**1. Introduction**

Complexity in pharmaceutical manufacturing and distribution is highly dependent on the product nature. Therapeutic drugs can be classified into two broad categories: (a) small molecules, (b) biologics. The former refers to chemically synthesised drugs, while the latter refers to products that involve components extracted from or produced by a living organism [1]. Biologics include monoclonal antibodies (mAbs), vaccines, blood products, and advanced therapy medicinal products (ATMPs). Figure 1 illustrates the drug categories considered here. Each of these products is characterised by key specifications and/or formulation that dominate decisions related to its manufacturing and supply chain. Small molecules are pharmaceuticals based on chemical components and characterised by large scale manufacturing. On the other hand, manufacturing of biologics involves cellbased production systems and complex downstream separation trains, largely performed in batch/semi-batch mode [2,3]. This often presents challenges in the optimisation and scale up of unit operations.

Enhanced clinical disease understanding has led the pharmaceutical industry to move from one-size-fits-all approaches and develop targeted therapeutics such as ATMPs. Their production process differs significantly from small molecules or mAbs as it involves a series of product- and often patient-specific steps [4]. Their patient-specific nature may challenge scale up and distribution and has led to a shift in the manufacturing and supply chain status quo, highlighting the need for smaller, more agile, and often regional manufacturing units that translate into distributed networks closer to the patient. In addition, such products are coupled with stringent distribution timelines and tight storage constraints that need to be satisfied. As a result, questions related to optimal number and location of facilities arise, as well as how can one design a robust investment planning model. Furthermore, network and task coordination become of primary importance as the supply

**Citation:** Sarkis, M.; Bernardi, A.; Shah, N.; Papathanasiou, M.M. Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution. *Processes* **2021**, *9*, 457. https:// doi.org/10.3390/pr9030457

Academic Editors: Luis Puigjaner and Bhavik Bakshi

Received: 11 January 2021 Accepted: 25 February 2021 Published: 3 March 2021

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chain becomes more complex. Once the network has been designed, manufacturers need to ensure that distribution and storage conditions are met and maintained throughout the product journey, in order to reduce losses due to product degradation that can lead to drug shortages or reduced quality.

**Figure 1.** Schematic of simplified pharmaceutical product categories.

In this paper, we discuss how the nature of therapeutics may impact the design of suitable manufacturing processes and supply chain networks. We have performed a literature review and we summarise some of the latest initiatives taken to assist the decision-making process in the pharmaceutical industry. We also discuss how process systems engineering has been aiding innovation in this space. In the last part of this paper, we present a perspective on current and future developments in this space.

#### **2. Engineering Challenges and Opportunities in Pharmaceutical Manufacturing and Supply Chain**

Recently, the term Pharma 4.0 has been introduced, referring to the adaptation of digital strategies and tools of Industry 4.0 principles, and their application to pharmaceutical manufacturing and supply chain practices [5,6]. In this context, digital tools and orchestration platforms are being developed under Industry 4.0/5.0 principles [7]. The term refers to manufacturing digitalisation and automation of processes, introducing autonomous, computerised systems. It utilises different types of mathematical models (e.g., statistical, kinetic) and Internet of Things to facilitate and maintain internal communication within and across the factories. Application of Industry 4.0/5.0 principles aims to facilitate: (a) data collection, analysis, and interpretation, (b) man-machine co-operation, (c) online monitoring and control, and (d) intra- and inter-facility data sharing. In the last few years, we have seen the emergence of cloud-based applications coming to assist decision-making in the pharmaceutical industry. Several industrial players have embraced Pharma 4.0 either through the development of digital platforms to be used by manufacturers (e.g., Siemens) or by integrating digitalisation into their manufacturing processes (e.g., ChemeCon GmbH) [8].
