Internet shopping, image storage in the cloud, turning a thermostat with an application – all are common. Now, the Internet of things and the cloud are entering the world of chemical research and production, as reported in the journal Angewandte Chemie. The researchers used remote servers in Japan to autonomously optimize the conditions for the synthesis of drugs in the British laboratory. The process was controlled online by researchers in the United States.
Modern production processes can not simply assemble the target molecule; they must be economical, efficient, robust and sustainable. It is therefore necessary to develop various alternative synthetic routes, designed equipment and to find optimum processing parameters. This is impossible without a deep understanding of the reactions that take place and the huge amount of data collected under different conditions. In the field of synthesis of natural products and drugs, this trend is directed towards the automation of repeated reactions and processes of self-optimization. They are based on machine learning and feedback in the form of measurements obtained from observation of reactions.
Researchers led by Steven V. Lay from the University of Cambridge (UK) and the Fulverton State University of California (US) have now shown that this approach can succeed through international boundaries and time zones – using the cloud. Remote servers in Tokyo (Japan) have autonomously developed optimal synthetic conditions for three pharmaceutical agents that were physically synthesized in laboratories in Cambridge (UK). The process was initiated, controlled and monitored by researchers in Los Angeles (USA) via an internet connection. In this way, machines could optimize individual synthetic steps for tramadol, lidocaine and bupropion as representative samples, with minimal intervention by operators over a period of several hours.
In the case of tramadol, three parameters are different: temperature, residence time and ratio of reactants. Guided by spectroscopic data, the control system performed nine fully autonomous experiments over a period of three hours and identified the optimized conditions for maximum conversion with the highest possible flow and low consumption of the starting materials.
The autonomous nature of this cloud-based approach makes widespread availability of specialized knowledge and equipment and efficiently uses these resources by avoiding layoffs and enabling global co-operation in which distance is irrelevant.
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