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. RetSynth 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.
RetSynth
Retrosynthesis and pathway discovery for chemical and biological production.
RetSynth 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.
RetSynth 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.
RetSynth 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 RetSynth 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.
{
"product": "RetSynth",
"mode": "pathway_discovery",
"target": { "name": "target_compound",
"identifier": "compound_id_or_inchi" },
"route": { "rank": 1, "steps": 6,
"type": "biological_or_hybrid" },
"reactions": [
{ "id": "R07003", "enzyme": "EC 2.5.1.21",
"genes": ["gene_candidate_1"],
"substrates": ["compound_a", "compound_b"],
"products": ["compound_c"] }
],
"outputs": ["pathway_graph", "reaction_table", ...]
}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.
Across molecular industries.
Wherever molecules, reactions, pathways, and production feasibility matter.
Industrial biotechnology
Pathway design for production strains and fermentation.
Specialty chemicals
Route discovery for high-value, low-volume molecules.
Pharmaceutical process development
Feasibility screening for scale-up and process routes.
Synthetic biology
Enzyme and pathway exploration for engineered organisms.
Materials and polymers
Synthesis planning for functional and structural materials.
Sustainable fuels and chemicals
Alternative feedstock and low-carbon route analysis.
Academic and translational research
Pathway mapping and computational feasibility studies.
Government and defense innovation
Biomanufacturing and molecular resilience programs.
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 RetSynth 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.
Let's talk about your molecules.
Interested in RetSynth, pilot collaborations, or custom cheminformatics infrastructure? Contact In Silico Biolabs to explore how computational synthesis intelligence can support your work.