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High Throughput Experimentation and Continuous Flow Synthesis of Active Pharmaceutical IngredientsShruti Biyani (12877664) 24 June 2022 (has links)
<p>Continuous flow synthesis provides an efficient, rapidly scalable, safer, and improved synthetic route over traditional batch synthesis owing to enhanced heat and mass transfer. High throughput experimentation (HTE) is a powerful tool to discover novel reaction conditions and optimize challenging transformations in significantly small amount of time and by exploring multiple arrays of reactions. The utilization of desorption electrospray ionization mass spectrometry (DESI-MS) couple to HTE enables the exploration of 384 unique reaction conditions in just ~7 minutes. Chapter 1 highlights the different organic transformations and the target-based synthesis that have been studied using the HTE in the literature. Validation of the HTE-DESI-MS was investigated by performing a large set of aldol reactions on triacetic acid lactone (TAL), a compound well studied for use as a bio-based platform molecule which can be transformed to a range of valuable agrochemicals, commodity chemicals and intermediates for pharmaceutical industry. Two different active pharmaceutical ingredients namely, HSN-608 and Lorazepam have been synthesized using continuous manufacturing. HTE-DESI MS tools were utilized for rapid reaction screening for Sonogashira couplings for the development of telescoped continuous flow synthesis of an alkynyl naphthyridine anti-cancer agent, HSN-608. It is a fms-like tyrosine kinase 3 (FLT-3) inhibitor, a drug-lead compound for potential treatment of acute myeloid leukemia. Furthermore, a 5-step continuous flow synthesis involving N-acylation, cyclization, N-oxidation, polonovski-type rearrangement, and hydrolysis has been developed for Lorazepam, an essential generic active pharmaceutical ingredient under shortage. Different synthetic routes scouting, and impurity profiling was done to propose the novel route that was further developed under continuous flow conditions with optimization of each step.</p>
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