(373d) Nonlinear Optimisation of Continuous Artemisinin Crystallisation with Explicit NRTL Model-Based Solubility Prediction
AIChE Annual Meeting
2017
2017 Annual Meeting
Pharmaceutical Discovery, Development and Manufacturing Forum
Model Based Integrated Design of Pharmaceutical Drug Substance Processes II
Tuesday, October 31, 2017 - 1:36pm to 1:58pm
One crucial aspect of continuous processing is the continuous separation of Active Pharmaceutical Ingredient (API) products, often at low scales of process throughput and strict purity requirements. Research in product separation, including downstream drug product formulation, is a vibrant area (Ierapetritou et al., 2016; Vural Gürsel et al., 2017; Yabuta et al., 2017). The recent technological development of plug flow crystallisers and Continuous Oscillatory Baffled Crystallisers (COBC, which operate in an oscillatory plug flow regime) offers production advantages, including enhanced heat and mass transfer and improved profile temperature control (Brown and Ni, 2011; McGlone et al., 2015).
Our recent publications explore process modelling, simulation and optimisation of the continuous synthesis and separation of ibuprofen (Jolliffe and Gerogiorgis, 2017a) and artemisinin (Jolliffe and Gerogiorgis, 2017b). By using systematic kinetic parameter estimation, solubility prediction via the UNIFAC method, and comprehensive economic evaluation, optimal total costs have been determined.
Artemisinin is a key antimalarial, and its continuous synthesis has recently been demonstrated (Kopetzki et al., 2013; Gilmore et al., 2014); product recovery and purity enhancement via crystallisation is a viable technique (Malwade et al., 2016). The present paper investigates further the modelling and systematic optimisation of continuous artemisinin crystallisation incorporating explicit solubility predictions via the Non-Random Two-Liquid (NRTL) model. Modelling a plug-flow COBC helps ensure high heat and mass transfer rates, with minimal impact of temperature and concentration gradients on the API product. Toluene, used in a promising CPM process for artemisinin (Horváth et al., 2015), is assumed to be the process solvent; the upstream portion of the flowsheet (reactor) performance is analysed on the basis of previous work (Jolliffe and Gerogiorgis, 2016). The antisolvents considered encompass three different binary mixtures (ethanol and ethyl acetate, ethanol and acetone, or acetone and ethyl acetate) chosen due to to their pharmaceutical processing suitability and the availability of solubility data and NRTL parameters (Nti-Gyabaah et al., 2010). The ratio of antisolvents in the binary mixture ranges continuously between 1:9 to 9:1 by weight. Similarly, the ratio of process solvent (toluene) to binary antisolvent mixture ranges between 1:1 to 1:5 by weight. A continuous crystalliser operating temperature range (between 40 °C and 5 °C) has been considered. Crystal growth and productivity have been modelled on the basis of similar systems (Horváth et al., 2015), and impurities have been assumed to not co-crystallise with the API product.
The nonlinear optimisation (NLP) formulation encompasses the optimal choice of antisolvent, rate of antisolvent addition and the operating temperature which is preferable for continuous artemisinin crystallization. Our results include objective function (minimal cost) surfaces for a range of key variables, such as API recovery; insightful three-dimensional illustrations are obtained for process cost as a function of decision variables, e.g. crystallisation operating temperature and ratio of binary antisolvent mixture addition over incoming reactor effluent. The systematic optimisation of technoeconomic indices under explicit process equilibria and thermodynamic solubility constraints offers unprecedented insight into fine-tuning Continuous Pharmaceutical Manufacturing (CPM) process design and operation.
LITERATURE REFERENCES
Brown, C.J., Ni, X., 2011. Online evaluation of paracetamol antisolvent crystallization growth rate with video imaging in an oscillatory baffled crystallizer. Cryst. Growth Des. 11, 719â725.
Gilmore, K., Kopetzki, D., Lee, J.W., Horváth, Z., McQuade, D.T., Seidel-Morgenstern, A., Seeberger, P.H., 2014. Continuous synthesis of artemisinin-derived medicines. Chem. Commun. 50, 12652â12655.
Horváth, Z., Horosanskaia, E., Lee, J.W., Lorenz, H., Gilmore, K., Seeberger, P.H., Seidel-Morgenstern, A., 2015. Recovery of artemisinin from a complex reaction mixture using continuous chromatography and crystallization. Org. Process Res. Dev. 19, 624â634.
Ierapetritou, M., Muzzio, F., Reklaitis, G., 2016. Perspectives on the continuous manufacturing of powder-based pharmaceutical processes. AIChE J. 62, 1846â1862.
Jensen, K.F., 2017. Flow chemistryâMicroreaction technology comes of age. AIChE J. 63, 858â869.
Jolliffe, H.G., Gerogiorgis, D.I., 2017a. Technoeconomic optimisation of a conceptual flowsheet for continuous separation of an analgaesic Active Pharmaceutical Ingredient (API). Ind. Eng. Chem. Res., in press.
Jolliffe, H.G., Gerogiorgis, D.I., 2017b. Technoeconomic optimisation and comparative environmental evaluation of continuous crystallisation and antisolvent selection for artemisinin recovery. Comput. Chem. Eng., in press.
Jolliffe, H.G., Gerogiorgis, D.I., 2016. Process modelling and simulation for continuous pharmaceutical manufacturing of artemisinin. Chem. Eng. Res. Des. 112, 310â325.
Kopetzki, D., Lévesque, F., Seeberger, P.H., 2013. A continuous-flow process for the synthesis of artemisinin. Chem.âEur. J. 19, 5450â5456.
Lee, S.L., OâConnor, T.F., Yang, X., Cruz, C.N., Chatterjee, S., Madurawe, R.D., Moore, C.M.V., Yu, L.X., Woodcock, J., 2015. Modernizing pharmaceutical manufacturing: from batch to continuous production. J. Pharm. Innov. 1â9.
Malwade, C.R., Buchholz, H., Rong, B.-G., Qu, H., Christensen, L.P., Lorenz, H., Seidel-Morgenstern, A., 2016. Crystallization of artemisinin from chromatography fractions of Artemisia annua extract. Org. Process Res. Dev. 20, 646â652.
McGlone, T., Briggs, N.E.B., Clark, C.A., Brown, C.J., Sefcik, J., Florence, A.J., 2015. Oscillatory Flow Reactors (OFRs) for continuous manufacturing and crystallization. Org. Process Res. Dev. 19, 1186â1202.
Nti-Gyabaah, J., Gbewonyo, K., Chiew, Y.C., 2010. Solubility of artemisinin in different single and binary solvent mixtures between (284.15 and 323.15) K and NRTL Interaction Parameters. J. Chem. Eng. Data 55, 3356â3363.
Vural Gürsel, I., Kockmann, N., Hessel, V., 2017. Fluidic separation in microstructured devices â Concepts and their Integration into process flow networks. Chem. Eng. Sci.
Yabuta, K., Hirao, M., Sugiyama, H., 2017. Process model for enhancing yield in sterile drug product manufacturing. J. Pharm. Innov. 1â12.