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Comprehensive Mass Analysis for Chemical Processes, a Case Study on L-Dopa Manufacture
Li, T. AND X. Li. Comprehensive Mass Analysis for Chemical Processes, a Case Study on L-Dopa Manufacture . GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge, Uk, 16(9):4241-4256, (2014).
This work is about a systematic approach to evaluate chemical process at early stage of development. It involves strategy characterization in the first stage, and detailed mass evaluation in the second. For mass analysis, we developed new algorithms to determine PMI for each input chemical, and components of waste streams. The hazardous chemicals or byproducts are identified and their masses are determined early on, so that chemists can address the issues at process design and development stage. This evaluation is demonstrated with L-Dopa manufacture as a testing case. The mass analysis has been used to evaluate process design options, such as recycle of the wrong enantiomer, and mass impact to improve productivity of critical steps. The projection will help to justify investment in more sustainable options in process design.
To evaluate the “greenness” of chemical processes in route selection and process development, we propose a comprehensive mass analysis to inform the stakeholders from different fields. This is carried out by characterizing the mass intensity for each contributing chemical or waste component with a new algorithm. The analysis is demonstrated with the evaluation of commercial processes for L-Dopa. The plan-wide impacts on inputs are estimated for design features such as the choice of starting material, the use of one-pot synthesis for multiple reactions, recycling of the wrong enantiomer, methods for intermediate isolation, and volumetric productivity. The waste effluent profile is generated to project waste management needs. It has been found that the current biocatalytic process (Ajinomoto) has the best process efficiency and minimal waste treatment needs. The mass efficiency has been improved by at least 6.5 fold through biocatalyst optimization, and reaction intensification employing the crystallization-induced equilibrium shift.