AI-Powered Drug Discovery.
From Pathways to Candidates.
Transform potential pathways into validated drug candidates with clinical intelligence — from academic research to pharmaceutical development.
Why Path2Drug?
Traditional drug discovery pipelines are slow, expensive, and prone to late-stage failures. Path2Drug solves these pain points with AI-powered automation and clinical intelligence.
Eliminate Manual Curation
Replace weeks of manual pathway analysis with AI-powered classification. Our hybrid LLM + rule-based system processes 80+ pathways in minutes, not months.
Accelerate Drug Discovery
Transform 100K+ OpenTarget drug-target hits into 138 validated candidates with clinical intelligence. Cut your discovery timeline from years to days.
Reduce Clinical Risk
Filter candidates with FDA adverse reaction data before investing in development. Our clinical intelligence layer surfaces safety signals early.
Increase Success Rate
Leverage comprehensive UniProt enrichment, literature validation, and druggability scoring to prioritize candidates with the highest therapeutic potential.
The Problem with Traditional Drug Discovery
Pharmaceutical companies spend $2.6 billion and 10+ years to bring a single drug to market. 90% of candidates fail in clinical trials, often due to safety issues that could have been predicted earlier.
Path2Drug changes this by surfacing clinical intelligence and safety signals at the discovery stage.
Professional
- Single user account
- Up to 100 pathways/month
- Surface receptor classification
- UniProt enrichment
- Basic drug discovery
Team
- Up to 5 seats
- Unlimited pathways
- Full OpenTarget integration
- Clinical intelligence filtering
- Literature validation
- Everything in Professional
Enterprise
- Custom user seats
- Custom LLM model selection
- Batch processing & automation
- Priority API access
- Dedicated support
- Everything in Team
Trusted by Researchers
“Path2Drug reduced our pathway analysis time from 3 weeks to 2 hours. Game-changing for our research timeline.”
Dr. Sarah Chen
Principal Investigator, Stanford Medicine
“The clinical intelligence filtering saved us from pursuing a candidate with hidden safety signals. Invaluable.”
Dr. Michael Torres
Head of Drug Discovery, BioTech Innovations
“138 validated candidates from 100K+ hits with literature backing. This is the future of drug discovery.”
Dr. Emily Robertson
Research Director, Pharma Solutions Inc
“The UniProt enrichment and OpenTarget integration gave us insights we would have missed manually.”
Dr. James Park
Computational Biologist, GeneTech Labs
About our Team
Ruslan Rust
Ruslan is a neuroscientist and Assistant Professor at the University of Southern California (USC) with 15 years of translational research experience in neurological and vascular disorders. Much of his work centers on RNA-seq, single-cell RNA-seq, cell-cell communication, and proteomics, where he has led and executed many projects from raw data to publication-ready figures. He brings expertise in analysis, visualization, and interpretation, with a strong ability to turn complex datasets into clear biological insights and compelling narratives.
Ruslan has published more than 60 scientific articles in major high-impact journals, led international collaborations, and secured major funding from government agencies and foundations in Germany, Switzerland, and the USA. His additional training in MBA, bio-entrepreneurship, and scientific leadership allows him to help companies bridge cutting-edge science with strategy, innovation, and impact. All Publications
Sean Simonini
Sean is a researcher and nonprofit leader advancing efforts to repair the brain after injury, disease, and aging. He has conducted drug discovery efforts at Harvard University and research on traumatic brain injuries and ALS at the University of Massachusetts Chan Medical School. Additionally, Sean serves as a board member and as the Vice President of Neuroscience and Policy for the Aging Initiative, a 501(c)(3) organization.
His research focuses primarily on how to understand elements of brain aging that drive neuronal loss, as well as how to engineer stem cell biology for the replacement of neurons lost in disease. Sean is driven by personal connections to neurodegenerative conditions and is adamant about advancing efforts to find cures for patients.
Dominikus Brian
Domi is a researcher and entrepreneur with 12+ years of academic training and Industry experience, including a PhD Fellowship (ABD) from New York University, and master's from University of Michigan - Shanghai JiaoTong University Joint Institute and domain expertise spanning across chemistry, material science, and engineering thermophysics. His experience bridges experimental, computational, and theoretical sciences, with deep expertise in AI for Science, Quantum Chemistry, Advanced Material, High-Performance Computing, Data Science, and Machine Learning.
He has authored 10+ peer-reviewed publications and previously led innovation strategy at enterprise scale in green energy R&D spearheading autonomous laboratory development and briefly work on decentralized computing infrastructure. With strong capabilities cloud and software architecture and development, Domi specializes in building intelligence systems that integrate analytics, simulation, and informatics to accelerate scientific discovery.