June 18, 2024

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ATMP: A new challenge for pharmaceutical production and distribution

ATMP will be a new challenge for pharmaceutical production and distribution


ATMP: A new challenge for pharmaceutical production and distribution.  The complexity of pharmaceutical production and distribution largely depends on the nature of the product.

ATMP: A new challenge for pharmaceutical production and distribution
Figure 1 illustrates two different drug classes. Therapeutic drugs can be divided into two categories: (a) small molecules, (b) biological agents. The former refers to chemically synthesized drugs, while the latter refers to products involving components extracted or produced from living organisms [1]. Biological agents include monoclonal antibodies (mAb), vaccines, blood products and advanced therapeutic drugs (ATMP). The complexity of pharmaceutical production and distribution largely depends on the nature of the product.

The production process of ATMP is significantly different from small molecules or mAbs because it involves a series of product-specific steps and usually patient-specific steps [4]. Their patient-specific characteristics may challenge the state of scale expansion and distribution, and lead to changes in the status quo of manufacturing and supply chains, thus highlighting the need for smaller, more agile, and often regional manufacturing units that can be transformed into more Distributed network close to patients. In addition, such products also need to meet strict release schedules and strict storage restrictions. As a result, there are issues related to the optimal number and location of facilities, and how to design a reliable investment plan model. In addition, as supply chains become more complex, network and task coordination become critical.



Engineering challenges and opportunities in the pharmaceutical production and supply chain

ATMP: A new challenge for pharmaceutical production and distribution


1. Manufacturing of medicines

Unlike all other categories, ATMP, such as chimeric antigen receptor T (CAR-T) cells, usually involves one or more patient-specific steps [9]. Autologous CAR-T cells are a typical example because their manufacture is based on T cells extracted from the bloodstream of patients [10,11].

Pharmaceutical manufacturers are committed to providing effective and safe products that meet global needs. In addition, process and product standardization are the main goals to ensure that batch-to-batch variation is minimized. At the same time, the production process needs to be economically feasible, which increases the complexity of determining the best candidate design. These are usually conflicting goals (see Table 1), and systematic procedures are required to determine the most suitable operating units and modes. These operating units and modes must meet product specifications and at the same time generate considerable profits. In efforts to improve processes and modernize, the pharmaceutical industry is at the forefront by creating new and/or adapting existing innovations.

(1) Quality comes from design

Quality by Design (QbD) was first discussed by Juran [12] in 1992 and refers to the integration of quality into processes and products. In other words, all design and operational decisions are aimed at meeting the pre-defined product quality. QbD recommends to first determine the quality target product profile (QTTP), and then determine the key quality attributes (CQA) [16,17]. CQA is defined as product attributes and/or characteristics that need to be within certain limits. The process is then designed to meet the pre-defined QTTP while keeping the CQA within the allowed threshold. This is achieved by manipulating those process parameters (called critical process parameters (CPP)) that directly affect CQA performance.
Although QbD has been widely used in mAbs and vaccines, the process of QbD driving is still an open challenge when it comes to ATMP [18]. The starting material usually has the special characteristics of the patient/donor, so systematic CQA identification cannot be carried out. In addition, the manufacturing performance of cell-based therapies is highly dependent on the quality of the extracted cells, thus leading to highly variable CPP-CQA interactions. With the maturity of ATMP manufacturing and a greater understanding of the optimal combination of conditions, the QbD principle can be adapted to incorporate patient files and incoming materials into key CPPs and map their impact on process and product performance.

(2) Continuous manufacturing of CM

CM is one of the most discussed trends and innovations in the pharmaceutical industry in recent years, and has been recognized by regulatory agencies [21]. A promising eco-efficient process for increasing productivity, CM has been successfully applied to many existing production processes, resulting in significant improvements [19].
As products become more specialized, so do manufacturing challenges. For example, CAR-T cells (ATMP) are manufactured using a closed production platform, which does not allow task parallelization or scaling up [35,36]. This translates into a comprehensive production line of unit operations to be occupied during the entire manufacturing process (> 10 days) of a therapy before the next therapy can be accepted. With the development of ATMP, manufacturers will need to increase production capacity. Given that it is impossible to scale up, other possibilities can be explored, such as scale-out, which refers to multiple kits running in parallel or a fully granular manufacturing process, where each step is performed in a separate unit, so it can be sequential Manufacture to reduce waiting time.


2. Supply chain

(1) Demand table

The pharmaceutical industry is global in nature, and its supply chain includes a network of manufacturers (primary and secondary), which includes internal or external contractors, packaging facilities, regional distribution centers (wholesalers), and ultimately healthcare providers, such as Hospitals and hospital pharmacies. Ready-made products, prescription drugs and vaccines can be produced on a large scale, and a “one size fits all” distribution method can be used to provide a large number of patient-unspecific doses of products from a single manufacturing batch.
As far as ATMP is concerned, there are two channels for distribution: allogeneic and autologous. In contrast, autologous ATMPs have been clinically more successful so far [9] and have the potential to reconfigure the standard supply chain structure because they represent a turning point in the feasibility of personalized medicine.

ATMP: A new challenge for pharmaceutical production and distribution
Figure 2 illustrates the general supply chain structure of mass-produced drugs and patient-specific therapeutics. In the case of CAR-T cell therapy, cell samples are taken from the patient, transported, modified and administered to the patient with the shortest cycle time (the return time of leading commercial products is 17-19 days) [39– 42 ]. The supply chain of these therapies is closer to customers, and there is a demand for a 1:1 business model, in which a single batch of products released is targeted at a specific patient. Opportunities for scaling up are limited, and the decentralization of manufacturing is a promising method [43].


(2) New players

The pharmaceutical ecosystem includes large R&D multinational companies, local companies, generic drugs, contract development and manufacturing organizations (contract manufacturing organizations, CMOs, and contract and development manufacturing organizations, CDMO), and biotechnology companies [45]. Large-scale R&D multinational companies are key players in the market and have operations in branded products and manufacturing plants in many places. In recent years, their research focus has shifted to the unmet needs of smaller patient groups, such as the prevention and treatment of rare diseases [46].

In this case, the complexity of new targeted therapies continues to increase, and large multinational companies lack in-house manufacturing expertise, which determines the increase in mergers and acquisitions (M&A) and outsourcing strategies through CMO or CDMO [46]. For example, CellforCure was acquired by Novartis, which expanded the company’s manufacturing capabilities in CAR-T cell therapy, Hitachi acquired Aptech to increase its manufacturing capabilities in Europe, and Thermo Fisher CMO Brammer Bio was acquired for US$1.7 billion, and GE Healthcare was acquired by Danaher (US$21.4 billion) [43].

As the number of stakeholders involved in clinical and commercial supply chains increases, end-to-end monitoring of CQA becomes more and more difficult [47]. Outsourcing and processing outsourcing to professional contract logistics providers is an attractive option to ensure the safe and reliable delivery of complex biological drugs. However, management and coordination among multiple agents has become a key challenge.

(3) Matters needing attention in logistics

The manufacturer specifies the stability condition of the product on the product label, which must be maintained throughout the supply chain. Small molecule drug products can usually be stored at 25°C [43]. In contrast, temperature drift and shock can seriously damage the stability of biological products. For example, CAR-T can be stored and transported fresh (-80°C) or frozen (-180°C), depending on manufacturing practices, and pointed out that since they are based on cells, they are naturally very sensitive to shear stress and vibration [9 ].

As the complexity of product structure and scope increases, it is becoming more and more important to monitor CQA related to storage and transportation environmental conditions and ensure timely delivery of treatments. Whether it is an internal solution or an outsourcing solution, the transparency of manufacturing and logistics operations contributes to the quality assurance and effectiveness of the entire supply chain [47].

(4) End-to-end monitoring

CAR-T and personalized therapy provide a new perspective on the importance of tracking and tracking functions to supply chain management and real-time monitoring. In these supply chains, the chain of identity (COI) and tracking are critical to ensure that treatment is returned to the appropriate patient before the end of the product cycle [9]. In addition, the chain of custody (COC) principle must be adopted, the purpose of which is to record data related to the processing, collection, and execution of samples in order to closely monitor patient-specific product profiles.

It is worth noting that the potential success of the off-the-shelf ATMP will also require tracking donor information throughout the supply chain to ensure compatibility and help effective donor-patient matching. After receiving treatment, patients need to be monitored for several years; this information should be used as much as possible to improve treatment design. There are also plans to improve the end-to-end visibility of the supply chain in conventional non-specific product areas. For example, Merck KGaA is committed to using data analysis to predict and prevent drug shortages [50]. In fact, companies are increasingly aware of the improvement in supply and demand forecasts provided by traceability, including its potential to prevent insufficient inventory of raw materials and counterfeit drugs from entering the supply chain.

As Papathanasiou [51] emphasized, cloud-based platforms can facilitate communication and seamless connections between stakeholders. In addition to cloud-based solutions, alternatives based on blockchain are also being developed in recent years. In short, blockchain is part of the broader distributed ledger technology (DLT) category, which is based on the participation of a network of devices called nodes, which keeps a copy of the database [53]. A significant advantage of the blockchain is that it does not require a central trusted party to verify the validity of the data, but instead relies on a consensus agreement that all participants are publicly available and reach a consensus [54].

Despite the huge potential, the scalability of blockchain applications is still an issue, yet to be proven. An interesting use case is the recent collaboration between NHSEngland and Hedera Hashgraph, a company that provides blockchain-based solutions, with the goal of using blockchain to enable cold chain monitoring of COVID-19 vaccines for a selected set of facilities [56]. Modum.io [57] is developing other examples of blockchain-based tools for real-time monitoring of the storage status and traceability solutions of sensitive goods, and is investigating a leading company in the field of ophthalmology in Italy [53].

(5) Production plan and plan

Although digitization and advanced surveillance have brought exciting opportunities, mature technologies still show a lot of room for improvement in the adaptability of production levels to demand. For small molecules and conventional biological agents, one of the main bottlenecks in the current manufacturing and distribution network is production planning and scheduling in response to short-term demand fluctuations [45]. The main manufacturing site usually includes a multi-purpose batch processing facility set up to allocate capital costs to a range of products. In the case of biopharmaceutical production, such as the production of monoclonal antibodies, because the fermentation titer is increased, the perfusion and fed-batch modes are the preferred operating modes [58].

The downtime caused by the conversion and the need to do a lot of cleaning to prevent contamination can result in a significant loss of revenue. This forces manufacturers to operate the site during long-term product activities, thereby ensuring profitable utilization of the factory throughout the time frame [45,59]. The small-molecule drug substance that leaves the main site can be stored for up to 1 year, and can be further processed at the secondary manufacturing site as needed. The filling and finishing and packaging tasks completed in this second phase are simpler, so you can more flexibly schedule the work time and supply the products to the distribution center.

Off-the-shelf production has followed the above planning paradigm for many years, but patient-specific treatments have gradually changed this approach. The planned production becomes a patient plan, where each batch contains only patient-specific therapeutic doses [9]. The business model has radically changed, and adapting to demand dynamics has become more and more important, as operations are now limited by the return time between sample collection, manufacturing, product release and reinjection at the beginning of the supply chain.

(6) Capacity and investment plan

To avoid financial losses related to poor forecasts and poor use of facilities, R&D companies are outsourcing the externalization of novel items in the development and production portfolio to contractors. The issue of capacity management has been outsourced to the CMO, who can better balance utilization by producing products for multiple innovators [43].

As biopharmaceutical products become more advanced and complex, the operational burden of cleaning tasks, pollution issues, and the constant demand for more flexible production are prompting many companies to use disposable production technologies. This manufacturing trend has multiple advantages in terms of saving installation costs, and the cost savings are in the range of 2 to 100 million U.S. dollars (2% to 20% of capital investment). The establishment of the new facility is shorter (1.5 years), and the advantage of parallelizing production and kits is retained to cope with short-term changes in demand. Interestingly, COVID-19 vaccine manufacturers chose to rely on flexible single-use systems instead of traditional commercial large-scale bioreactors and fermenters, thus assessing the potential of installing production capacity at a higher speed, which is healthy globally It is crucial during the crisis [63].

The advantages of disposable devices are also reflected in the field of personalized medicines. Among these products, the risk of cross-contamination will lead to a decrease in patient specificity and adversely affect the health of patients. Since it is no longer necessary to clean the equipment components, but discard them and replace them, the replacement time of equipment components is reduced from 1 month to 0.5 days [61], and it has the ability to adapt to the incoming patient schedule.

However, the disposal method of disposable technology is still an issue that needs to be considered. Used components are often biohazardous, which means that waste disposal tasks must be performed on-site before disposal in a landfill. Another option is to send the used components to a geographically separated waste-to-energy facility for incineration and recovery of electricity [64].



2. Through Process System Engineering (PSE)

Assist the digitization of the pharmaceutical industry

Traditionally, Process Systems Engineering (PSE) has been assisting decision-making in the pharmaceutical industry [46,65-68]. The adoption of digitization in the pharmaceutical production and supply chain will be the key to seamless data exchange across manufacturing facilities and supply chain networks, as it will allow connections between processes, products and people.

Figure 3 summarizes the main considerations and challenges currently facing the pharmaceutical industry, as well as some of the most outstanding calculations and other innovations that help decision-making.


In the pharmaceutical industry, changes to approved processes and/or products need to be re-registered by the regulatory agency. This poses additional challenges for adapting to new methods and technologies. Through quality measures such as design and design space identification, a thorough understanding of the process and product can be achieved, which can make the process more flexible and speed up the approval process.
In this regard, computer-based modeling plans and tools have great potential because they provide a low-cost experimental platform and have the ability to identify optimal process operation profiles offline. Computer-based product development and manufacturing modeling has great potential. It provides a low-cost experimental platform that can evaluate the CQA-CPP interaction under various conditions [71-73].

PSE researchers also seek to quantify parameter uncertainties and their effects on product and process performance in a similar way [74,75]. From an operational point of view, many groups are using digital twin technology to design optimal operating settings, optimized configuration files [76-79], and smart controllers that can operate without measurement unavailability [80-82].

In the field of supply chain management, optimization-based methods have improved the pharmaceutical and biopharmaceutical processes, as well as the strategies and operations of distribution in a variety of ways. Considering the problem of supply chain design and capacity planning, as well as mid- and short-term decision-making, a calculation tool was developed to find the best long-term strategic plan to solve production planning and planning problems [69]. Supply chain design, capacity and investment optimization models focus on the strategic location of factories, storage and procurement of raw materials, contracts with CMOs and CDMOs and logistics providers, and long-term decisions regarding future investment in new capacity [58,62,83 -87].

Tools for optimizing production planning and scheduling have great potential in assisting daily operational decisions. The systematic approach in production planning can estimate production targets, inventory levels and material flows in the entire supply chain within a few months [59,60,88]. Instead, scheduling tools rely on a more detailed description of the manufacturing and distribution process, and take into account resource constraints, thereby providing detailed tasks and operating sequences, fulfilling orders and achieving production goals [89,90].

Integrating different levels of decision-making on many time scales is a problem worthy of study [91,92], and it also involves coordination between multiple geographically distributed manufacturing and storage facilities, including the supply chain. The size of the optimization problem becomes difficult to solve with commercially available solvers, and many methods have been proposed in the literature, including rolling range, space [88] and time decomposition [88,89] schemes. Solving the above problems under uncertain circumstances is still an open challenge [93]. Fluctuations in demand, continuous global competition and the uncertainty of pending clinical trial results pose challenges for long-term strategic decision-making.


Therefore, the novelty of patient-oriented products and ATMP provides fertile ground for PSE tools that can support investment planning and establish a successful supply chain that can respond to the expected demand for these products. Similarly, planning and planning tools can aid decision-making and address operational challenges posed by patient-specific and treatment cycle time constraints [96,97].





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