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“Process Systems Engineering for Pharmaceutical Manufacturing” https://doi.org/10.1595/205651319X15680343765046 Johnson Matthey Technol. Rev., 2019, 63, (4), 292–298 www.technology.matthey.com “Process Systems Engineering for Pharmaceutical Manufacturing” Edited by Ravendra Singh (Rutgers, The State University of New Jersey, USA) and Zhinhong Yuan (Tsinghua University, Beijing, China), Computer Aided Chemical Engineering, Volume 41, Elsevier, Amsterdam, The Netherlands, 2018, 674 pages, ISBN: 978-0-444-63963-9, US$187.50, £150.00, €184.57 Reviewed by Michael D. Hamlin development, covering solubility and dissolution Johnson Matthey, 25 Patton Rd, Devens, kinetics, pKa, excipient types and the standard MA 01434, USA formulation processes of direct compression as well as wet and dry granulation and capsule filling. Email: [email protected] This chapter is recommended reading for anyone not familiar with formulation of drug tablets as Introduction it provides a well-organised summary helpful in understanding the types of processes modelled “Process Systems Engineering for Pharmaceutical in the chapters on continuous manufacturing, Manufacturing” is an ambitious reference flowsheet and unit operation modelling as it relates comprising 24 chapters covering process systems to drug product. engineering (PSE) methods and case studies of I have organised this review according to general interest to engineers working in pharmaceutical topics covered rather than by sequential order of process development, model development, process the chapters. simulation, process optimisation and supply- chain or enterprise optimisation. Business model Business Model and Optimisation optimisation, including optimisation of clinical trials and supply chain, are topics covered in Chapter 1, ‘New Product Development and Supply Chapters 1 and 21–24. Continuous manufacturing Chains in the Pharmaceutical Industry’, contributed of drug product (downstream) is a key theme by Catherine Azzaro-Pantel (Université de covered in Chapters 6 and 16–20, while process Toulouse, France), introduces the pharmaceutical control, flowsheet modelling and key unit operation supply chain and summarises the product life modelling are covered in Chapters 5, 7, 8–11 and cycle of a drug starting from discovery through 13–15. Of particular interest is the topic of small clinical trials, registration and commercialisation. molecule upstream development and workup solvent This chapter provides a concise summary of clinal selection and optimisation discussed in Chapters trial phases, pre-launch and launch activities and 3–4, with case studies involving separation solvent is recommended reading for those not familiar selection presented for ibuprofen, artemisinin and with the pharmaceutical business model and drug diphenhydramine in Chapter 4. development process (Figure 1). Chapter 2, ‘The Development of a Pharmaceutical Chapter 21, contributed by Brianna Christian and Oral Solid Dosage Forms’ submitted by Rahamatullah Selen Cremaschi (Auburn University, USA), covers Shaikh, Dónal P. O’Brien, Denise M. Croker and ‘Planning of Pharmaceutical Clinical Trials Under Gavin M. Walker (University of Limerick, Ireland), Outcome Uncertainty’. The authors reference provides a summary of solid oral dosage form an increase in attrition rates in clinical trials and 292 © 2019 Johnson Matthey https://doi.org/10.1595/205651319X15680343765046 Johnson Matthey Technol. Rev., 2019, 63, (4) Exploratory Preclinical Preclinical trials: Registration Commercialisation research trials Phases I, II and III 10,000 targeted 100 tested 10 drug candidates 1 drug molecules molecules 5 years 10 R&D years 20 years Patent Patent deposit expiration Fig. 1. Drug development process. Copyright (2018). Reprinted with permission from Elsevier state “the time from discovery to product launch complex network. A takeaway from this chapter of a drug is around 10–15 years with an average is that pharmaceutical companies can anticipate research and development (R&D) cost of about improved access to software tools to compare the $2.6 billion per drug” as motivating factors driving impact of supply chain alternatives as research the need for better clinical trial optimisation. This is translated into commercial software offerings. chapter provides details of a “perfect information” deterministic mixed-integer linear programming model (MILP) problem including constraints. By Process Analytical Technology using an innovative heuristic modification to the stochastic programming model a five order of Chapter 12, ‘PAT for Pharmaceutical Manufacturing magnitude improvement is reported. Process Involving Solid Dosages Forms’ Chapter 22, ‘Integrated Production Planning contributed by Andrés D. Román-Ospino and and Inventory Management in a Multinational Ravendra Singh (Rutgers, The State University Pharmaceutical Supply Chain’ contributed by of New Jersey, USA), Vanessa Cárdenas and Naresh Susarla and Iftekhar A. Karimi (National Carlos Ortega-Zuñiga (University of Puerto Rico, University of Singapore) presents a MILP model USA), presents near-infrared (NIR) calibration for a complex supply chain and provides a models and chemometrics. For those not skilled in strategy to optimise inventory, resources and process analytical technology (PAT) and analytical production schedules in the supply chain to determination, this chapter is very informative maximise profit. The intent of the model is and provides comparison of various methods for as a tool for decision making for “production analytical data fitting to determine blend uniformity planning and scenario analysis in a multinational for real-time control of continuous pharmaceutical pharmaceutical enterprise”. To mitigate risk processes. Principal component analysis (PCA), associated with the complex, multinational partial least squares (PLS) and multivariate curve network of supply, drug inventories of 180 resolution alternating least squares (MCR-ALS) days are not atypical. However, high levels of are presented as suitable techniques for multiple inventory come at a cost. A change introduced parameter determination where linear regression in the supply network may have impact on or classical least squares methods are not inventories, lead-times and dependencies suitable. Layering of talc and lactose as a specific as impacted by other portions of the supply case study in non-homogeneity is discussed in network. In this chapter the authors describe this chapter. Finally, a process example utilising their approach to this optimisation problem. Unscrambler® X Process Pulse II (Camo Analytics While looking at the authors’ formulation of their AS, Norway) and NIR (Viavi Solutions Inc, USA) case study problem, the value of working with is presented where Unscrambler® X software is fewer strategic suppliers in a vertically integrated utilised to generate and upload a calibration model supply network is evident in that it will minimise generated via methods presented in the chapter. the complexity, delay and cost associated with a In the example the NIR data processing system is 293 © 2019 Johnson Matthey https://doi.org/10.1595/205651319X15680343765046 Johnson Matthey Technol. Rev., 2019, 63, (4) interfaced to a DeltaVTM distributed control system this method is useful for process development. (Emerson Electric Co, USA) to provide real time An interesting adaptation of the ADNC method process control of a tableting process. to a two-stage continuous mixed-suspension Chapter 19, ‘Monitoring and Control of a mixed-product removal (MSMPR) crystalliser Continuous Tumble Mixer’ contributed by Carlos system is an innovation by Yang et al. (1) where Velázquez, Miguel Florían and Leonel Quiñones, heating and cooling is performed on the jacket of a (University of Puerto Rico, USA), presents a case wet mill while the MSMPR crystalliser is maintained study for the mixing of naproxen sodium with at constant temperature. The MSMPR with wet mill excipient using a continuous mixer designed by achieves both form control and FBRM particle count Velázquez. The PAT technology implemented for this control under continuous flow operation. case study employed the use of NIR in conjunction ® with Unscrambler X in a PAT implementation Continuous Drug Product similar to that described in Chapter 12. The closed- Manufacturing (Downstream) loop control dynamics for the experimental mixer are evaluated. A finding from the study is that a Chapter 5, ‘Flowsheet Modeling of a Continuous different control scheme is required for very low Direct Compression Process’ contributed by dosage active pharmaceutical ingredient (API) vs. Seongkyu Yoon, Shaun Galbraith, Bumjoon Cha higher dosages. The authors identified flowrate and Huolong Liu (The University of Massachusetts control of API addition at very low dosage as Lowell, USA), summarises the scope of individual variable due to poor powder flow properties as well unit operation models for continuous powder as limitations of the NIR methods employed in low blending, powder feeding (and potency control), dosage applications. tablet press, feed frame and tablet compaction. Chapter 9, ‘Crystallization Process Monitoring The authors highlight both a population balance and Control Using Process Analytical Technology’ model (PBM) as well as a stirred-tanks-in-series contributed by Levente L. Simon (Syngenta modelling approach to blending. The value of the Crop Protection AG, Switzerland), Elena Simone modelling is in being able to accurately predict (University of Leeds, UK) and Kaoutar Abbou the response of perturbations on key quality
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