Building the next generation of cheminformatics intelligence
In Silico Biolabs develops computational tools for retrosynthesis, pathway discovery, molecular feasibility analysis, and AI-assisted chemical decision-making across chemistry, biology, and industrial synthesis.
Cheminformatics infrastructure for the molecular economy.
We believe the future of chemistry will be increasingly computational. Molecules, reactions, enzymes, pathways, properties, and production constraints should be searchable, comparable, and programmable.
In Silico Biolabs is building software infrastructure to help scientists, engineers, and companies reason across chemical and biological synthesis spaces faster and more intelligently. OptiSynth is our first product; the broader platform is designed to grow into a decision-support layer for synthesis, biomanufacturing, and molecular discovery.
Reactions, enzymes, and pathways as first-class queryable objects.
Routes and feasibility available to humans, APIs, and AI agents alike.
OptiSynth
Retrosynthesis and pathway discovery for chemical and biological production.
OptiSynth is a computational route-discovery platform designed to help users explore how target molecules may be produced through chemical synthesis, biological pathways, or hybrid approaches. It searches reaction networks, identifies candidate routes, maps biological reactions to enzymes and genes where available, and supports structured reporting for technical decision-making.
Route discovery
Identify candidate pathways from starting compounds to target molecules across multi-step reaction networks.
Biological pathway intelligence
Connect reactions to enzymes, genes, and organism-specific context where biological data is available.
Chemical synthesis planning
Explore synthetic routes and compare potential production strategies with structured, comparable outputs.
Feasibility-oriented analysis
Support early decision-making around route length, biological plausibility, and production constraints.
AI-assisted reporting
Convert pathway results into readable technical summaries and downloadable reports for R&D and grants.
Future-ready architecture
Designed to support additional databases, APIs, MCP connectors, and integration into external workflows.
OptiSynth is being developed to support advanced computational biology and cheminformatics capabilities, including AI-assisted pathway interpretation, constraint-based feasibility modeling, and future machine-learning-driven route prioritization. Current capabilities and roadmap features are distinguished during pilot engagements.
Beyond one product: cheminformatics infrastructure for the molecular economy.
OptiSynth is a starting point. Our long-term direction is a platform where synthesis planning, pathway intelligence, feasibility scoring, APIs, and MCP connectors compose into custom scientific software for partners across chemistry, biology, and industrial synthesis.
Built for scientists, developers, and AI-native workflows.
Modern scientific software should be accessible through both intuitive interfaces and programmable infrastructure. In Silico Biolabs is building OptiSynth with integration in mind, including structured outputs, API-ready architecture, and future MCP-compatible connectors for AI-native research environments. Public API and SDK access are part of the platform roadmap.
Concept diagram · roadmap
Interfaces built for technical users, not just developers.
Programmatic access to pathway discovery and analysis primitives.
Designed to plug into AI agent toolchains and orchestration frameworks.
Embed cheminformatics steps into internal R&D and automation systems.
JSON, tabular, and graph-native results ready for downstream ETL.
Convert analysis into technical summaries and grant-ready reports.
Software, science, and decision support in one stack.
Interdisciplinary by design
Bridging computational chemistry, biology, AI, and modern software engineering.
Data into decisions
We turn complex pathway and reaction data into usable technical decisions.
For experts and non-specialists
Tools accessible to seasoned computational chemists and cross-functional teams alike.
Earlier production strategy
Explore molecule production routes long before wet-lab commitment.
R&D and commercialization support
Structured outputs suited to grants, technical reports, and internal reviews.
Product and consulting-enabled
Combine platform access with expert-led technical feasibility assessments.
Multiple ways to work with us.
Product demos & early access
See OptiSynth and evaluate fit for your team.
Pilot projects
Scoped engagements against a real target molecule or program.
Custom cheminformatics workflows
Software built around your specific data and questions.
Technical feasibility assessments
Structured expert reports on route and pathway feasibility.
API & integration partnerships
Embed our capabilities into your platform or pipeline.
Grant & R&D collaboration
Co-develop proposals and joint research initiatives.
A computational chemistry and cheminformatics company.
In Silico Biolabs is a computational chemistry and cheminformatics company focused on building software infrastructure for molecular discovery, synthesis planning, and pathway intelligence.
We combine cheminformatics, computational biology, AI-assisted analysis, and modern software engineering to help scientific teams move from molecular ideas to actionable production strategies. We work with technical partners across industrial biotech, chemicals, pharma, materials, sustainable fuels, and translational research.
From molecules to pathways to decisions.
Anh-Dung Le, PhD
Founder & Chief Engineer
Anh-Dung Le is the founder and technical lead of In Silico Biolabs, where he leads the development of OptiSynth, a computational platform for designing and optimizing molecular production strategies. His background spans scientific software, computational modeling, biotechnology, intellectual property, and technology commercialization.
Anh earned his PhD in Nanoscience and Microsystems Engineering from the University of New Mexico and later spent two years as a postdoctoral fellow at the U.S. Food and Drug Administration. He also brings several years of experience supporting federal technology commercialization and innovation programs, working with emerging technologies and helping move research toward practical applications.
At In Silico Biolabs, he leads product architecture, software development, technical strategy, and commercialization.
Charlie Villanueva
Strategic Advisor, Biotechnology & Commercialization
Charlie Villanueva advises In Silico Biolabs on biotechnology commercialization, market strategy, partnerships, and company development. He currently serves as SVP of Commercialization at Azuca, where he leads commercialization strategy, manufacturing scale-up, and the translation of biotechnology products into market-ready offerings.
His background spans the full product commercialization lifecycle. At Nature's Toolbox (NTxBio), he worked with inventors to develop and commercialize a platform for bioactive small molecules and biologics. At PureColor Inc., he helped grow the company from pre-product to five standard offerings and managed the intellectual property portfolio.
He holds a scientific background from the University of New Mexico, including research experience in computational chemistry using VASP, Gaussian, and NAMD.
Let's talk about your molecules.
Interested in OptiSynth, pilot collaborations, or custom cheminformatics infrastructure? Contact In Silico Biolabs to explore how computational synthesis intelligence can support your work.