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Medicinal Chemistry Services for Drug Discovery Programs
Chemists who work on your series as their own, with the computational and screening tools to decide what is worth making before anyone makes it.
What slows a series down
Rarely the ideas. Usually the fact that half the compounds a team designs are hard to make, and the chemistry to find that out takes weeks that the program does not have. The cycle stretches, the SAR thins, and decisions get made on fewer data points than anyone wanted.
Our medicinal chemists work inside that loop rather than at the end of it. Designs come back with a view on synthetic feasibility attached, and where the route is genuinely uncertain we model it before committing bench time.
Predicting chemistry before you run it
Our quantum mechanics platform is used prospectively, on live projects, not as a retrospective explanation of what already happened. It predicts reactivity and which site on a molecule will react, improves the quality of a proposed route, helps assign structures when the data are ambiguous, and resolves synthetic problems that have already stalled.
Retrospective QM analysis of unanticipated results showed that most synthetic dead ends were avoidable. Applying the same analysis prospectively has raised success rates, shortened cycle times and improved overall yields across synthetic sequences.
Source cites Glorius et al., Chem. Soc. Rev. 2020, 49, 6154 and Neese et al., J. Am. Chem. Soc. 2019, 141, 2814.
Designing what to make next
Our computer-aided drug design platform runs from hit identification through to IND, with milestones at target validation, hit identification, hit-to-lead and lead optimization.
Virtual screening — computational triage of large compound sets so synthesis effort goes to the candidates worth testing.
Structure-based design — design against the target protein structure where one is available.
Ligand-based design — predictive models built from known actives when no 3D structure of the target exists, which is the situation most programs are actually in.
Hit-to-lead and lead optimization
We support every stage from target validation through hit generation, hit-to-lead and lead optimization — at scales from milligrams to kilograms, across a wide range of chemistry.
Keeping a live series supplied is as much a logistics problem as a chemistry one. Analytical, purification, reagent and building-block teams sit alongside the chemists, and compounds move through a managed supply operation.
Degraders and covalent inhibitors
Two modalities where the chemistry decides whether the program is viable at all, and where we have built dedicated teams rather than handling them case by case.
Targeted protein degraders. Our more than 1,100 chemists have worked on linkers, E3 ligase ligands and target protein ligands since 2016, across more than 180 client collaborations and 238,000 compounds. More than 1,000 distinct linkers have been made, with over 100 held in stock. Deep experience across CRBN, VHL, IAP and MDM2 and newer E3 ligases, with more than 30 CRBN and VHL ligands available now and more than 60 series of target protein ligands already pre-coupled to linkers — which is usually the difference between a first degrader in six weeks and one in six months.
Molecular glues. Degradation without a linker, where a small molecule stabilizes a new interface between an E3 ligase and the target. The design and screening work draws on the same E3 ligase ligand collection and degrader chemistry as the linker-based programs, so both approaches can be run on a target while it is still open which one will work.
Targeted covalent inhibitors. More than 180,000 compounds across over 100 collaborations, with more than 40 warhead types synthesized and 17 available off the shelf. A robotic synthesizer runs up to 500 reactions a day with less dispensing deviation than manual work, and a dedicated purification team handles separation, so a warhead-scan campaign is a matter of days rather than weeks.
How we work with your team
Full-time equivalent — named chemists dedicated to your program, who learn your series and stay with it. This is how most medicinal chemistry work runs.
Fee-for-service — a defined deliverable at an agreed specification, for a discrete piece of work.
The cycle time you actually feel
“Design-make-test-analyze” is where a discovery program either builds momentum or stalls. Every week between a design and its data is a week the biology team spends waiting, and the cost is not the synthesis — it is the question that gets answered late, or not at all.
Shortening that loop is the job. It is why, at WuXi AppTec, medicinal chemistry, computational design and analytical support sit in one team rather than three queues.