Optimization with Uncertainty for Pharmaceutical Process Design - Ibuprofen Synthesis as case study

By intensifying the manufacturing processes of active pharmaceutical ingredients, there is potential for enhanced productivity and efficiency. This approach may also contribute to a reduction in environmental impact and result in savings from both energy and cost. In this contribution, optimum operational conditions that maximize the concentration of 1-(4-isobutylphenyl)-ethanol (IBPE), which is an intermediate product for the synthesis of ibuprofen, are studied. The results from deterministic and stochastic optimization techniques are performed and discussed. Since the uncertainties are present in the process/kinetics models, we account for the uncertainties in assessing the robustness of the proposed solution. To this end, MOSKopt stochastic simulation-based optimization framework is used to deal with uncertain parameters in the constraints. The optimization under uncertainty yields different operational conditions with roughly 10 grams less of product in the batch. This optimization with uncertainty approach provides the engineer with the flexibility to generate and test robust design concepts as a trade-off between objective function (such as high yield) and confidence in the expected performance.