The synthesis of small molecules is an essential step in drug development. Recent advances in artificial intelligence have led to substantial breakthroughs in the area of computer-aided synthesis planning, in particular for the development of data-driven retrosynthetic software. However, gaps remain in coupling this software with continuous manufacturing aiming towards fully autonomous syntheses. Additionally, regulatory bodies are pushing the transition from batch to continuous flow in pharmaceutical industry to ensure safer, cheaper, and more environmentally friendly drug production. This research proposal brings a groundbreaking chemical engineering approach to optimize reaction conditions and telescope syntheses in flow, to aid chemists in the design of new synthesis routes and to provide the missing link for an autonomous system. The Laboratory of Chemical Technology is world-wide known for its expertise in multiscale modeling applied to industries where continuous manufacturing is commonplace. The multiscale modeling approach, with the focus on kinetic modeling and artificial intelligence, will be applied to the field of synthesis planning. Quantum chemical calculations and new experimental measurements will support and validate these models. The aim of this project is to predict the feasibility of a reaction in flow, as well as optimal reaction conditions and associated yield of target and byproducts.