Who should use the AI-Driven Molecule Synthesis and Hit Discovery workflow?
Teams or solo builders working on life sciences tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Life Sciences
Leverage Molecule.one's AI and robotic synthesis platform to plan retrosynthesis, execute high-throughput synthesis, and discover validated hits for target molecules.
Deliverable outcome
Biological activity data for top hits, enabling go/no-go decisions for lead optimization.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
Biological activity data for top hits, enabling go/no-go decisions for lead optimization.
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use Molecule.one to a prioritized list of 2-3 retrosynthetic routes with predicted feasibility scores. Then, you pass the output to Molecule.one to a fully specified hte plate design ready for robotic execution. Then, you pass the output to Molecule.one to a completed hte run with raw analytical data for all reactions. Then, you pass the output to Molecule.one to a prioritized list of 5-10 hit conditions with validated yield and purity data. Then, you pass the output to Molecule.one to 2-3 validated, purified target molecules with confirmed identity and >95% purity. Finally, Arctoris is used to biological activity data for top hits, enabling go/no-go decisions for lead optimization.
Define Target and Generate Retrosynthetic Pathways
A prioritized list of 2-3 retrosynthetic routes with predicted feasibility scores.
Design High-Throughput Experiment (HTE) Library
A fully specified HTE plate design ready for robotic execution.
Execute Robotic Synthesis and Inline Analysis
A completed HTE run with raw analytical data for all reactions.
Analyze HTE Data and Identify Hits
A prioritized list of 5-10 hit conditions with validated yield and purity data.
Scale-Up and Validate Top Hits
2-3 validated, purified target molecules with confirmed identity and >95% purity.
Assay Hits for Biological Activity (Optional)
Biological activity data for top hits, enabling go/no-go decisions for lead optimization.
Input the target molecule structure (SMILES or SDF) into Molecule.one's AI retrosynthesis engine. The AI will propose multiple synthetic routes, ranking them by feasibility, cost, and yield. Review and select the top 2-3 routes for experimental validation.
Why Molecule.one: Molecule.one is explicitly a retrosynthesis planning platform, directly matching the step's need for retrosynthetic pathway generation.
For each selected route, define a matrix of reaction parameters (catalysts, solvents, temperatures, stoichiometries) using Molecule.one's HTE design module. Generate a combinatorial library of up to 96 reactions per plate, ensuring coverage of key variables.
Why Molecule.one: Molecule.one includes a high-throughput synthesis module and reagent database, directly supporting HTE library design.
Upload the HTE plate design to Molecule.one's robotic synthesis platform. The robots will perform the reactions in parallel, with inline HPLC or LC-MS analysis after a fixed reaction time. Monitor real-time data to flag failed reactions early.
Why Molecule.one: Molecule.one's high-throughput synthesis capability aligns with robotic synthesis, though inline LC-MS is not explicitly listed; it is the closest match from the menu.
Use Molecule.one's data analysis module to process LC-MS traces, calculate yields, and identify reaction conditions that produce the target molecule with >70% purity. Generate a hit list ranked by yield and purity, with statistical confidence intervals.
Why Molecule.one: Molecule.one includes an HTE data analysis module, directly matching the step's requirement.
Select the top 2-3 hit conditions and perform scale-up reactions (e.g., 100 mg to 1 g) using the same robotic platform or manual synthesis. Purify the product (e.g., column chromatography) and confirm identity via NMR and HRMS.
Why Molecule.one: Molecule.one's high-throughput synthesis can support scale-up, though it lacks explicit mention of purification or NMR/HRMS; it is the best fit from the menu.
If the target molecule is intended for a specific biological target, submit the validated hits to a relevant in vitro assay (e.g., binding affinity, enzyme inhibition). Use the results to select the most promising candidate for further optimization.
Why Arctoris: Arctoris offers high-throughput screening and real-time kinetic profiling, which directly supports in vitro biological assays.
§ Before you start
Teams or solo builders working on life sciences tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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