The CAS BioFinder Discovery Platform is now available for trial access at our Institute from 15 October 2026 to 30 November 2026.

CAS BioFinder is a module that transforms complex, disconnected scientific data into a clear, decision-ready view for drug development. It provides drug discovery teams with the data and tools they need on a single platform. Researchers can search comprehensive pharmaceutical data through ligands, biological targets, and diseases. Enhanced with AI-powered predictive technologies and knowledge graphs, the platform enables researchers to obtain faster results, accelerate candidate molecule identification, and make more informed decisions. By modeling protein-ligand interactions based on scientific literature data, CAS BioFinder enables rapid in silico prediction of pharmacological and biological activity. Its AI-assisted target prediction feature helps narrow down the pool of candidate molecules for in vitro testing and identify the most promising candidates (P. Natho et al., 2025). Rather than evaluating compounds in isolation, CAS BioFinder allows researchers to explore how structural modifications affect biological activity and selectivity. This AI-driven approach supports target discovery, candidate molecule optimization, and research portfolio strategy development by identifying meaningful patterns grounded in literature and experimental evidence.

📅 Access Information

• Access Dates: 15 October 2026 – 30 November 2026
• Scope: Comprehensive access to published and predicted bioactivity data, ligand-protein interactions, biomarkers, and much more.
• Database Access: Accessible to all SciFinder users. You can log in at biofinder.cas.org using your username and password.

An educational webinar on using BioFinder will be hosted by Dr. Elena Detta, an expert Medicinal Chemist. The webinar details are provided below:

Date: Tuesday, October 20

Time: 10:30 – 12:00

Microsoft Teams meeting

Join: https://teams.microsoft.com/meet/23423805701252?p=GyCWTbvNQplsUSsjOB

Meeting ID: 234 238 057 012 52

Passcode: wV93PK3j