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We can provide benefits by derisking and shortening process development, enabling more sustainable and cost efficient process conditions, and providing robust evidence to support processes to regulators. Our expertise lie in applying our technology to the organic chemistry space with particular interest in the agrochemical, fine chemical, pharmaceutical, and polymer industries. SOLVE is a recent spin-out from Imperial College London (April 2024) based in the Molecular Sciences Research Hub, White City, London Dr Linden Schrecker CEO
About the company At SOLVE, we enable efficient chemical processes through efficient automated empirical data collection and a suite of machine learning methods. Our services lead to more sustainable and flexible processes informed by robust empirical data. Our core know-how utilises transient flow to collect data series across different continuous process parameters – such as temperature, concentration, and solvent conditions – with high accuracy and 20 times faster than standard methods. Combining this efficient empirical data collection method with machine learning methods allows us to autonomously focus on the most valuable process regions to create a high functioning flexible predictive model.
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