AI-Powered Chemistry Solutions for Drug Discovery Teams

Route design, forward synthesis, and SA scoring across a whole discovery program

Diagram showing a pipeline or flow from point A through a chemical reaction or processing stage to point B.

Forward Synthesis · SA Score · Retrosynthesis

How AI Connects Route Design to Your Team's Data

Discovery programs generate years of internal synthesis data: ELN records, past routes, and records of what worked and what failed. This data is rarely reused across a portfolio. ChemAIRS® combines AI-generated route design with your own experimental history, so route proposals reflect published chemistry and also what your team has already learned on every target in the pipeline.

Retrosynthesis for Discovery Teams

ChemAIRS® combines machine learning and chemical intuition to generate feasible, diverse synthetic routes for both existing and novel molecules, offering multiple reaction strategies so teams can optimize for yield, cost, complexity, or route length.
ChemAIRS® integrates tens of millions of building block data points to identify shorter, more efficient routes, reducing synthesis steps by 20 to 70 percent. By accessing a team's own ELN (Electronic Lab Notebook) entries, it also identifies synthetic routes with a track record of experimental success, improving reproducibility across a program rather than starting from zero on every target.

Retrosynthesis in Practice:

FDA-Accepted

Route Design for Daraxonrasib (RMC-6236)

RAS(ON) inhibitor

Read the case study Agrochemical

Route Design for Corteva's New Insecticide

New ISO common name granted

Read the case study 9 Steps → 4

Route Design for Sonrotoclax (BGB-11417)

Late-stage head group installation

Read the case study

Retrosynthesis Feature

Forward Synthesis for Discovery Teams

Forward Synthesis is a computational tool that lets teams create and evaluate molecular libraries before running synthesizability screenings, working across two dimensions: the core skeleton that defines a molecule's structure, and the synthetic route that determines how it can be built.
ChemAIRS® helps teams rapidly generate large-scale molecular libraries while ensuring every candidate is actually feasible to synthesize, filtering out structures prone to instability, degradation, or toxicity risk before they ever reach a chemist's bench.

Forward Synthesis Feature

SA Score for Discovery Teams

SA Score evaluates synthesizability with AI-driven precision, helping teams assess feasibility and prioritize the most accessible compounds by analyzing building block availability, reaction complexity, and cost.
ChemAIRS® evaluates hundreds of thousands of molecules in hours, ranking them by synthetic accessibility so a full program's candidate pool can be triaged overnight. In a 1,346-molecule validation study, ChemAIRS® matched Merck's expert synthesis team, with its AI-driven assessments identifying viable intermediates that human experts had overlooked.