Celebrating Excellence in Industrial Organic Synthesis, 2019 - ACS Axial
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Celebrating Excellence in Industrial Organic Synthesis, 2019

The Journal of Organic Chemistry has published a Special Issue, put together by guest editors Spencer Dreher at Merck and John Ragan at Pfizer. This Special Issue takes a look at the past, present and future state of applied industrial synthesis through publications from more than 40 different organizations across 14 different countries. The Special Issue also contains perspectives on the future outlook from leaders at research-based organizations, including one from Kai Rossen at Lundbeck, Editor-in-Chief of Organic Process Research & Development. Rossen’s perspective describes the role of Green Chemistry in industrial chemistry, and the importance of assessing the entire, holistic “greenness” of a process, rather than just a select few steps in the route.  

Underscoring the value of industrial research, the guest editors point out that several Nobel Prizes in Chemistry have been awarded to industrial researchers over the years (not to mention, Alfred Nobel himself was an industrial chemist). Industrial organic chemistry, for example, has played a crucial role in the discovery and development of:  

  • Novel antibiotics like vancomycin, which was discovered by scientists at Eli Lilly and Company,
  • Oral contraceptives, including the first hormonal birth control, Enovid, discovered by G. D. Searle, and
  • Anti-HIV protease inhibitors

Looking ahead, industrial chemists have a lot to look forward to:  Not only will the demand for excellence continue to grow, but new technology and tools will accelerate what industrial chemists can accomplish in a day:

  • High-tech revolutions in adjoining scientific fields like genetics, computation/ informatics, and biological screening will present continuous new opportunities to generate more information, more quickly in the preparation, evaluation, and design of new molecules.
  • New Synthesis Tools (think big-data chemistry, robots, and machine-learning algorithms) that can accelerate daily workflow

Access the Special Issue Now to Learn More.

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