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Autonomous laboratories can accelerate discoveries in chemical synthesis, but this requires automated measurements coupled with reliable decision-making.
The integration of artificial intelligence (AI) and machine learning (ML) in drug design has the potential to transform small molecule drug discovery in the pharmaceutical industry, enhancing the efficiency and productivity of the drug design and discovery process.
Self-Driving Labs (SDLs) combine automated hardware with computational experiment planning tools to reduce the time between experiments and liberate chemists from routine work, allowing them to focus on bigger, more conceptual problems.