Chronic illnesses or non-communicable diseases that affect the health of the global population are on the rise and, in turn, attributing to a large proportion of deaths and a higher economic burden year-on-year (1). To help combat these long-term illnesses, the bio/pharmaceutical industry has been investing in the development of novel therapies that are increasingly complex in nature.

“The complexity of drugs and their delivery has been increasing over the past few decades,” explains Peter Droc, vice president, head of Drug Product Services, Lonza. “Combined with a growing prevalence of chronic illnesses, this market evolution is putting more pressure on pharmaceutical manufacturers to develop novel therapies that might also have unique formulation needs.”

Many of these novel, complex therapies are biologic-based drugs that are delivered parenterally. “The injectable drug market is experiencing significant growth,” adds Gareth Jenkins, vice president, Science and Technology, Candidate Development, Quotient Sciences. “As a result, robust and efficient sterile manufacturing lines are essential across the manufacturing scales from the early phase to the commercial launch.”

“In its very nature, the aseptic processing market is bound to be less efficient than other market sectors,” remarks Nate Smart, process engineer, CRB Group. “[The] focus is delivering critical therapies to vulnerable patient populations in methods that bypass many of the body’s natural defense systems. Therefore, in contrast to other drug product markets (i.e., OSD [oral solid dosage]), the greatest care must be taken to ensure product quality is maintained.”

However, attaining high quality in aseptic processing is a time-consuming endeavor, as manufacturers need to pay close and accurate attention to adherence to strict guidelines, confirms Maximilian Kappler, process engineer, CRB Group. “The highest quality is imperative in aseptic processing to ensure product safety and effectiveness, making it non-negotiable to invest time for quality whether in design, processing, and product testing,” he states.

Regulatory authorities are scrupulous of all aseptic processing facilities and hold manufacturers to stringent standards, agrees Smart. “As a result, aseptic fill lines and their associated barrier systems are custom and costly,” he says. “In many facilities the aseptic filling equipment is the most expensive and longest lead equipment in the facility.”

As a result of these overheads, many manufacturers try to make their lines flexible so that the utility of their equipment can be maximized and new products, formulations, or formats can be added, Smart specifies. “The more products and formats you can run on a single line, the greater utilization and return on investment you can get out of your line,” he says.

“Despite these efforts, fill lines have notoriously low OEE [overall equipment efficiencies],” asserts Smart. “Many lines, even recent installations, have turnaround times of up to 24 hours or beyond. Any reusable critical contact parts (direct and indirect) must be washed and sterilized out of place and then installed in an aseptic manner.”

“The regulatory bodies are currently pushing for a continued reduced risk of contamination,” adds David King, senior director of Aseptic Processing at Samsung Biologics. “This push is focused on the removal of humans from the aseptic filling process, as humans are the primary source (directly and indirectly) of aseptic area microbial intrusions. The primary change is an industry-wide transition from open RABS [restricted access barrier system] filling systems to isolator contained filling systems.”

“The distinct advantage is that the environment around the open packaging container is sterilized (typically with vaporized hydrogen peroxide [VHP]) with the use of isolator systems,” King specifies. “Isolators cause a bottleneck in regards to small batches as the [process changeover times] can be complex with the requirement to reduce the risk of product contamination from hydrogen peroxide.”

“Ensuring sterility through the manufacturing process is critical and can lead to bottlenecks both for product release and during product changeovers or when there is a temporary issue on the line that is holding up production,” confirms Jenkins. A microbiology team can play a crucial role in helping to minimize such disruptions, he explains, as microbiology considerations can be incorporated at the process design stage and when optimizing operations.

“Sterility assurance is critical for quality control (QC) release of sterile drug products, and the industry-wide approach involves a two-week incubation period—both for testing the drug product and environmental monitoring of the facility,” Jenkins continues. “Numerous rapid sterility testing methods are now commercially available to help address this and can be applied in later stages of development.”

Additionally, supply chain disruptions, which have impacted many global industries over the past few years, can be challenging for aseptic processing, asserts Aimee Hodge, vice-president Business Operations, PCI Pharma Services. “Lengthy lead times for components and drug substance can be very challenging, especially for time critical projects,” she says.

“Delays or disruptions in the procurement of essential packaging materials can significantly impact production timelines and quality assurance efforts in aseptic processing,” states Kappler. “Addressing these supply chain challenges early in a project is crucial to maintaining the integrity and efficiency of the aseptic processing workflow.”

Improving the efficiency of the aseptic workflow is key to ensure critical therapies reach patients in a timely fashion while also being safe and effective. “Automating processes and bringing robotics into aseptic processing, together with single-use systems, [are] helping to streamline processes, minimizing human intervention and reducing the risk of errors or contamination,” emphasizes Hodge.

“Innovations in analytical testing such as rapid microbial and particle detection and rapid sterility testing can save valuable time for releasing drug product to clinical trials or commercial supply,” Hodge adds. “For example, with rapid sterility testing sample results are available in less than seven days, providing time efficiencies when compared to the 14-day incubation required for compendial sterility.”

However, regulatory requirements for viable particulate monitoring are based upon colony forming units, which “cannot easily be directly correlated with fluorescent particle counting results,” Smart asserts. “Manufacturers must be able to validate new methods against the existing standards to demonstrate the new method’s equivalence or superiority.”

Smart points out that rapid micro methods use biofluorescent particle counters in place of settle plates for viable particulate monitoring. “This technology has enormous potential to benefit manufacturers by providing real-time microbial data during aseptic processing,” he says. “Rather than waiting weeks to find out about EM [environmental monitoring] failures, operations can respond to issues as they occur and limit or avert resulting investigations and batch losses.”

“[Another] advancement that is now being more accepted by the regulatory bodies is the use of rapid microbial monitoring systems, [which not only] monitor particles within the filling environment, but also have the capability to determine if the particle is viable or non-viable,” King adds. “If the particle is viable, it is captured real time on a growth medium. This is reducing environmental monitoring excursion identification time frames.”

The presence of particles, subvisible or visible, in parenteral products causes delays and contributes to medicines shortages worldwide, specifies Belinda Holdsworth, strategic growth project lead, Drug Product Services, Lonza. “Having a robust, fast, and reliable method for visual inspection is therefore of utmost importance to drug developers, as well as to their patients,” she says. “An important trend in this space is the utilization of robotics and automated visual inspection (AVI) for defect and visual particle identification in drug products.”

“[Additionally,] the utilization of AI [artificial intelligence] for data analysis [of] image and pattern recognition significantly enhances the detection of difficult-to-inspect parenteral drug products and decreases false reject rates,” Holdsworth specifies. “Combined with an automated robotics approach, this robust process can eliminate the formation of air bubbles, thus greatly enhancing process timelines.”

Focusing on an engineering perspective, Kappler believes that industry will move toward more standardized processes. “In terms of smaller batches, the industry apparently tends to move toward established and validated components such as ready-to-use/ready-to-fill containers,” he says. “This [approach] allows [the manufacturer to] focus on the product core without investing too much time and effort on side processes.”

It has been a decade since ready-to-use pre-sterilized nests of vials were launched by glass pharmaceutical packaging specialist, Schott, explains Jenkins. “These [nests of vials] were designed in collaboration with filling-line manufacturers to eliminate certain processing steps, such as vial washing, drying, and sterilization at the drug product manufacturing line,” he says.

“The nested packaging also reduced incidents of glass vial damage due to vial-to-vial and vial-to-machine contact,” Jenkins states. “This [innovation] paved the way for advancements in robotics and automation, leading to a range of filling solutions, from small-scale support for early clinical supply to more robust systems capable of filling hundreds of vials per hour.”

Further innovation is being seen in the machine manufacturing space that reduces operator interactions, Kappler continues. “Advancements have been made surrounding environmental monitoring that is causing streamlining of operations of critical monitoring steps that ensure that the product remains aseptic throughout the process,” he confirms.

“Advancements in automation and robotics are revolutionizing aseptic fill/finish processing,” confirms Hodge. “From vial loading to stoppering, advanced robotics are streamlining and enhancing the efficiency of sterile fill/finish operations with reduced human interventions, minimizing contamination risks, while optimizing production speed and time to provide life-changing therapies to patients.”

Although, robotics still have some limitations, particularly in responding to faults, jams, and other unplanned events that are not programmable, Smart stresses. “In these cases, there is future potential for use of vision systems and machine learning/AI to provide robotics the capacity for responding to unplanned interventions without the risks inherent in human operations,” he says. “Manufacturers looking to maximize the benefit of robotics and other automation should seek to understand how to maximize flexibility in how they implement these solutions. A set of robotic tooling that is fit to a single format does not provide significant operational advantages over a set of single size format parts in a traditional line.”

“Time-to-market can mean the difference between having a viable product or the competing product taking the market,” emphasizes King. “The best way to reduce the time[-to-market] is to have all production activities at one site. If a company can produce the drug substance and drug product at the same site, product testing, storage, and release times can be greatly reduced.”

Managing to get a product to commercialization quicker also helps to provide patients with life-changing therapies in a better timeframe and ultimately improves their health outcomes, Hodge adds. “Biopharma companies can endeavor to accelerate the delivery of their drug product to patients by developing well defined processes and testing methods together with a product road map early in the drug development lifecycle to identify the steps to plan for to advance along the journey to commercial readiness and launch,” she says.

“Contract development and manufacturing organizations (CDMOs) also play a crucial role in supporting the accelerated supply of life changing therapies to patients by providing expert solutions for drug development, manufacturing, and clinical trial services,” Hodge specifies. “When partnering with a CDMO, to ensure a robust supply chain and support speed to market, it is vital that a preferred CDMO has global reach together with flexible, scalable solutions to support clinical trial from early phase through to commercialization.”

For Droc, the use of sterile, ready-to-use, and single-use packaging solutions is valuable when trying to increase product quality and patient safety, and also reduces time-to-market. “From the perspective of drug developers, these solutions can also accelerate time to market by streamlining operations and expediting product development,” he says. “For drug product manufacturing, pre-sterilized containers, such as vials, syringes, and cartridges, that are ready for filling are especially relevant.”

“Flexibility will be another key aspect of future time-to-market aspects,” reveals Kappler. “[Because] the variety of single products during clinic is high, systems that allow switching between different packaging materials, and quick change between different product set ups will increase usage and allow pharmaceutical manufacturers to quickly react on formulation in early phases.”

Although the benefits of reducing the time it takes to commercialize products are obvious, there is also a need to balance leveraging the use of innovative technologies with standard “tried-and-true” practices, Smart adds. “No one in pharma wants to jump in at the ‘peak of inflated expectations’ in the Gartner Hype Cycle, whereas waiting too long jeopardizes potential competitive advantages,” he says.

“While in many ways the [aforementioned] technologies are not new to the industry, their adoption still has far to go,” concludes Smart. “Courage is required to innovate, but the potential gains are significant. Given that regulatory agencies are themselves recognizing the benefits of these technologies, it seems that the way is paved for industry to reap the rewards of implementation.”

Hacker, K. The Burden of Chronic Disease. 

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Vol. 48, No. 6
June 2024
Pages: 10–13

When referring to this article, please cite it as Thomas, F. Streamlining Aseptic Processes through Automation. 

Articles

Cover Story

Leveraging automation advancements can help improve efficiency in aseptic processing and speed up commercialization of critical drug products. 

Streamlining Aseptic Processes through Automation 

Stability data of samples of pharmaceuticals are often generated as replicate test results, typically as duplicates. A statistical analysis for determination of an expiration date can then be applied on either the replicates or their corresponding averages in line with the methodology suggested in International Council for Harmonisation (ICH) Q1A(R2) and Q1E guides. This paper aims at clarifying when a shelf-life derived from all replicates or averages is justified and correct. When replicate stability data represent preparations of the same sample, this is a case of pseudoreplication, and, therefore, the statistically derived shelf-life should be based on the averages of the replicates. However, when these replicate data represent independently and randomly selected and tested samples at each time point, a statistically derived shelf-life based on all replicate data is justifiable.

ICH Q1A (R2) and Q1E are often followed in the pharma industry for the evaluation of stability data of drug substances and products and for a statistical extrapolation of a shelf-life of a drug product or a retest period for a drug substance. The length of derived shelf-life or retest period is based heavily on whether data exhibit a change-over-time and/or variability. The outcome of the statistical evaluation depends on the number of the stability data points analyzed. Usually, a new product submission file is expected to include stability data collected during at least the first year (0, 3, 6, 9, and 12-month time intervals) along with a projected shelf-life (or retest period) statistically derived from these five time points. This shelf-life is subsequently updated as more data are generated. Stability samples are usually each tested in several replicates (duplicates or triplicates) while an average result is recorded as a representative test result. For instance, in the case of a solid dosage form such as tablets, not fewer than 20 tablets are randomly selected from the original stability sampling units (e.g., bottle), weighed to determine a tablet average weight, and ground to make a uniform composite from which several portions (typically two) are tested to yield assay results of the mean content of the active ingredient in an average tablet. Thus, the final test results to be subsequently employed for a statistical analysis consist of either these individual replicates or of a single average result of these replicates.

Often, the drug characteristic that is being tested changes linearly over time, and, therefore, a simple linear regression analysis is first performed on the stability data. The shelf-life/retest period is then determined as the time at which the 95% one-sided confidence limit for the mean curve intersects either the lower (e.g., assay of the pharmaceutical active ingredient) or the upper (e.g., impurity content) specification. While the suitability of the linear model is also expected to be evaluated and justified, this paper concentrates solely on how the stability data are used to derive a shelf-life/retest period from a fitted linear model. Should the shelf-life be derived from a linear model fitted to either all individual replicates (duplicates or triplicates) results or to their arithmetic average results?

Submitted: Jan. 1, 2024
Accepted: Feb. 20, 2024

Raphael Bar, PhD, rbar@netvision.net.il, is a pharmaceutical consultant at BR Consulting.

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Vol. 48, No. 6
June 2024
Pages: 24–29

When referring to this article, please cite it has Bar, R. Determination of Shelf-Life from Stability Data: From Replicates or from Averages? 

Peer-Reviewed Research

A statistical analysis for determining an expiration date can be applied to replicates or their corresponding averages as suggested in industry guidelines.

Determination of Shelf-Life from Stability Data: From Replicates or from Averages?

Artificial intelligence (AI) and machine learning (ML) in the biopharmaceutical industry have been widely applied across drug discovery and clinical development efforts. These technologies also have potential to impact many other aspects of drug development and manufacturing. Their use in formulation development has been growing in recent years due to the potential for AI/ML to streamline and accelerate this process, particularly for challenging drug substances such as those that suffer from poor solubility and bioavailability (1).

The traditional approach to formulation development involves extensive, time-consuming, and costly physical experimentation and screening, both in vitro and in vivo, to identify optimal formulations. Leveraging AI/ML algorithms allows for identification of formulations with the greatest likelihood of success, reducing the time and resources needed for physical evaluation. These technologies can also uncover new materials with attractive excipient properties and new formulation approaches not previously considered (2).

One example of an AI-based prediction tool designed specifically to aid formulation design is the freely available web-based platform, FormulationAI (3).

Formulations play a critical role in stabilizing APIs, enabling patient administration, and potentially mitigating toxic side effects while enhancing drug efficacy. “Regrettably,” observes Christine Allen, a professor within the Leslie Dan Faculty of Pharmacy at the University of Toronto and CEO of Intrepid Labs, a biotech start-up that utilizes AI/ML and robotics to accelerate formulation development, “the significant potential of formulations is often underestimated and, consequently, given lower priority in drug development, despite their ability to directly improve safety and efficacy.” She notes that approximately 80% of drugs fail in clinical development due to safety concerns and lack of efficacy, areas where better-formulated drugs might succeed.

Poor solubility/bioavailability present many development challenges

Between 70–90% of new chemical entities (NCEs) have solubility issues, according to Allen. A formulation that excels in enhancing solubility and bioavailability but falls short in safety, efficacy, or patient acceptability does not fulfill its therapeutic potential, adds Sanjay Konagurthu, senior director of science and innovation within Thermo Fisher Scientific’s Pharma Services business.

“One of the greatest challenges, therefore, is for developers to meticulously balance these considerations, creating formulations that not only improve drug delivery but also meet the broader criteria necessary for successful patient outcomes,” Konagurthu contends.

Speed is another ongoing challenge in the journey from molecule to medicine. “While maintaining safety and efficacy, scientists are always looking for a faster way to overcome hurdles like poor solubility and bioavailability and the trial-and-error formulation development process to get therapies into the hands of patients as soon as possible,” explains Konagurthu.

Difficulties arise, Allen adds, because current formulation methods are often slow and resource-intensive, which can hinder the rapid development and optimization of drug formulations that are crucial for overcoming solubility challenges.

In fact, Konagurthu comments, because poor API solubility typically corresponds with lower bioavailability and thus impacts the efficacy of the drug product, it can create a negative ripple effect from discovery to clinical trials. He points to several factors, from molecular properties to the characteristics of the excipients and formulations, as determining the solubility and bioavailability of an API. “For this reason, identification of the most effective combinations of drug and excipients is a complex and resource intensive process that requires rigorous experimentation, data collection and analysis,” he says.

Historically, scientists have looked to resolve poor API solubility through trial-and-error testing, which often results in longer development timelines. “With pharmaceutical companies focused on getting life-saving therapies to patients as quickly as possible, there is an urgent need for streamlined workflows that allow scientists to efficiently find the best way to improve a drug’s bioavailability,” Konagurthu concludes.

Predictive capabilities offer many benefits

Advanced predictive algorithms can help overcome this important challenge. “AI/ML offers low-cost predictions of properties such as solubility, dissolution rate, and stability,” Allen says. “Importantly, advanced AI approaches, such as those employed at Intrepid Labs, no longer rely on data-hungry ML models. In addition, combining technologies such as autonomous preparation and real-time sensing further enhances data-driven processes,” she adds.

In addition to predicting the most effective combinations of solubility enhancement technologies and excipients for drug development, Konagurthu believes use of AI/ML in this type of application can help scientists better understand the complex behavior of molecules, improve the speed of API discovery, and increase the accuracy of formulation development. “Ultimately, because these new technologies are able to generate high-quality data and insights for use throughout the drug discovery and development process, using them can have a significantly positive impact on budgets, timelines, and resources,” he states.

Another advantage of using AI/ML in formulation development is the ability to leverage wide-ranging datasets depending on the prediction target, route of administration, and so on. To address poor solubility, for instance, Allen notes that the apparent solubility or dissolution rate for amorphous solid dispersions (ASDs) can be predicted using ML models trained on datasets containing the composition of the ASD formulations, molecular descriptors, or other representations of the API(s) and polymers, and additional information on the method used to make the formulations, such as the processing parameters and attributes of the solution used for solubility or dissolution testing.

In many cases, computational chemistry methods including quantum mechanics (QM) and molecular dynamics (MD), quantitative structure-activity relationship models, and aspects of ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis are being applied to create customized formulation predictions as well, according to Konagurthu. To address poor solubility specifically, he adds that many solutions use proprietary algorithms to create predictive models based on specific properties of the substances. These tools are then used to generate predictive models for solubility and bioavailability enhancement; accelerated stability models for shelf-life and packaging determination; materials science, compaction simulation, and process models; and ADME/PK (pharmacokinetic) models to predict the effects of API physicochemical properties and pharmacokinetics.

For example, Konagurthu observes that techniques like QM/MD offer modeling capabilities that provide deep insights into physicochemical properties and molecular-level interactions, enabling structural mechanism exploration, free-energy evaluation, and spectroscopic characterization. “Using these insights in combination with AI/ML approaches has proven to be accurate and more efficient than trial-and-error experimentation,” he adds.

Application in formulation development is increasing

Over the past two decades, there has been a substantial increase in literature focused on the role of computational chemistry in the pharmaceutical industry, which highlights the capabilities of AI/ML in formulation development, according to Konagurthu. “The literature suggests an uptick in adoption and gives the scientific community proof points of how these new technologies address long-standing industry challenges of solving poor API solubility and bioavailability,” he notes.

One way to infer the level of adoption of AI/ML, Konagurthu says, is to look at the increase in regulatory submissions that involve these methods. Since 2021, FDA has received more than 100 submissions for drug and biologic applications using AI/ML components, spanning the drug development landscape from molecule to medicine (4). This surge in interest prompted FDA to create specialized regulatory groups that serve as both resources and facilitators of innovation for the pharmaceutical industry, he notes.

Specifically considering the development of formulations for poorly soluble/bioavailable APIs, Allen observes that the use of AI/ML is less advanced than it is for other areas of drug development, but it is growing.

To further the use of AI/ML solutions for formulation development, there are many hurdles to clear. As is the case with any data-driven application, large quantities of relevant, high-quality data are needed to create and train AI/ML models for formulation development. “Alternative ML approaches that require less data should also be evaluated. To see real success in this area, however, there is a need to embrace integration of AI/ML platforms within existing pharmaceutical frameworks,” comments Allen.

Other challenges noted by Konagurthu include model interpretability, intellectual-property concerns, cost of implementation, workforce training, and the need for regulators to develop and establish standards that not only help to maintain the integrity of these computational methods, but also help governing bodies evaluate submissions that use AI/ML in drug development.

These hurdles can be overcome, according to Allen, by building more interdisciplinary teams combining AI/ML expertise with pharmaceutical knowledge and increasing investment in AI/ML capabilities and training within the pharmaceutical sector​​. “Concerted efforts in data management, regulatory engagement, technology integration, and training will ensure that the benefits of AI and ML can be fully realized in pharmaceutical formulation development,” Konagurthu agrees.

Drug developers can also better leverage AI/ML platforms by identifying and working with a strategic contract development and manufacturing organization (CDMO) with deep experience and a strong track record of managing challenges posed by new technology adoption, according to Konagurthu. “For scientists who are looking to address poor API solubility and bioavailability, it can be extremely beneficial to collaborate with a CDMO specializing in computational drug development. CDMO partners are committed to staying at the forefront of pharmaceutical innovation and are adopting new technologies focused on speed, scalability, and innovation as a part of their end-to-end offerings,” he says.

Such partnerships can be highly effective in supporting pharmaceutical companies across the clinical supply chain, helping to ensure the faster delivery of high-quality therapeutics to patients, Konagurthu contends. He also emphasizes that widespread collaboration between pharmaceutical companies, CDMOs, and regulators on next-generation technologies could have many positive benefits for the pharmaceutical industry and the patients it serves.

AI/ML poised to have a significant impact

Both Allen and Konagurthu expect to see valuable short- and long-term benefits realized due to the use of AI/ML technologies to enable formulation development for APIs with poor solubility and bioavailability. For instance, working with colleagues at the University of Toronto, Allen has demonstrated that ML algorithms can be used to predict experimental drug release from long-acting injectable formulations and help guide their design (5).

“Using AI/ML technologies to address solubility and bioavailability challenges is a significant shift for the pharmaceutical industry. These technologies offer a more streamlined, accurate, and cost-effective path forward for drug development in general. For poorly soluble APIs in particular, they are enabling optimization of the selection of solubility enhancement technologies and excipients and paving the way for a more efficient and sustainable process,” states Konagurthu.

In the short term, Allen expects the enhanced predictive capabilities afforded by AI/ML platforms will lead to more efficient formulation processes. Longer-term, she anticipates that as drug formulation datasets reach critical mass and formulation scientists become more well-versed in AI/ML, ongoing advances in these technologies will continue to unlock new potential in formulation science, requiring continuous adaptation and learning within the industry. “There is tremendous potential for AI/ML to enable the accelerated discovery of new drug formulations and innovative drug delivery technologies,” she comments.

In fact, Konagurthu believes that AI/ML technologies “are poised to further accelerate the journey from molecule to medicine—leading us to a healthier society.” He adds that “as the industry continues to evolve, embracing these technological advancements will be key to overcoming long-standing challenges in drug development and unlocking new possibilities in the quest for more effective and accessible treatments.”

Jiang, J.; Ma, X.; Ouyang, D.; and Williams III, R.O. Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms. 

Allen, C. Machine Learning Directed Drug Formulation Development. 

Dong, J.; Wu, Z.; Xu, H.; and Ouyangt, D. FormulationAI: A Novel Web-based Platform for Drug Formulation Design Driven by Artificial Intelligence. 

FDA. Artificial Intelligence and Machine Learning (AI/ML) for Drug Development. March 18, 2024. 

https://www.fda.gov/science-research/science-and-research-special-topics/artificial-intelligence-and-machine-learning-aiml-drug-development

Richards,K. U of T Scientists Use AI to Fast-track Drug Formulation Development. Press Release. Jan. 11, 2023. 

https://www.utoronto.ca/news/u-t-scientists-use-ai-fast-track-drug-formulation-development

Cynthia A. Challener, PhD, is a contributing editor to 

®
Vol. 48, No. 6
June 2024
Pages: 14–17

When referring to this article, please cite it has Challener, C.A. Using Advanced Algorithms to Solve Formulation Challenges. 

Development

Artificial intelligence and machine learning can help overcome poor solubility and bioavailability.

Using Advanced Algorithms to Solve Formulation Challenges

Continuous processes continue to advance in bioprocessing. In downstream processing, continuous chromatography is gaining traction in the purification of protein therapeutics. As the biopharmaceutical industry strives to demonstrate, continuous manufacturing offers the benefits of higher productivity and better product quality than traditional batch manufacturing. In addition, continuous processing intensifies production and lowers capital costs, while enabling better control (1). 

Although significant strides have been made to advance continuous upstream processing, downstream processing has not advanced at the same pace. However, according to Gerstweiler et al., “Research on continuous chromatographic purification for antibodies is maturing, and work has commenced on other unit operations and on process system integration” (1).

Somasundaram et al. had earlier noted that “Rapid advances in intensifying upstream processes for biologics production have left downstream processing as a bottleneck in the manufacturing scheme” (2). But to increase efficiency and promote flexibility, biomanufacturers are looking to implement continuous downstream process development. However, despite successful laboratory trials, it has remained difficult to achieve continuous downstream processing at commercial manufacturing scale.

Perhaps another challenging aspect with continuous downstream processing is the ability to implement process control strategies. Advances in process analytical technologies and modeling techniques, however, may provide solutions to improving chromatography control for industrial-scale manufacturing (3). These advances offer opportunities to enhance process robustness, increase productivity and move towards real-time release testing.

It has been previously noted that process optimization and controlling the steps in downstream chromatography contributes to increased consistency of product quality as well as better management of process variability. In addition, control of the downstream processing steps can lead to cost reductions (3). However, the biopharma industry needs to enhance monitoring and control strategies to realize these benefits as current chromatography control strategies remain limited, leading to sub-optimal processing operations. Ultimately, this limitation in control strategies leads to delays in purification for new therapeutic molecules (3).

In speaking with Pharmaceutical Technology EuropeTM, Christine Rozanas, PhD, global product marketing manager at Cytiva, discussed the advantages and persistent challenges with implementing continuous downstream chromatography.

 What is continuous chromatography, and how has it improved downstream bioprocessing?

 Continuous chromatography differs from traditional ‘batch’ chromatography in two key ways: the chromatography system can be loaded continuously, which is a useful approach when the purification step is connected to an upstream perfusion or fed-batch bioreactor, and, by having two or more columns in the loading zone, you can overload the first column [because] any product/target molecule that is breaking through is being captured by the second column in the loading zone. When used with a perfusion or fed-batch bioreactor, continuous chromatography can help reduce the amount of resins and buffers needed. It also provides greater flexibility for processes and uses a smaller footprint in a manufacturing facility.

 What are the benefits of using a continuous chromatography process in downstream bioprocessing?

 Compared with batch operations, continuous chromatography can offer significant productivity gains and increased production capacity, for example, through increased utilization of chromatography resin binding capacity, reduced buffer usage, and smaller column size.

 What have been the major drawbacks or challenges to using continuous chromatography in downstream bioprocessing?

 Despite the benefits, the industry has been to slow to adopt continuous chromatography in downstream bioprocessing for a number of reasons. It can be a more complicated set up compared to a traditional batch process, and, while batch chromatography is done over a single shift or sometimes over 24 hours, the larger volumes processed continuously from perfusion or fed-batch bioreactors must be processed over several weeks or up to a month. [This] can make it more difficult to trace any potential issues that might occur. While regulatory agencies express interest in supporting the use of continuous processing, many companies continue to develop batch purifications first, before evaluating whether a continuous chromatography process would significantly reduce production costs or increase productivity and output.

 How does multi-column continuous chromatography work, and in what scenarios would a biomanufacturer opt to implement this?

 For multi-column chromatography, the large capture column is split into multiple smaller columns that alternate in binding and elution operations in multiple cycles to process the feed from the upstream bioreactor. It can be a great option when working with sensitive molecules, where continuously removing the molecule from a potentially harmful environment into the first purification step can be the only viable option. In scenarios where there is a limited product demand (in kg), continuous chromatography can also allow significant reduction of the needed resin volume through running a higher number of cycles in the available time and thus reducing the column size.

 What key innovations have been instrumental in promoting the use or adoption of continuous chromatography?

 [Some] continuous chromatography systems use controls (e.g., dynamic ultraviolet control, as with Cytiva’s systems) that enable real-time monitoring and control of the process. In Cytiva’s case, its system can adjust accordingly to changes in feed concentration, for example, to optimize processing of the perfusion output. Also, pre-packed columns have provided greater consistency and quality of the internal conditions of each column so that the feed is processed in the exact same way in the alternating columns during the continuous run.

1. Gerstweiler,L.; Bi, J.; Middelberg, A. P. J. Continuous Downstream Bioprocessing for Intensified Manufacture of Biopharmaceuticals and Antibodies. 

, 116272. DOI: 10.1016/j.ces.2020.116272
2. Somasundaram, B.; Pleitt, K.; Shave, E.; Baker, K.; Lua, L. H. L. Progression of Continuous Downstream Processing of Monoclonal Antibodies: Current Trends and Challenges. 

 (12), 2893–2907. DOI: 10.1002/bit.26812
3. Armstrong, A.; Horry, K.; Cui, T.; et al. Advanced Control Strategies for Bioprocess Chromatography: Challenges and Opportunities for Intensified Processes and Next Generation Products. 

, 461914. DOI: 10.1016/j.chroma.2021.461914

Feliza Mirasol is the science editor for 

ope®
Vol. 36, No. 6
June 2024
Pages: 30–31

When referring to this article, please cite it as Mirasol, F. Evaluating the Use of Continuous Chromatography. 

Manufacturing

The biopharma industry is looking at continuous chromatography for sensitive molecules.

Evaluating the Use of Continuous Chromatography

Raw materials are integral to developing and manufacturing safe and effective therapies. When the supply of these materials is in jeopardy, so are the final drug products those materials are used in. Any delay in the complex supply chain of a drug can lead to a shortage of much needed medications.

The COVID-19 pandemic highlighted some of the problems in supply chains of many different products, not just pharmaceuticals. The fast development and market delivery of COVID-19 vaccines and treatments, however, also created a belief that drugs can be developed, manufactured, and marketed quicker than the industry has been used to, according to Jordi Robinson, chief commercial officer, Navin Molecular. “As such, there has been a shift in the industry whereby delivery times of raw materials need to be faster, with the aim of getting molecules into the clinic more rapidly than ever,” says Robinson. In this post-pandemic world, pharmaceutical manufacturers are applying the lessons learned during COVID-19 in regard to the supply of the raw materials they procure.

Some pharma companies are choosing to make APIs and excipients in-house instead of relying on foreign suppliers, and others are diversifying the suppliers they choose to obtain materials from. “This helps ensure a steadier flow of materials, which is crucial to keep production lines humming. Of course, there’s a trade-off. Companies are also holding onto more safety stock—extra ingredients in case things get tight again. It might mean a bit more storage space needed, but it’s a small price to pay to avoid those production slowdowns,” says Ada Bedelek, director of Supply Chain and Demand Planning, C2 PHARMA.

“By lowering reliance on China and other vulnerable geographies and supplier de-risking through a diverse supply base, efforts have been made to diversify and build a robust supply chain,” says Sundar Narsimhan, chief procurement officer at Neuland Labs. “To lessen future interruptions, there is also a stronger focus on sourcing essential supplies from local production to secure critical materials and ensure supply continuity during crises, while aligning with broader economic and geopolitical strategies to decrease reliance on far-flung supply markets. Companies are also focusing on shortening the supply chain through better logistics and distribution practices, that help improve agility and responsiveness to market changes.”

Wherever they obtain their materials, manufacturers should find suppliers that provide quality materials in a reliable fashion because the final product is influenced by the consistency of the raw materials involved, asserts Bedelek. “Therefore, it’s crucial to thoroughly evaluate suppliers’ quality management systems, certifications, and track records to ensure they consistently meet specifications. When evaluating reliability, assessing the supplier’s capacity, production capabilities, and supply chain resilience helps avoid risks of disruptions,” she states.

When choosing a raw materials supplier, Selwyn Lustman, senior vice president, Global Sourcing and Procurement, LGM Pharma, specifies that pharma companies should ensure that a supplier meet the basic criteria of quality, price, and delivery. Pharma companies should also consider how long the supplier has been in business and if the supplier’s goals and priorities align with those of the pharma company, he remarks. The supplier should be able to meet the pharma company’s short- and long-term needs and provide sufficient space capacity to meet requirements. Suppliers should also have all the needed approvals for the appropriate markets. Environmental requirements are also a consideration, according to Lustman.

Suppliers must follow current good manufacturing practices (CGMPs) and maintain a robust quality system, emphasizes Narsimhan. “Alongside this, factors such as reliability, financial stability, stringent quality controls, and ethical conduct are also crucial considerations,” he adds. “Additionally, when selecting a supplier, we keep a close eye on his/her past performance, innovative approaches to efficiency, and customer-centricity.”

Robinson points to sustainability as a “critical factor” in selecting a supplier. “The supplier’s approach to sustainability is also becoming a critical factor in materials sourcing, with a requirement that they achieve minimum standards in both industry metrics (such as their Ecovadis rating) and reporting,” he says.

“Additionally, sourcing groups are often under pressure to reduce the number of suppliers that they use, so ideally a chosen partner should offer a broad platform of technologies as well as the ability to support a wide range of manufacturing scales,” Robinson adds.

The type of raw material needed should also be a consideration for manufacturers when deciding on a supplier. The nature and complexity of raw materials, as well as the techniques needed to produce them, may require different supply chain securities, explains James Lawler, general manager, C2 PHARMA. “In addition, raw materials for APIs which are designated as lifesaving medicines or form part of niche or orphan drugs may require additional security measures,” he says. “These can vary widely and are critical factors when considering supply chain securities.”

“Alongside the increasing pressure to deliver new drugs to the market quickly and efficiently, is the complexity of new molecules, and, by extension, their raw materials,” says Robinson. “In order for the supply of such materials to meet clinical and commercial demand uninterrupted, it is critical that key materials can be sourced from multiple suppliers. These will often be strategically spread geographically, to mitigate against any potential manufacturing issues that might arise, or wider geopolitical issues that could affect the supply chain.”

Flexibility and adaptability can be ensured by having multiple suppliers of necessary raw materials. However, warns Bedelek, more suppliers mean performing more qualification actions. “If the demand is small, it may not be worth qualifying several suppliers,” she says. “While there are benefits to working with multiple suppliers, it’s essential for manufacturers to carefully manage these relationships to optimize performance effectively.”

Lustman agrees that additional suppliers may mean additional precautions and work. “When a manufacturer develops a new drug product, they will generally go with the source that meets the right quality, regulatory, pricing and delivery requirements,” he says. “Approving more than one API source requires significant time and manpower; specifications of both/all sources have to match to ensure approval of the drug product by the authorities. Some manufacturers may choose to work with one source for launch and then add a further source later. It is very rare to see more than two API sources being approved for any one drug product. The key is to work with reliable sources, have good relationships with them, give forecasts and confirm POs well in advance of need to ensure a continuous supply chain.”

Narsimhan counters that not having a good supply of materials outweighs the risk and cost of multiple suppliers. “Diversifying suppliers not only mitigates risks but also introduces new perspectives and strategies for achieving efficiency, fostering innovation throughout the supply organization, and promoting sustainable solutions across all business domains. However, it’s essential to allocate business shares appropriately and employ scientific criteria to ensure optimal outcomes from this practice,” he says.

Intermediates, used during API synthesis before the molecule becomes an API, are hygienically formulated using high-grade raw materials (1) and are often used in research and development. Advanced intermediates are advanced forms of drug intermediates used to perform drug interaction activity (1). According to Lawler, the supply of these important materials is tenuous. “Availability of key materials relies heavily on suppliers being able to produce intermediates utilizing a wide variety of, and often complex manufacturing techniques. However, the supply and availability of these may also be limited or restricted due to high manufacturing costs, high raw material costs, availability of materials, environmental concerns and/or restrictions, and on geo-political factors,” he says.

According to Lee Karras, CEO, Noramco Group, “there is a gap in high-quality, domestically supplied advanced intermediates—most come from India and China. These advanced intermediates still require significant regulatory oversight, and in many cases, are regulated similarly to final raw materials/APIs.”

“The supply chain for advanced intermediates is fraught with challenges that tend to affect its resilience. The intricacies of synthesis, rigorous regulatory and quality control requirements, and the ever-changing dynamics of the global market and cost pressures brought about by competition are among the factors that pose hurdles in the supply chain for advanced intermediates used in API synthesis,” says Narsimhan. “To address these concerns and establish a robust supply chain, stakeholders often implement strategic sourcing strategy that focusses on continually generating options for diversifying/derisking the supplier base; [adopting] risk management practices to address supply risks; and relentlessly [monitoring] supply market signals. Additionally, collaboration among industry participants, regulatory bodies, and research institutions plays a crucial role in overcoming challenges and bolstering resilience in the supply of advanced intermediates.”

“There is a change in the market regarding advanced intermediates,” asserts Lustman. “Traditionally, starting intermediates and advanced intermediates were sourced from China. The Indian manufacturers understand that this may lead to supply chain issues with an overreliance on Chinese manufacturers of raw materials. Many Indian API manufacturers are now backward integrating their process so that they can start production of API from the early starting materials. This [integration] ensures a stable supply of needed advanced intermediates and better control over costs.”

Onshoring versus foreign supply is a debate that extends across many industries. The critical nature of patients in need of safe and effective medicines adds to the complicated conversation. Drug manufacturers have a variety of quality, regulatory, and cost considerations to evaluate. Ensuring a quality product means performing risk management and qualification of the materials used in drug products.

Narsimhan points out that countries have taken steps to stabilize the supply chain and there has been a move toward onshoring. “This [move] involves decreasing our dependency on certain international suppliers and establishing our own local supply lines. I’ve personally witnessed companies placing greater importance on strengthening partnerships with local suppliers. This strategic shift aims to reduce our reliance on unpredictable supply sources, resulting in a shorter supply chain, increased resilience, lower transportation costs, and ensuring a more secure and reliable provision of critical materials,” he says.

According to Lustman, there is a shift in industry away from suppliers located in China to those located in India and Europe, which has been driven by geopolitical and quality factors. “A US bill has recently branded certain Chinese biotechnology companies as security threats. The bill is a threat not just to a few specific companies in China, but also to the wider pharmaceutical industry based there,” he states. “With increased FDA inspections of foreign manufacturing facilities, we are seeing more scrutiny on the quality of APIs being shipped to the USA. To help ensure quality and reliability of API production, many drug product manufacturers are reassessing the sources of product they are purchasing from, with a move to Europe and India from China.”

“The increasing tensions around the China-Taiwan situation, as well as recent developments with respect to the [United States] and the use of Chinese CDMOs [contract development and manufacturing organizations] has led to changes in sourcing strategy for many big companies, with many now employing a ‘China +1’ approach, whereby at least one of the material suppliers has to be non-Chinese,” adds Robinson. “This has led to an increased preference for providers in other low-cost economies such as India, and in some cases the re-shoring of projects to Europe and the US. A requirement for manufacturing partners to similarly be ‘China independent’ in respect of their own supply chains is becoming an important factor in the selection of vendors, to ensure robust, secure provision of materials.”

So, should manufactures choose a supplier close to home? “For security of supply chain and risk mitigation, where possible, most companies look to have multiple sources of raw materials and advanced intermediates. It is always preferable to have reliable suppliers which are either based domestically, local, or both, and many companies now favor full or nearly full back integration for key intermediate supply especially for high value APIs and those under patent protection,” specifies Lawler.

“I fully expect that drug shortages will continue to be the norm and actually get worse, without a real commitment from the US government to ensure more high-quality domestic supply,” warns Karras.

BioSpace. Drug Intermediate Market: Fast Growing Biotechnology and Life Sciences Sectors Is Expected to Drive the Growth. 

When referring to this article, please cite it as Haigney, S. Diversifying the Supply of Raw Materials. 

The final drug product relies on the quality and reliability of the raw materials used in its production.

Diversifying the Supply of Raw Materials 

Developing a robust and reliable strategy for analytical studies of a biosimilar in development is crucial for a successful regulatory pathway. The importance of biosimilar products is tied to the push for more affordable, accessible biological treatments. However, bringing a biosimilar to market has strict challenges because the biosimilar developer must have a large set of analytical similarity data compared to the innovator biologic. In addition, the biosimilar developer must also contend with demonstrating interchangeability (1). 

Establishing biosimilar analytical studies

There are several key criteria to consider when establishing analytical studies for a biosimilar drug candidate to ensure its safety, efficacy, and similarity compared to the reference product, says Olaf Stamm, PhD, technical business development director, Biopharmaceutical Testing Solutions, Charles River Laboratories.

Among these criteria are comparability, biological activity, impurity assessment, and stability studies, Stamm notes. He explains that, for comparability, the biosimilar needs to demonstrate similarity to the reference product in terms of structure, function, purity, and potency. Analytical methods should thus be chosen or developed to compare critical quality attributes (CQAs) between the biosimilar and the reference product. “This involves assessing the physicochemical properties of the biosimilar, such as molecular weight, size, charge, and higher-order structure. Techniques [such as] mass spectrometry, chromatography, spectroscopy, and electrophoresis are commonly used for this purpose,” Stamm says.

The biological activity of the biosimilar should also be evaluated in analytical studies to ensure it matches the biological activity of the reference product. Analytical studies for determining biological activity may involve in-vitro assays, cell-based assays, or other relevant biological assays depending on the mechanism of action of the drug, Stamm remarks.

Identifying and quantifying impurities should include process-related impurities, degradation products, and contaminants. This is a crucial aspect of biosimilar development, Stamm notes. “Analytical methods should be sensitive enough to detect impurities at levels that are relevant to safety and efficacy,” he states. Stamm also points out that analytical methods should be established to identify and quantify residual host cell proteins to ensure they are within acceptable limits because their presence could impact safety and efficacy as well. “The evaluation of process-related impurities, such as residual solvents, reagents, and by-products, should be performed using appropriate analytical techniques,” he adds.

Meanwhile, stability studies are essential for assessing the biosimilar product’s shelf-life under various storage conditions. Analytical methods used for stability studies should monitor degradation pathways and stability-indicating parameters over time.

In biosimilars development, it is not enough to establish analytical evidence of the product’s biosimilarity to the reference product, but also its interchangeability. Luckily, establishing analytical studies for testing biosimilarity and interchangeability involves similar principles, Stamm explains. However, there are some key differences in the objectives and scope of these studies.

Stamm points out that the primary objective of analytical studies for demonstrating biosimilarity is to demonstrate that the proposed biosimilar is highly similar to the reference product in terms of quality, safety, and efficacy. “The goal is to show that any differences between the biosimilar and the reference product are not clinically meaningful,” he says.

In comparison, the objective of studies for interchangeability goes beyond demonstrating similarity. “[Interchangeability studies] aim to provide evidence that the biosimilar can be substituted for the reference product without any additional risk in terms of safety or diminished efficacy compared to using the reference product alone,” Stamm states.

Stamm further explains that interchangeability studies may involve additional clinical work. “Clinical studies for interchangeability are specifically designed to assess the impact of switching between the biosimilar and the reference product on safety and efficacy outcomes. These studies may include switching studies, pharmacokinetic (PK) and pharmacodynamic (PD) assessments, and immunogenicity evaluations in both naive and switch populations,” he says.

Both biosimilarity studies and interchangeability studies provide information that is crucial for regulatory authority evaluation. Stamm emphasizes that each type of study yields required data as explained in the following sections.

 According to Stamm, biosimilarity studies generate extensive analytical data comparing the biosimilar product’s CQAs with the CQAs of the reference biologic, including physicochemical characterization, biological activity assays, impurity profiling, and stability data.

 Meanwhile, clinical studies provide evidence of equivalent efficacy, safety, and immunogenicity between the biosimilar and the reference product in sensitive patient populations. These studies typically include PK/PD assessments as well as comparative clinical trials in relevant patient populations.

 Immunogenicity data—including an assessment of the development of anti-drug antibodies—is also a critical component of biosimilarity studies because these data help evaluate the potential risk of immunogenic reactions to the biosimilar.

 Interchangeability studies yield data on the safety and efficacy of switching between the biosimilar and the reference product, notes Stamm, who explains that these studies also include assessments of PK/PD, immunogenicity, and clinical outcomes following multiple switches between the two products.

Data from interchangeability studies also provide insights into patient outcomes from the impact of switching medications, including any potential risks associated with switching between the biosimilar and the reference product.

 Immunogenicity of the biosimilar product is also assessed in patients who undergo repeated switching between the biosimilar and the reference product.

 Regulatory authorities require evidence demonstrating that switching between a biosimilar and its reference product neither compromises clinical outcomes nor poses additional risks to patient safety or efficacy compared to using the reference product alone.

“Overall, both biosimilarity and interchangeability studies generate comprehensive data sets that regulatory authorities evaluate to assess the similarity, safety, efficacy, and interchangeability of biosimilar products compared to their reference products. These studies are essential for the regulatory approval of biosimilars and for ensuring their safe and effective use in clinical practice,” Stamm concludes.

1. Mirasol, F. Moving Biosimilars Forward in a Hesitant Market. 

ope®
Vol. 36, No. 6
June 2024
Pages: 32–33

When referring to this article, please cite it as Mirasol, F. Reviewing the Importance of Biosimilarity and Interchangeability. 

Analytics

Biosimilar analytical assessments focus on demonstrating biosimilarity and interchangeability with the reference biologic.

Reviewing the Importance of Biosimilarity and Interchangeability

On 3 May 2024, the European Medicines Agency (EMA) initiated a public consultation to review draft recommendations published in its reflection paper on “the use of real-world data (RWD) in non-interventional studies (NIS) to generate real-world evidence (RWE)” (1). The paper discusses methodological aspects of NIS using RWD, such as claims databases, hospital data, electronic health records (EHR), registries, and medical health data, to generate RWE for regulatory decision-making. The paper is part of the Methodology Working Party Workplan 2022–2024 and the joint Heads of Medicines Agency (HMA)-EMA Big Data Steering Group plan 2023–2025 (2,3).

According to EMA, a clinical trial is defined as a clinical study where:

the assignment of the subject to a particular therapeutic strategy is decided in advance and does not fall within the normal clinical practice of the member state concerned

the decision to prescribe the investigational medicinal products is taken together with the decision to include the subject in the clinical study

diagnostic or monitoring procedures in addition to normal clinical practice are applied to the subjects. RWD are data that describe patient characteristics (including treatment utilization and outcomes) in routine clinical practice (1).

A NIS is a clinical study that does not fulfil any of the above conditions, based on Article 48 of Regulation (EU) No 536/2014 on clinical trials on medicinal products for human use (4).

Key topics discussed in the reflection paper

The reflection paper discusses feasibility assessment, bias, confounding, and data quality and provides guidance on four key areas:

The paper also recognizes the importance of using protocol formats when designing NIS for RWD generation. For example, applying the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP) Checklist for Study Protocols and The HARmonized Protocol Template to Enhance Reproducibility (HARPER) protocol template (5,6).

In March 2024, the US Food and Drug Administration (FDA) published its draft guidance on 

Real-World Evidence: Considerations Regarding Non-Interventional Studies for Drug and Biological Products

, which is open for consultation until 18 June 2024 (7). EMA’s guidance closely aligns with FDA’s; however, the regulatory agencies’ definition of NIS differs and further clarification and standardization will help drive the utilization of RWD moving forward (8).

EMA promotes the use of RWD in decision-making

EMA’s Regulatory Science Strategy to 2025 promotes using high-quality RWD in decision-making (9). To this end, EMA aims to create a flexible framework to deliver rapid access to and analysis of RWD throughout a product’s lifecycle; to develop computing capacity and skills in the agency to analyze large amounts of healthcare data, and to implement processes to feed data into regulatory assessments.

In March 2024, EMA launched its RWD catalogues to help regulators, pharmaceutical companies, and researchers identify and use RWD to investigate the safety and effectiveness of medicines (10). The catalogue of RWD sources replaces the ENCePP Resources Database. The data are searchable and can be exported by registered entities.

In April 2024, EMA’s Real-World Evidence Team (TDA-RWE) of the Data Analytics and Methods Task Force released new guidance detailing the types of studies that can be performed for RWE generation and how it can be used to support regulatory decision-making (11). The regulators recognize that RWD provides additional benefits compared to traditional randomized control trials. For instance, it can be generated quickly and reduce the risk of data duplication, RWD can be used to fill in knowledge gaps and provide tailored analyses to the committee’s questions (11).

The draft reflection paper highlights the importance that EMA places on RWD and its potential impact on decision-making. It also establishes a framework for scientific and methodological rigour, helps to improve the transparency of data collection and analysis, and ultimately should increase the reliability of RWD generated by the industry.

The reflection paper will be presented at the multi-stakeholder joint HMA-EMA workshop on RWE methods on 14 June 2024 (12). Stakeholders are invited to provide feedback on the draft reflection paper by 31 Aug. 2024.

1. EMA. Reflection Paper on the Use of Real-World Data in Non-Interventional Studies to Generate Real-World Evidence. Draft Reflection Paper. 

. 15 April 2024.
2. EMA. Revised Consolidated 3-Year Work Plan for the Methodology Working Party (MWP). Work Programme. 

. 15 Jan. 2024
3. HMA/EMA Joint Big Data Steering Group. Big Data Workplan 2023–2025. Work Programme. 

Regulation (EU) No 536/2014 on Clinical Trials on Medicinal Products for Human Use

. 16 April 2014.
5. ENCePP. ENCePP Checklist for Study Protocols. 

, 15 Oct. 2018.
6. Wang, S.V.; Pottegård, A.; Crown, P.; et al. HARmonized Protocol Template to Enhance Reproducibility of Hypothesis Evaluating Real-World Evidence Studies on Treatment Effects: A Good Practices Report of a Joint ISPE/ISPOR Task Force. 

. Guidance Document, March 2024.
8. McCully, S. What’s in a Name? Towards Standardizing the Terminology of Real-World Data and Real-World Evidence. 

, 30 Jan. 2024.
9. EMA. Decision-Making. 

EMA is promoting the use of RWD in decision-making and has started a public consultation to review its draft recommendations.

Pharmaceutical Technology, June 2024

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Diversifying the Supply of Raw Materials

Reviewing the Importance of Biosimilarity and Interchangeability

Using RWD in Non-Interventional Studies

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