(165d) Systematic Optimisation of Continuous Separation for Artemisinin Recovery in Continuous Pharmaceutical Manufacturing

Gerogiorgis, D. I. - Presenter, University of Edinburgh
Jolliffe, H. G., University of Edinburgh
An environment of growing R&D expenditure and increasing competition from generic manufacturers has led to a sustained research interest in Continuous Pharmaceutical Manufacturing (CPM), which has emerged as a promising alternative to the current paradigm of batch production. The latter, while possessing benefits including equipment flexibility and the extensive industry know-how of a mature technology, is hampered by disadvantages including low efficiency (of both material and energy use), problematic process scale-up and poor heat and mass transfer. Moreover, its status as a mature technology means improvements are incremental at best. Novel CPM methodologies provide enticing options toward fostering the concept of Quality by Design (QbD) which is enthusiastically pursued by the US pharmaceutical industry, and the closely related development of Process Analytical Technology (PAT), which focuses on efficient, online pharmaceutical process monitoring and control. The concepts of CPM, QbD and PAT have accordingly received attention and encouragement by influential, world-leading regulatory authorities (Lee et al., 2015).

Artemisinin is one of the most important antimalarial substances available today. First identified and isolated from the plant Artemisia annua in the late 1970s (Tu, 2011), work for which the 2015 Nobel Prize in Physiology/Medicine was awarded, artemisinin is currently produced via batch extraction from the cultivated plant. However, long product lead times, and fluctuating demand due to unpredictable burden of malaria, lead to highly variable prices and production levels (Jolliffe and Gerogiorgis, 2015a). Recent research has demonstrated the continuous synthesis of artemisinin (Kopetzki et al., 2013; Seeberger et al., 2014). This novel synthesis uses a waste product from the current batch production process as a feedstock, and produces artemisinin via two sequential plug flow reactors, the first of which employs photo-oxidation. Remarkable product yields can be achieved, and the process has been further adapted to produce several artemisinin derivatives (Gilmore et al., 2014).

Critical to harnessing the full potential of CPM is the design and employment of continuous product separation systems. A recent published study of ours has explored the potential performance of eight solvents for continuous crystallisation of artemisinin via both computationally predicted (UNIFAC) and experimentally reported solubilities; results indicate promise for the use of ethanol or ethyl acetate (Jolliffe and Gerogiorgis, 2015a, 2016). We have also previously employed nonlinear optimization toward finding ideal continuous separation scenarios for another API: promising temperatures, solvent and liquid-liquid extraction (LLE) configurations have been determined toward minimising the total CPM process cost, by means of comprehensively considering mass transfer, thermodynamics and detailed economic cost modelling (Jolliffe and Gerogiorgis, 2015b).

The present paper expands upon our previous contributions in the field of CPM: we investigate further the continuous separation of artemisinin by formulating a nonlinear optimization problem comprehensively considering mass transfer modelling via empirical correlations, solubility prediction via group contribution methods (UNIFAC, NRTL), and environmental and sustainability metrics (E-factor, Mass Intensity), for several potential separation unit operations and solvents. The CPM process studied here, based on the chemistry developed by Kopetzki et al. (2013), has been shown to be compatible with a range of separation methods (Horváth et al., 2015). The design space illustrates clear nonconvexities for several key process variables, and potential local minima in the final objective surface arise from regions of applicability of empirical relations. The solved problem and our novel results illustrate how the crucial consideration of less easily quantifiable characteristics (e.g. environmental impact, safety, toxicity) can qualify optimised solutions of superior technical performance.


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