Major milestone unlocked: Our recent case study with Pfizer

Major milestone unlocked: In our recent case study with Pfizer, we showed that ReactWise is delivering measurable real-world impact for chemists facing complex multi-objective optimization.

The challenge was to identify a temperature profile for a hydrogenation process that could maximize yield while minimizing impurity across a complex, highly interdependent design space.

Using an iterative multi-objective Bayesian optimization workflow, we explored broad operating ranges, rapidly identified the variables that mattered most, and converged on the optimal region far more efficiently than traditional trial-and-error experimentation.

The outcome was 97.5% yield with 1% impurity, alongside the discovery of a critical parameter related to the temperature profile that materially influenced process performance.

By optimizing hold temperatures, hold times, temperature ramp rates, and the broader time-temperature profile together, this work highlights what an AI copilot for chemical process development can make possible: faster learning, smarter experimentation, and better process outcomes.

A strong example of how AI can help scientific teams navigate process complexity with greater speed, precision, and confidence.

Let’s make chemistry smarter - together.

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