AI tools for chemistry, biotech and drug discovery
Short answer
Retrosynthesis, generative molecule design and protein engineering with AI: European vendors compared on pricing, privacy and use cases.
In chemistry and biotechnology, AI moves the most expensive part of the work forward: instead of screening thousands of variants in the lab, candidates are pre-selected computationally and only the most promising ones are synthesised or expressed.
The tools cover three tasks: retrosynthesis – how can a target molecule be made at all, generative design – which structure meets the desired profile, and protein engineering – which sequence variant is more stable or more active.
Because structure data and sequences are among a research programme's most valuable IP, EU headquarters, contractual data separation and the option of local installation are hard selection criteria in this category.
All tools in this category (2)
IktosParis-based specialist for generative molecule design: Makya designs new drug candidates against a target profile, Spaya plans the matching synthesis routes.
PaidGDPR / EU
SYNTHIA (Merck KGaA)Retrosynthesis software by Merck of Darmstadt: SYNTHIA breaks a target molecule down into possible synthesis routes, drawing on more than 100,000 chemist-coded reaction rules.
PaidUnclear
Frequently asked questions
What can AI retrosynthesis actually do?
It proposes synthesis routes from commercially available starting materials to the target molecule, scored by step count, cost and availability. It does not replace the judgement of experienced synthetic chemists but saves a lot of search time.
Are there affordable options for universities?
Yes. SYNTHIA Lab explicitly targets academic and non-profit labs and is far cheaper than the industrial licence; Iktos also offers academic terms for its retrosynthesis tool.
Are my molecular structures safe in the cloud?
European vendors contractually guarantee tenant-separated processing and offer NDAs. For very early leads or pending patent filings, an on-premises installation remains the safer choice.
Do I need my own lab?
For protein engineering, yes: platforms like Cradle learn from your own measurements and only get really good over several rounds. Pure synthesis planning works without immediate lab capacity.