Absci Drug Creation

Unlocking new drug candidates faster by integrating AI with proprietary wet-lab data.

by Absci · Drug Discovery AI

Executive Summary

Absci Drug Creation is an AI-powered drug discovery platform that integrates generative AI with high-throughput wet-lab data to design, predict, and optimize novel therapeutic proteins. It is used by biopharmaceutical companies and researchers to accelerate drug discovery, de-risk development, and bring better therapeutics to market faster. Its key differentiation lies in its ability to generate and leverage proprietary, high-quality biological data to train and validate its AI models, leading to more effective and developable drug candidates.

Use Cases

  • Discovery of novel antibody therapeutics with enhanced binding and developability.
  • Optimization of existing protein drugs for improved stability, potency, or reduced immunogenicity.
  • Identification and validation of novel therapeutic targets for various disease areas.
  • Accelerated lead candidate selection by predicting key properties early in the discovery funnel.
  • De-risking drug development by assessing developability and manufacturability of candidates.
  • Engineering enzymes or other functional proteins for industrial or therapeutic applications.

Features

Visibility

  • Interactive Data Visualization: Explore complex biological data and AI predictions through intuitive charts, graphs, and 3D protein visualizations.
  • Candidate Comparison Tools: Side-by-side analysis of multiple drug candidates based on predicted and experimental properties.
  • Project Management & Tracking: Monitor the progress of drug discovery projects, experimental batches, and AI model iterations.
  • Developability Scoring: Predict and visualize the developability profile of protein candidates early in the discovery process.

Intelligence

  • De Novo Protein Design: Generative AI models create entirely new protein sequences with desired therapeutic properties.
  • Predictive Property Modeling: AI predicts key biophysical and functional properties like binding affinity, stability, and immunogenicity.
  • Automated Experimental Design: AI suggests optimal experimental conditions and assays to validate predictions and generate new training data.
  • Lead Optimization: AI-guided iterative refinement of lead candidates to enhance efficacy, safety, and manufacturability.

Support

  • Dedicated Scientific Support: Access to Absci's team of computational biologists and protein engineers for scientific guidance and collaboration.
  • Comprehensive Documentation: Detailed guides and resources for platform usage, data interpretation, and best practices.
  • Training & Workshops: Onboarding and advanced training sessions to maximize user proficiency and platform utilization.

Technical Specifications

Architecture
Cloud-native SaaS, leveraging high-performance computing for AI/ML workloads
Deployment
Cloud/SaaS
Authentication
SSO, SAML 2.0, MFA, OAuth 2.0
API Available
Yes
MCP Server
No

Infrastructure

  • AWS
  • GCP

AI/ML Stack

  • Machine Learning
  • Deep Learning
  • Generative AI
  • Predictive Modeling

Integrations

  • Laboratory Automation
  • Protein Expression Systems

Security & Compliance

Certifications: SOC 2 Type II, ISO 27001

Encryption: AES-256 at rest, TLS 1.2+ in transit

Pricing

Model
Custom enterprise
Starting Price
Contact sales
Target Customer
Enterprise biopharma, large biotech
Contract Type
Multi-year agreements
Free Trial
No (credit card required)

About Absci

Absci is a clinical-stage biopharmaceutical company that leverages its Integrated Drug Creation™ platform, combining generative AI with synthetic biology to design and advance novel biologic therapeutics faster. They aim to create better biologics for patients by unifying drug discovery and cell line development into one simultaneous process.

Founded: 2011 · Headquarters: Vancouver, WA, United States · Employees: 201-500 · Public