ChemPass AI - Evogene

Chempass AI™
Tailor-Made Generative AI Molecular Design

ChemPass AI™, Evogene’s proprietary generative AI tech-engine, bridges advanced AI molecule design with practical product outcomes across pharma and agriculture, helping translate scientific potential into commercial success.

Advanced Discovery & Optimization

Based on 38B molecules, ChemPass AI foundation model redefines molecular innovation – enabling the generation of novel, highly potent and synthesizable compounds tailored to specific biological and chemical requirements.

By replacing the slow, iterative trial-and-error process of optimizing conflicting properties with a streamlined, AI-first workflow that takes multiple parameters into account simultaneously, ChemPass AI™ empowers product development to move faster, smarter, and further.

Three Core Advantages

Multi-parameter optimization

Unlike conventional AI engines, ChemPass AI optimizes potency, selectivity, stability, toxicity, scaffold design, ADME, and synthesizability simultaneously, yielding molecules with superior performance and real-world viability.

Designed for Potency & Precision

By fusing advanced AI design with targeted experimental validation , ChemPass AI produces molecules with higher predicted efficacy and binding precision.

Novelty Beyond Existing Libraries

Built on a 38 billion-molecule chemical universe, ChemPass AI generates novel structures that give a decisive IP and competitive edge in pharma and ag-chem markets.

Addressing the multi-parameter optimization

Potency Binding Affinity
Synthetic Accessibility
Solubility
Chemical Stability
IP/Novelty
Molecular Weight
Lipophilicity (LogP)
Metabolic Stability
Hydrogen Bond Donors/Acceptors
Scaffold
Selectivity
ML Models (QSAR)

Potency Binding Affinity
Synthetic Accessibility
Solubility
Chemical Stability
IP/Novelty
Molecular Weight

Lipophilicity (LogP)
Metabolic Stability
Hydrogen Bond Donors/Acceptors
Scaffold
Selectivity
ML Models (QSAR)

Each molecule must overcome a complex web of scientific and commercial challenges to become a real product.

DRIVING HIGHER CUMULATIVE PROBABILITY OF SUCCESS

ChemPass AI™

Literature search, data preprocessing and target modeling
Identify potential hits using PointHit
Identify elaborated  analogs using ActiveSearch
Generate novel leads using LeadOptGPT

Target Preprocessing

Target Preprocessing

The first step of the discovery process begins with a joint definition of the biological target and program objectives during. We perform literature search, data preprocessing and target modeling in preparation for the hit identification step.
Hit Screening

Hit Screening

We use ChemPass AI engine to perform virtual screening, searching a large database of commercially available compounds for the most promising molecules that can bind to the target protein. These molecules are then tested in relevant assays, and the best performers move to the next stage.
Hit-To-Lead

Hit-To-Lead

Around each top-performing molecule, we create a family of compounds with comparable structure and properties, which are also available for purchase. These are tested again in relevant assays to refine our selection.
Lead Optimization

Lead Optimization

With the insights gathered so far, we move to the most critical step – designing novel molecules optimized across multiple criteria. These are synthesized and tested, representing novel chemical entities with the strongest potential to become the product defined at the start of the process.

partner / internal expertise

Target elucidation and biological interpretation
Purchase hits and test activity and selectivity
Purchase analogs and test activity and selectivity
Synthesis of novel leads  and validation

This closed-loop system dramatically shortens time-to-lead, lowers development costs, and delivers highly optimized molecules ready for downstream validation and commercialization.

Technological Collaboration with google cloud

Scales real-world innovation across industries – from generative models to autonomous discovery.

FIRST COLLABORATION –
FIRST-IN-CLASS FOUNDATION MODEL

A proprietary generative AI model for novel molecular candidates, addressing multiple parameters was developed based on 38B structures, achieving 90% precision, compared to ~30% in traditional GPT models.

SECOND COLLABORATION –
INITIATION OF ADVANCED AI AGENTS INTEGRATION

Integration of AI agents into ChemPass AI™ using Google Cloud Vertex AI, to decrease manual errors, accelerate design-make-test-analyze cycles, and enable scalable generation of novel small-molecules with improved probability of commercial success.

BOAZ MAOZ

MANAGING DIRECTOR
GOOGLE CLOUD ISRAEL

“This expanded collaboration with Evogene demonstrates the power of integrating cutting-edge artificial intelligence into scientific research. By leveraging our technology to deploy advanced AI agents, we are enabling Evogene to automate and scale their complex discovery workflows. This foundation accelerates the speed and precision of identifying small molecules, further cementing Evogene’s role as a leader in next-generation molecular design for the pharmaceutical and agricultural industries.” (Feb. 2026)

CHEMPASS AI™ MULTI-PARAMETER DESIGN ENGINE FOR REAL-WORLD INNOVATION

Chempass AI™
Tailor-Made Generative AI Molecular Design

Advanced Discovery & Optimization