Perspectives on the flexibility analysis for continuous pharmaceutical manufacturing processes

doi:10.1016/j.cjche.2021.12.005

Abstract

Abstract: Pharmaceutical continuous manufacturing, especially under the context of COVID-19 pandemic, is regarded as an emerging technology that can guarantee the adequate quality assurance and mitigate process risk while guaranteeing the desirable economic performance. Flexibility analysis is one approach to quantitively assess the capability of chemical process to guarantee feasible operation in face of variations on uncertain parameters. The aim of this paper is to provide the perspectives on the flexibility analysis for continuous pharmaceutical manufacturing processes. State-of-the-art and progress in the flexibility analysis for chemical processes including concept evolution, mathematical model formulations, solution strategies, and applications are systematically overviewed. Recent achievements on the flexibility/feasibility analysis of the downstream dosage form manufacturing process are also touched upon. Further challenges and developments in the field of flexibility analysis for novel continuous manufacturing processes of active pharmaceutical ingredients along with the integrated continuous manufacturing processes are identified.

Key words: Pharmaceuticals, Model, Optimization, Continuous manufacturing, Flexibility, Uncertainty

摘要： Pharmaceutical continuous manufacturing, especially under the context of COVID-19 pandemic, is regarded as an emerging technology that can guarantee the adequate quality assurance and mitigate process risk while guaranteeing the desirable economic performance. Flexibility analysis is one approach to quantitively assess the capability of chemical process to guarantee feasible operation in face of variations on uncertain parameters. The aim of this paper is to provide the perspectives on the flexibility analysis for continuous pharmaceutical manufacturing processes. State-of-the-art and progress in the flexibility analysis for chemical processes including concept evolution, mathematical model formulations, solution strategies, and applications are systematically overviewed. Recent achievements on the flexibility/feasibility analysis of the downstream dosage form manufacturing process are also touched upon. Further challenges and developments in the field of flexibility analysis for novel continuous manufacturing processes of active pharmaceutical ingredients along with the integrated continuous manufacturing processes are identified.

关键词: Pharmaceuticals, Model, Optimization, Continuous manufacturing, Flexibility, Uncertainty

Wenhui Yang, Wuxi Qian, Zhihong Yuan, Bingzhen Chen. Perspectives on the flexibility analysis for continuous pharmaceutical manufacturing processes[J]. Chinese Journal of Chemical Engineering, 2022, 41(1): 29-41.

Wenhui Yang, Wuxi Qian, Zhihong Yuan, Bingzhen Chen. Perspectives on the flexibility analysis for continuous pharmaceutical manufacturing processes[J]. 中国化学工程学报, 2022, 41(1): 29-41.

References

[1] S. Lier, D. Wörsdörfer, M. Grünewald, Transformable production concepts: flexible, mobile, decentralized, modular, fast, Chembioeng Rev. 3(1) (2016) 16–25.
[2] A.P. Howard, L.S. Slaughter, K.M. Carey, J.W. Lillard, Bridges to biotechnology and bioentrepreneurship: improving diversity in the biotechnology sector, Nat. Biotechnol. 39(11) (2021) 1468–1474.
[3] D.J. Wettstein, S. Boes, Assessing social preferences in reimbursement negotiations for new Pharmaceuticals in Oncology: an experimental design to analyse willingness to pay and willingness to accept, BMC Health Serv. Res. 21(1) (2021) 1–18.
[4] A.L. Kelly, T. Gough, R.S. Dhumal, S. Halsey, A. Paradkar, Monitoring ibuprofen–nicotinamide cocrystal formation during solvent free continuous cocrystallization (SFCC) using near infrared spectroscopy as a PAT tool, Int. J. Pharm. 426(1–2) (2012) 15–20.
[5] L.X. Yu, G. Amidon, M.A. Khan, S.W. Hoag, J. Polli, G.K. Raju, J. Woodcock, Understanding pharmaceutical quality by design, AAPS J. 16(4) (2014) 771– 783.
[6] A. Rogers, M. Ierapetritou, Challenges and opportunities in modeling pharmaceutical manufacturing processes, Comput. Chem. Eng. 81(2015) 32– 39.
[7] A. Giridhar, A. Gupta, M. Louvier, G. Joglekar, Z.K. Nagy, G.V. Reklaitis, Intelligent process management for continuous operations in pharmaceutical manufacturing, Comput. Aided Chem. Eng. Amsterdam: Elsevier (2014) 391– 396.
[8] Q.L. Su, S. Ganesh, M. Moreno, Y. Bommireddy, M. Gonzalez, G.V. Reklaitis, Z.K. Nagy, A perspective on Quality-by-Control (QbC) in pharmaceutical continuous manufacturing, Comput. Chem. Eng. 125(2019) 216–231.
[9] ICH Q13 ICH harmonized guideline—continuous manufacturing of drug substances and drug products, 2021.
[10] Q.L. Su, S. Ganesh, D.B. Le Vo, A. Nukala, Y. Bommireddy, M. Gonzalez, G.V. Reklaitis, Z.K. Nagy, A quality-by-control approach in pharmaceutical continuous manufacturing of oral solid dosage via direct compaction, Comput. Aided Chem. Eng. Amsterdam: Elsevier (2019) 1327–1332.
[11] K. Plumb, Continuous processing in the pharmaceutical industry: changing the mind set, Chem. Eng. Res. Des. 83(6) (2005) 730–738.
[12] R. Singh, M. Ierapetritou, R. Ramachandran, An engineering study on the enhanced control and operation of continuous manufacturing of pharmaceutical tablets via roller compaction, Int. J. Pharm. 438(1–2) (2012) 307–326.
[13] A. Domokos, B. Nagy, B. Szilágyi, G. Marosi, Z.K. Nagy, Integrated continuous pharmaceutical technologies—A review, Org. Process. Res. Dev. 25(4) (2021) 721–739.
[14] M. Baumann, T.S. Moody, M. Smyth, S. Wharry, A perspective on continuous flow chemistry in the pharmaceutical industry, Org. Process. Res. Dev. 24(10) (2020) 1802–1813.
[15] A. Adamo, R.L. Beingessner, M. Behnam, J. Chen, T.F. Jamison, K.F. Jensen, J.C. Monbaliu, A.S. Myerson, E.M. Revalor, D.R. Snead, T. Stelzer, N. Weeranoppanant, S.Y. Wong, P. Zhang, On-demand continuous-flow production of pharmaceuticals in a compact, reconfigurable system, Science 352(6281) (2016) 61–67.
[16] R.L. Hartman, Managing solids in microreactors for the upstream continuous processing of fine chemicals, Org. Process. Res. Dev. 16(5) (2012) 870–887.
[17] K.P. Cole, M.D. Johnson, Continuous flow technology vs. the batch-by-batch approach to produce pharmaceutical compounds, Expert. Rev. Clin. Pharmacol. 11(1) (2018) 5–13.
[18] S.D. Schaber, D.I. Gerogiorgis, R. Ramachandran, J.M.B. Evans, P.I. Barton, B.L. Trout, Economic analysis of integrated continuous and batch pharmaceutical manufacturing: a case study, Ind. Eng. Chem. Res. 50(17) (2011) 10083– 10092.
[19] N. Collins, J. Malerich, J. Szeto, J.A. Kozocas, Continuous flow synthesis of 490 ibuprofen, U.S. Pat., US20210114962A1(2021).
[20] https://www.pharmtech.com/view/advanced-manufacturing-technologiesshift-outside-the-box.
[21] R.E. Swaney, I.E. Grossmann, An index for operational flexibility in chemical process design. Part I: Formulation and theory, AIChE J. 31(4) (1985) 621– 630.
[22] J.H. Saleh, G. Mark, N.C. Jordan, Flexibility: a multi-disciplinary literature review and a research agenda for designing flexible engineering systems, J. Eng. Des. 20(3) (2009) 307–323.
[23] E.A. Wolff, S. Skogestad, J. Perkins, In a procedure for operability analysis, In: Institution of Chemical Engineers Symposium Series, London, U.K., 1994.
[24] F.V. Lima, Z.Y. Jia, M. Ierapetritou, C. Georgakis, Similarities and differences between the concepts of operability and flexibility: The steady-state case, AIChE J 56(3) (2010) 702–716.
[25] A.K. Saboo, M. Morari, Design of resilient processing plants—IV: Some new results on heat exchanger network synthesis, Chem. Eng. Sci. 39(3) (1984) 579–592.
[26] A.K. Saboo, M. Morari, D.C. Woodcock, Design of resilient processing plants— VIII. A resilience index for heat exchanger networks, Chem. Eng. Sci. 40(8) (1985) 1553–1565.
[27] M. Morari, Design of resilient processing plants—III: A general framework for the assessment of dynamic resilience, Chem. Eng. Sci. 38(11) (1983) 1881– 1891.
[28] I.E. Grossmann, M. Morari, Operability, resiliency, and flexibility: Process design objectives for a changing world. In A. W. Westerberg, & H. H. Chien (Eds.), Proc. 2nd international conference on foundations computer aided process design, CACHE 937(1984).
[29] I.E. Grossmann, B.A. Calfa, P. Garcia-Herreros, Evolution of concepts and models for quantifying resiliency and flexibility of chemical processes, Comput. Chem. Eng. 70(2014) 22–34.
[30] A. Rogers, M. Ierapetritou, Feasibility and flexibility analysis of black-box processes Part 1: Surrogate-based feasibility analysis, Chem. Eng. Sci. 137(2015) 986–1004.
[31] A. Rogers, M. Ierapetritou, Feasibility and flexibility analysis of black-box processes part 2: Surrogate-based flexibility analysis, Chem. Eng. Sci. 137(2015) 1005–1013.
[32] M.G. Ierapetritou, New approach for quantifying process feasibility: Convex and 1-D quasi-convex regions, AIChE J. 47(6) (2001) 1407–1417.
[33] L.T. Biegler, I.E. Grossmann, A.W. Westerberg, Systematic Methods for Chemical Process Design, Prentice Hall PTR, U.S., 1997.
[34] E.N. Pistikopoulos, Uncertainty in process design and operations, Comput. Chem. Eng. 19(1995) 553–563.
[35] K.P. Halemane, I.E. Grossmann, Optimal process design under uncertainty, AIChE J. 29(3) (1983) 425–433.
[36] E.N. Pistikopoulos, T.A. Mazzuchi, A novel flexibility analysis approach for processes with stochastic parameters, Comput. Chem. Eng. 14(9) (1990) 991– 1000.
[37] V.D. Dimitriadis, E.N. Pistikopoulos, Flexibility analysis of dynamic systems, Ind. Eng. Chem. Res. 34(12) (1995) 4451–4462.
[38] H. Zhou, Y. Qian, X.X. Li, J. Cui, A. Kraslawski, The dynamic flexibility of batch exothermic reaction system: take into account the effect of the initial operational temperature, Chin. J. Chem. Eng. 16(6) (2008) 916–922.
[39] Y. Friedman, G.V. Reklaitis, Flexible solutions to linear programs under uncertainty: Equality constraints, AIChE J. 21(1) (1975) 83–90.
[40] I.E. Grossmann, R.W.H. Sargent, Optimum design of chemical plants with uncertain parameters, AIChE J. 24(6) (1978) 1021–1028.
[41] I.E. Grossmann, K.P. Halemane, Decomposition strategy for designing flexible chemical plants, AIChE J. 28(4) (1982) 686–694.
[42] R.E. Swaney, Analysis of operational flexibility in chemical process design (uncertainty, optimization), Ph. D. Thesis, Carnegie Mellon Univ, U.S., 1983.
[43] I.E. Grossmann, K.P. Halemane, R.E. Swaney, Optimization strategies for flexible chemical processes, Comput. Chem. Eng. 7(4) (1983) 439–462.
[44] I.E. Grossmann, C.A. Floudas, Active constraint strategy for flexibility analysis in chemical processes, Comput. Chem. Eng. 11(6) (1987) 675–693.
[45] E.N. Pistikopoulos, I.E. Grossmann, Optimal retrofit design for improving process flexibility in linear systems, Comput. Chem. Eng. 12(7) (1988) 719– 731.
[46] D.A. Straub, I.E. Grossmann, Integrated stochastic metric of flexibility for systems with discrete state and continuous parameter uncertainties, Comput. Chem. Eng. 14(9) (1990) 967–985.
[47] D.A. Straub, I.E. Grossmann, Design optimization of stochastic flexibility, Comput. Chem. Eng. 17(4) (1993) 339–354.
[48] D.A. Straub, I.E. Grossmann, Evaluation and optimization of stochastic flexibility in multiproduct batch plants, Comput. Chem. Eng. 16(2) (1992) 69–87.
[49] S. Skogestad, M. Morari, Design of resilient processing plants-IX. Effect of model uncertainty on dynamic resilience, Chem. Eng. Sci. 42(7) (1987) 1765– 1780.
[50] M.J. Mohideen, J.D. Perkins, E.N. Pistikopoulos, Optimal synthesis and design of dynamic systems under uncertainty, Comput. Chem. Eng. 20(1996) S895– S900.
[51] M.J. Mohideen, J.D. Perkins, E.N. Pistikopoulos, Optimal design of dynamic systems under uncertainty, AIChE J. 42(8) (1996) 2251–2272.
[52] G.M. Ostrovsky, N.N. Ziyatdinov, T.V. Lapteva, Optimization problem with normally distributed uncertain parameters, AIChE J. 59(7) (2013) 2471–2484.
[53] Z.H. Yuan, B.Z. Chen, J.S. Zhao, An overview on controllability analysis of chemical processes, AIChE J. 57(5) (2011) 1185–1201.
[54] T.V. Thomaidis, E.N. Pistikopoulos, Integration of flexibility, reliability and maintenance in process synthesis and design, Comput. Chem. Eng. 18(1994) S259–S263.
[55] H. Jiang, B. Chen, Research progress of chemical process stability analysis, CIESC J. 69(1) (2017) 76–87(in Chinese).
[56] F. Xiao, J. Du, L.L. Liu, G.Y. Luan, P.J. Yao, Simultaneous optimization of synthesis and scheduling of cleaning in flexible heat exchanger networks, Chin. J. Chem. Eng. 18(3) (2010) 402–411.
[57] P.A. Bahri, J.A. Bandoni, J.A. Romagnoli, Integrated flexibility and controllability analysis in design of chemical processes, AIChE J. 43(4) (1997) 997–1015.
[58] D.S. Dvoretsky, S.I. Dvoretsky, S.V. Mishchenko, G.M. Ostrovsky, New approaches to the integrated synthesis of flexible automated chemical engineering systems, Theor. Found. Chem. Eng. 44(1) (2010) 67–75.
[59] M. Escobar, J.O. Trierweiler, I.E. Grossmann, Simultaneous synthesis of heat exchanger networks with operability considerations: Flexibility and controllability, Comput. Chem. Eng. 55(2013) 158–180.
[60] Q. Xu, B.Z. Chen, X.R. He, An extended algorithm of flexibility analysis in chemical engineering processes, Chin. J. Chem. Eng. 1(2001) 51–57.
[61] W.C. Rooney, L.T. Biegler, Design for model parameter uncertainty using nonlinear confidence regions, AIChE J. 47(8) (2001) 1794–1804.
[62] V. Goyal, M.G. Ierapetritou, Determination of operability limits using simplicial approximation, AIChE J. 48(12) (2002) 2902–2909.
[63] L. Zhang, X.R. He, Q. Xu, A modified model for flexibility analysis in chemical engineering processes, Chin. J. Chem. Eng. 12(5) (2004) 673–676.
[64] R.A. Bates, H.P. Wynn, E.S. Fraga, Feasible region approximation: a comparison of search cone and convex hull methods, Eng. Optim. 39(5) (2007) 513–527.
[65] F. Zhao, X. Chen, Analytical and triangular solutions to operational flexibility analysis using quantifier elimination, AIChE J. 64(11) (2018) 3894–3911.
[66] J.L. Pulsipher, V.M. Zavala, A mixed-integer conic programming formulation for computing the flexibility index under multivariate Gaussian uncertainty, Comput. Chem. Eng. 119(2018) 302–308.
[67] J.L. Pulsipher, D. Rios, V.M. Zavala, A computational framework for quantifying and analyzing system flexibility, Comput. Chem. Eng. 126(2019) 342–355.
[68] M.P. Ochoa, I.E. Grossmann, Novel MINLP formulations for flexibility analysis for measured and unmeasured uncertain parameters, Comput. Chem. Eng. 135(2020) 106727.
[69] M.P. Ochoa, S. García-Muñoz, S. Stamatis, I.E. Grossmann, Novel flexibility index formulations for the selection of the operating range within a design space, Comput. Chem. Eng. 149(2021) 107284.
[70] G.M. Ostrovski, L.E.K. Achenie, A.M. Karalapakkam, Y.M. Volin, Flexibility analysis of chemical processes: selected global optimization sub-problems, Optim. Eng. 3(1) (2002) 31–52.
[71] S.T. Harding, C.A. Floudas, Global optimization in multiproduct and multipurpose batch design under uncertainty, Ind. Eng. Chem. Res. 36(5) (1997) 1644–1664.
[72] G.M. Ostrovsky, Y.M. Volin, M.M. Senyavin, An approach to solving a twostage optimization problem under uncertainty, Comput. Chem. Eng. 21(3) (1997) 317–325.
[73] G.M. Ostrovsky, L.E.K. Achenie, Y.P. Wang, Y.M. Volin, A new algorithm for computing process flexibility, Ind. Eng. Chem. Res. 39(7) (2000) 2368–2377.
[74] V. Bansal, J.D. Perkins, E.N. Pistikopoulos, Flexibility analysis and design of linear systems by parametric programming, AIChE J. 46(2) (2000) 335–354.
[75] C.G. Raspanti, J.A. Bandoni, L.T. Biegler, New strategies for flexibility analysis and design under uncertainty, Comput. Chem. Eng. 24(9–10) (2000) 2193– 2209.
[76] Z.H. Gümüş C.A. Floudas, Global optimization of nonlinear bilevel programming problems, J. Glob. Optim. 20(1) (2001) 1–31.
[77] C.A. Floudas, Z.H. Gümüş Global optimization in design under uncertainty: feasibility test and flexibility index problems, Ind. Eng. Chem. Res. 40(20) (2001) 4267–4282.
[78] V. Bansal, J.D. Perkins, E.N. Pistikopoulos, Flexibility analysis and design using a parametric programming framework, AIChE J. 48(12) (2002) 2851–2868.
[79] G.M. Ostrovsky, L.E.K. Achenie, Y. Wang, Y.M. Volin, A unique approach for solving sub-problems in flexibility analysis, Chem. Eng. Commun. 189(1) (2002) 125–149.
[80] Z.H. Gümüş C.A. Floudas, Global optimization of mixed-integer bilevel programming problems, Comput. Manag. Sci. 2(3) (2005) 181–212.
[81] I. Banerjee, M.G. Ierapetritou, Feasibility evaluation of nonconvex systems using shape reconstruction techniques, Ind. Eng. Chem. Res. 44(10) (2005) 3638–3647.
[82] V. Goyal, M.G. Ierapetritou, Stochastic MINLP optimization using simplicial approximation, Comput. Chem. Eng. 31(9) (2007) 1081–1087.
[83] Z.N. Pintarič, Z. Kravanja, Identification of critical points for the design and synthesis of flexible processes, Comput. Chem. Eng. 32(7) (2008) 1603–1624.
[84] F. Boukouvala, M.G. Ierapetritou, Feasibility analysis of black-box processes using an adaptive sampling Kriging-based method, Comput. Chem. Eng. 36(2012) 358–368.
[85] H. Jiang, B.Z. Chen, I.E. Grossmann, New algorithm for the flexibility index problem of quadratic systems, AIChE J. 64(7) (2018) 2486–2499.
[86] F. Zhao, I.E. Grossmann, S. García-Muñoz, S.D. Stamatis, Flexibility index of black-box models with parameter uncertainty through derivative-free optimization, AIChE J. 67(5) (2021) 17189.
[87] C.L. Zheng, F. Zhao, L.Y. Zhu, X. Chen, Flexibility index and design of chemical systems by cylindrical algebraic decomposition, Comput. Chem. Eng. 144(2021) 107142.
[88] L.X. Kang, Y.Z. Liu, A three-step method to improve the flexibility of multiperiod heat exchanger networks, Process. Integr. Optim. Sustain. 2(3) (2018) 169–181.
[89] D.F. Marselle, M. Morari, D.F. Rudd, Design of resilient processing plants—II Design and control of energy management systems, Chem. Eng. Sci. 37(2) (1982) 259–270.
[90] C.A. Floudas, I.E. Grossmann, Synthesis of flexible heat exchanger networks with uncertain flowrates and temperatures, Comput. Chem. Eng. 11(4) (1987) 319–336.
[91] J.L. Li, J. Du, Z.C. Zhao, P.J. Yao, Efficient method for flexibility analysis of largescale nonconvex heat exchanger networks, Ind. Eng. Chem. Res. 54(43) (2015) 10757–10767.
[92] B.Z. Chen, A.W. Westerberg, Structural flexibility for heat integrated distillation columns—I. Analysis, Chem. Eng. Sci. 41(2) (1986) 355–363.
[93] A.W. Westerberg, B.Z. Chen, Structural flexibility for heat integrated distillation columns—II. Synthesis, Chem. Eng. Sci. 41(2) (1986) 365–377.
[94] R.M. Wagler, P.L. Douglas, A method for the design of flexible distillation sequence, Can. J. Chem. Eng. 66(4) (1988) 579–590.
[95] D.C.H. Chien, P.L. Douglas, A. Penlidis, A method for flexibility analysis of continuous processing plants, Can. J. Chem. Eng. 69(1) (1991) 58–66.
[96] S. Diaz, E.A. Brignole, A. Bandoni, Flexibility study on a dual mode natural gas plant in operation, Chem. Eng. Commun. 189(5) (2002) 623–641.
[97] E.E. Tarifa, S. Franco, D. Humana, S. Mussati, Flexibility study for an MSF desalination plant, Desalination Water Treat. 10(1–3) (2009) 229–237.
[98] M.J. Mohideen, J.D. Perkins, E.N. Pistikopoulos, Robust stability considerations in optimal design of dynamic systems under uncertainty, J. Process. Control. 7(5) (1997) 371–385.
[99] A.R. Bogdan, S.L. Poe, D.C. Kubis, S.J. Broadwater, D.T. McQuade, The continuous-flow synthesis of Ibuprofen, Angew. Chem. Int. Ed. Engl. 48(45) (2009) 8547–8550.
[100] H.G. Jolliffe, D.I. Gerogiorgis, Plantwide design and economic evaluation of two Continuous Pharmaceutical Manufacturing (CPM) cases: Ibuprofen and artemisinin, Comput. Chem. Eng. 91(2016) 269–288.
[101] W.H. Yang, H.Y. Yin, Z.H. Yuan, B.Z. Chen, Flexibility analysis for continuous ibuprofen manufacturing processes, Chin. J. Chem. Eng. (2021) (in press).
[102] I. Banerjee, M.G. Ierapetritou, Design optimization under parameter uncertainty for general black-box models, Ind. Eng. Chem. Res. 41(26) (2002) 6687–6697.
[103] F. Boukouvala, M.G. Ierapetritou, Surrogate-based optimization of expensive flowsheet modeling for continuous pharmaceutical manufacturing, J. Pharm. Innov. 8(2) (2013) 131–145.
[104] Z.L. Wang, M. Ierapetritou, A novel feasibility analysis method for black-box processes using a radial basis function adaptive sampling approach, AIChE J. 63(2) (2017) 532–550.
[105] F. Boukouvala, F.J. Muzzio, M.G. Ierapetritou, Methods and tools for design space identification in pharmaceutical development. Comprehensive Quality by Design for Pharmaceutical Product Development and Manufacture, John Wiley & Sons Inc, Hoboken, NJ, USA, 2017, pp. 95–123.
[106] J. Markarian, Advanced manufacturing technologies shift outside the box, Pharm. Technol. 45(4) (2021) 16–19.
[107] S. Mascia, P.L. Heider, H.T. Zhang, R. Lakerveld, B. Benyahia, P.I. Barton, R.D. Braatz, C.L. Cooney, J.M.B. Evans, T.F. Jamison, K.F. Jensen, A.S. Myerson, B.L. Trout, End-to-end continuous manufacturing of pharmaceuticals: integrated synthesis, purification, and final dosage formation, Angew. Chem. Int. Ed. 52(47) (2013) 12359–12363.
[108] Q. Zhang, W. Feng, A unified framework for adjustable robust optimization with endogenous uncertainty, AIChE J. 66(12) (2020) e17047.
[109] C.Q. Ge, Z.H. Yuan, Production scheduling for the reconfigurable modular pharmaceutical manufacturing processes, Comput. Chem. Eng. 151(2021) 107346.
[110] A.C. Bédard, A. Adamo, K.C. Aroh, M.G. Russell, A.A. Bedermann, J. Torosian, B. Yue, K.F. Jensen, T.F. Jamison, Reconfigurable system for automated optimization of diverse chemical reactions, Science 361(6408) (2018) 1220–1225.