EVA Platform

AI-driven platform for ultra-high-throughput protein engineering and antibody discovery.

by LabGenius · Drug Discovery AI

Executive Summary

EVA Platform is an AI-driven drug discovery engine that integrates synthetic biology, robotic automation, and machine learning to engineer novel therapeutic proteins, particularly antibodies. It is used by pharmaceutical and biotech companies to accelerate the identification and optimization of complex therapeutic antibodies, offering rapid, unbiased discovery of high-performing molecules with non-intuitive designs. The platform aims to significantly reduce the time and increase the success rate of developing advanced medicines.

Use Cases

  • Discovery and optimization of novel therapeutic antibodies.
  • Engineering proteins with enhanced properties, such as resistance to degradation in the GI tract.
  • Co-optimization of mono- and multi-specific single domain antibodies for biochemical and biofunctional properties.
  • Addressing on-target, off-tumor toxicity in oncology by identifying selectivity-enhanced antibodies.
  • Accelerating lead optimization rounds in the drug discovery process.
  • Designing, producing, purifying, and characterizing large panels of multispecific/multivalent antibodies.

Features

Visibility

  • Automated Functional Screening: Conducts automated functional screening of protein designs to assess their characteristics and performance.
  • Digital Variable Tracking: Tracks experimental variables digitally to ensure data quality and reproducibility for machine learning model training.
  • Antibody Characterization: Capable of characterizing panels of multispecific/multivalent antibodies in their final format using disease-relevant, cell-based assays.

Intelligence

  • AI-Driven Protein Design: Utilizes artificial intelligence to design and enhance protein structures and functions.
  • ML-Driven Optimization: Applies machine learning to co-optimize multiple therapeutically valuable protein features simultaneously, such as stability, potency, and selective cell killing.
  • Active Learning Loop: Operates on an active learning principle, continuously learning from experimental results to improve its design capabilities.
  • Non-Intuitive Design Discovery: Capable of exploring vast antibody design spaces to discover high-performing molecules with non-intuitive designs that might be missed by conventional methods.

Support

  • Partnership-based Engagement: LabGenius operates a hybrid business model, partnering with biotech and pharmaceutical companies, implying collaborative support during projects.

Technical Specifications

Architecture
Hybrid (On-premise Robotics & Cloud-based AI/Data Processing)
Deployment
Hybrid
Authentication
Not publicly disclosed
API Available
Yes
MCP Server
No

AI/ML Stack

  • Machine Learning
  • Artificial Intelligence
  • Active Learning

Integrations

  • Robotic Labs
  • Screening Platforms

Security & Compliance

Encryption: Not publicly disclosed

Pricing

Model
Custom enterprise
Starting Price
Contact sales
Target Customer
Pharmaceutical and Biotech Companies
Contract Type
Not publicly disclosed
Free Trial
No (credit card required)

About LabGenius

LabGenius is a drug discovery company pioneering the use of machine learning for the discovery of novel therapeutic antibodies. Its proprietary EVA™ platform integrates artificial intelligence, robotic automation, and synthetic biology to accelerate the identification and co-optimization of complex therapeutic antibodies. The company focuses on developing selectivity-enhanced antibodies for the treatment of solid tumors.

Founded: 2012 · Headquarters: London, United Kingdom · Employees: 51-200 · Private