A statistically driven, automated approach to optimize glucose transformations to platform chemicals, methyl lactate and levulinic acid, is reported.
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery.
High-throughput experimentation (HTE) has become integral to the pharmaceutical industry with most major pharmaceutical companies investing in automation and high-throughput screening technologies.