Solutions Small Molecules Discovery Aragen Integrated Drug Discovery (AIDD) Computational and Data Science AI/ML

AI/ML

Integrated Drug Discovery

AIDD Scope AIDD Scope

Target Identification and Validation

Hit Identification

Lead Optimization Lead Optimization

Case Study: RNA inhibitor

Modalities Modalities

Protein Degrader

Small Molecule Conjugates

Covalent Therapeutics

Computational and Data Science Computational and Data Science

Computer Aided Drug Design (CADD)

Aragen’s in-house Knowledge base

AIDD Chemistry

AIDD Biology AIDD Biology

In-vitro assay Development

In-vivo Animal Models

ADME/PK

Discovery Safety Assessment Discovery Safety Assessment

In-vitro Toxicology

Safety Pharmacology

At IDD we had developed our proprietary AI/ML toolbox for various utilities in Drug discovery process.

ML Platform for Generative Chemistry: Aragen IDD had developed an ML platform for generation of new molecules form a given compound or a set of compounds. The user can define the required parameters and the out new chemical entities are being generated with great diversity index.
AI/ML platform for Predictive ADME model: We had developed inhouse our predictive model for prediction of Vdss, PPB and aqueous solubility. This helps our scientist to make some informed decision during lead optimization stage.
ML toolbox form PROTAC generation: Using our proprietary E3ligase and linker database in addition to the publicly available data sources, we had developed an ML platform for generation of PROTACs based on novel E3ligase and linkers. This helps our PROTAC programs to generate molecules in rapid scale and in a property directed way.

Learn more about our end-to-end capabilities

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