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Chronicles

The story behind the story

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Singapore-based ChemLex raised a $45M funding round led by Granite Asia to build an AI-powered, automated chemistry lab to accelerate drug discovery

Rachyl Jones / Semafor :

Semafor Rachyl Jones

Context & Ripple Effects

ChemLex’s round arrives amid a visible funding cycle for AI-and-automation drug-discovery platforms. Glasgow peer Chemify recently secured a $50M+ Series B for AI, robotics and chemistry, following its earlier financing for molecule design and automated synthesis.

The Singapore company also sits near a broader local automation push: Augmentus raised funding to make industrial robotics easier to deploy, while earlier AI drug-discovery financing for XtalPi showed that investors will fund the category at substantial scale.

First-order effects

  • ChemLex gains $45M, led by Granite Asia, to develop the AI-powered automated lab it says will accelerate drug discovery.
  • Granite Asia becomes the lead backer of ChemLex’s lab-building effort, tying the round’s immediate execution risk to the company’s ability to turn funding into an operating discovery platform.

Second-order effects

  • ChemLex now enters a more directly financed competitive set that includes Chemify; comparable rounds make the race to demonstrate integrated AI-and-robotics chemistry workflows more consequential for both companies.
  • Pharmaceutical customers evaluating external discovery platforms may see more competing options that combine molecule design with laboratory execution, rather than offering software or lab services separately.

Third-order effects

  • If well-funded platforms can make automated labs operational at scale, differentiation in AI drug discovery may shift from model claims toward control of the end-to-end experimental loop: design, synthesis and iteration.
  • The pattern points to a capital-intensive segment of life-sciences AI in which companies must finance both software development and physical laboratory automation, potentially favoring teams able to raise repeatedly.

The trend: AI drug discovery is evolving from model-led molecule design toward vertically integrated, automated laboratory platforms backed by larger venture rounds.