Molecule.one develops AI-driven software for custom organic synthesis, utilizing deep learning and a high-throughput laboratory to synthesize complex compounds in as little as two weeks. The platform addresses the challenge of accessing difficult-to-synthesize molecules, enabling pharmaceutical and chemical industries to efficiently obtain diverse compounds on a success-fee basis.
Funding
$4.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Synthesizing novel or complex organic molecules can be a significant bottleneck in pharmaceutical, agrochemical, and specialty chemical research and development. Traditional synthesis methods are often time-consuming, expensive, and have a low success rate, hindering the discovery of new compounds. Accessing diverse chemical libraries with expedited shipping remains a challenge.
Solution
Molecule.one provides an AI-driven platform that accelerates custom organic synthesis, enabling researchers to efficiently obtain diverse and previously inaccessible compounds. The platform leverages deep learning models trained on a large chemical reaction dataset, including data from their own high-throughput experimentation (HTE) lab, to predict optimal synthesis pathways and reaction conditions. Molecule.one's AI copilot, Maria, automates key stages of molecular synthesis, from pathway selection to robotic execution, reducing synthesis times to as little as two weeks. The company offers custom synthesis services, access to a virtual library of over 1 trillion de novo drug-like molecules (SpaceM1), and a synthetic accessibility scoring tool (M1 RetroScore) to enhance drug discovery pipelines. Molecule.one also provides data generation and licensing services, creating custom datasets using their HTE Data Generation Blueprint.
Target Audience
Molecule.one serves pharmaceutical, agrochemical, and specialty chemical companies seeking to accelerate drug discovery and materials science research through efficient access to novel and complex molecules.
Features
- AI-driven retrosynthesis software trained on the world's largest curated reaction dataset from CAS and proprietary HTE lab data
- High-throughput experimentation (HTE) lab capable of running over 100,000 reactions to expand reaction conditions prediction capabilities
- SpaceM1 virtual library of over 1 trillion make-on-demand molecules with diverse chemistry and building blocks
- M1 RetroScore tool for predicting the likelihood of synthesis for novel small molecules
- Maria AI copilot for automating key stages of molecular synthesis
- Direct-to-biology SpaceM1 libraries for hit expansion and discovery
- Custom data generation services using a proprietary HTE Data Generation Blueprint