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Khyati Patni

@khyatipatni

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I build biomedical AI systems for drug discovery, knowledge graphs, and high-scale LLM retrieval.

India

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What I'm looking for

I'm looking to build scalable AI/ML systems for biomedical and healthcare problems, particularly across knowledge graphs, NLP, LLMs, RAG, and drug discovery.

At Meril Life Sciences–MicroCRISPR, I build end-to-end biomedical AI pipelines for drug discovery, from literature and clinical-trial processing to NER, entity linking, relation extraction, and target prioritisation.

I designed a production-ready Neo4j biomedical Knowledge Graph with 7.3M+ nodes and 12.8M+ relationships, along with high-throughput ingestion, validation, evidence aggregation, and containerised infrastructure.

I built an agentic retrieval platform and hybrid RAG system for 40M articles using self-hosted LLMs, Cypher-based retrieval, FAISS, Milvus, and MedCPT. This reduced architecture latency from 15 minutes to 10 seconds while maintaining quality.

My research combines computational biology and interpretable machine learning. I've published first-author work on drug-resistance mechanism prediction and computational evaluation of PE-PGRS39.

Experience

Work history, roles, and key accomplishments

Current

Senior Executive, AI/ML – R&D

Current

Meril Life Sciences

Jan 2024 - Present (2 years 8 months)

Ideated and built end-to-end biomedical AI pipelines for drug discovery, including large-scale text processing, NER, entity linking, and relation extraction. Designed a production-ready biomedical Knowledge Graph in Neo4j and deployed containerised infrastructure with Docker Compose.