Highly Parallel Optimisation of Nickel-Catalysed Suzuki Reactions through Automation and Machine Intelligence

We report the development and application of a scalable machine learning optimisation framework for batched multi-objective reaction optimisation. Through experimental data-derived benchmarks, we demonstrate our approach’s capacity to efficiently handle large parallel batches and high-dimensional search spaces characteristic of high-throughput experimentation (HTE). We also establish the framework’s robustness to reaction... Show more