated support and custom integrations.

Use Cases

• Drug Discovery — screen millions of compounds in hours with AI-powered virtual screening
• Molecular Optimization — optimize lead compounds for efficacy, safety, and drug-likeness
• Target Identification — discover novel drug targets with bioinformatics and ML
• ADMET Prediction — predict absorption, metabolism, and toxicity before synthesis
• Chemical Library Design — build diverse, drug-like libraries for high-throughput screening
• Biomarker Discovery — identify treatment-response biomarkers with multi-omic analysis

Documentation

Comprehensive guides covering a comprehensive set of tools organized by the drug discovery pipeline: target identification, structure analysis, hit discovery, lead optimization, ADMET and safety, and synthesis planning. Includes quickstarts, API references, and CLI documentation.

Open source under FSL-1.1-Apache-2.0 (converts to Apache 2.0 after 2 years). Self-hosting documentation available at ivybiosciences.com/docs.