Automated Chemical Identification System for Accelerated R&D Processes

The client faces significant delays—taking approximately 6 months—manual effort required by domain experts to identify, name, and catalog chemical compounds from scientific literature and existing databases, hampering R&D efficiency and timely decision-making.

A large, global pharmaceutical or biotech company seeking to streamline chemical research and identification workflows to accelerate drug development and product innovation.

• Reduce the chemical identification process from 6 months to under 24 hours.
• Develop an AI-powered interface allowing experts to upload scientific literature in PDF format for automated processing.
• Extract chemical compounds including their names, identifiers (InchiKey, CAS, Smiles code), molecular formulas, and synonyms.
• Enrich internal chemical databases with comprehensive chemical property data for each identified compound.
• Cross-reference identified chemicals with existing sales or catalog data to determine current availability.
• Deliver a secure, enterprise-compliant solution hosted on the client's infrastructure.

• Secure user interface for uploading scientific literature (PDF files).
• AI-driven extraction pipeline utilizing large language model frameworks to identify chemical mentions.
• Chunking mechanism to handle large data inputs exceeding language model limitations.
• Integration with chemical databases to retrieve properties like InchiKey, CAS, Smiles, molecular formulas, and synonyms.
• Automated cross-referencing with internal catalogs to identify existing chemicals in the inventory.
• Visualization tools displaying chemical information alongside 2D molecular structure images.
• Secure storage compliant with enterprise data security standards.
• Logging, tracking, and documentation of extraction processes for auditing.

• External chemical databases for property retrieval (InchiKey, CAS, Smiles, etc.)
• Internal catalog databases for existing chemical inventory checks
• Enterprise authentication and authorization systems
• Secure file storage and transfer mechanisms

• High scalability to process large volumes of literature and chemical data
• Performance: Chemical identification and data retrieval within 24 hours of upload
• Enterprise-grade security and compliance standards
• Data integrity and auditability of extraction and enrichment processes
• Hosted within the client’s secure infrastructure

The implementation of this AI-driven chemical identification system is expected to drastically reduce manual processing time from months to less than a day, significantly accelerating R&D workflows. This will enhance decision-making speed, improve data accuracy and consistency, and support faster product development cycles, ultimately leading to increased innovation and competitive advantage.