Behind the Headlines Episode 27

Ask the Expert

Small Molecules, APIs, and Excipients—Trends, Challenges, and Opportunities

Drug Digest September 2025

Artificial intelligence, machine learning, and novel instruments are helping drug developers.

Enhancing Bioanalysis and Drug Development with Advanced Tools and Technologies

J.P. Morgan Report Lists Biologics, Obesity, China

Top Trends Reshaping Pharma R&D

3D Robot arm working automated in factory, industry 5.0 artificial intelligence computer aided manufacturing process control with computer digital technology modern futuristic background | Image Credit: © DIgilife - stock.adobe.com

The bio/pharma manufacturing industry is an ever-growing and evolving landscape, where emerging modalities and shifts in the field drive technological innovation. Advances in the field are clear to see from the approval rates by regulatory bodies, such as FDA’s Center for Drug Evaluation and Research, which approved 55 novel drugs in 2023 (1) for a variety of conditions. Therapeutic areas such as oncology and immunology are expected to dominate spending worldwide until 2027 (2) thanks, in part, to product innovations, improved patient outcomes, and increasing incidence of disease. Along with this market growth, cell and gene therapies, messenger RNA (mRNA) vaccines, and other new advancements have spurred innovations in every aspect of the pharmaceutical industry, including manufacturing of both small-molecule and large-molecule drugs.

Regarding current technological developments, Daniel Spurgin, director of Strategic Partnerships at ReciBioPharm, points to an industry need for speed, specifically through artificial intelligence (AI). “We’re seeing a rise in the utility of AI to monitor, control, and predict processes. However, AI technologies are only as good as the data they are trained on. Tightly controlled real data [are] essential to realizing the power of digital technology,” Spurgin says. “Autonomous decision-making allows processes to advance to next-unit operations without the need for quality gates and human intervention. In some cases, traditional release panels may be required based on regulatory positions, but the ability to autonomously advance processes would drastically improve the speed and quality of drug manufacturing, which is why FDA is funding MIT and ReciBioPharm to develop such capabilities for RNA modalities.”

Melanie Langhauser, team lead, Process Development DSP and Analytical Development, Ascend Advanced Therapies, has similar thoughts on the focus of the industry. “The biggest developments in manufacturing technology are focused on improving the productivity and efficiency of production processes while simultaneously boosting quality and reducing cost, particularly in the advanced therapies space, where robust, cost-effective, scalable processes are essential to future success,” she says. “Reducing the manufacturing costs is one important goal in our field, but what is even more important for our clients is to shorten the time to market.”

The bio/pharma market is moving towards greater integration of data analytics, machine learning, and AI, according to Oladimeji Fashola, chief technology officer, Quantoom Biosciences. This shift comes from a desire for process optimization, predictability, and a need for real-time decision-making. “Manufacturers are also focusing on personalized care vaccines/therapies,” he adds.

This focus is also seen by Cyrill Kellerhals, COO, Andelyn Biosciences, who states that personalized medicines require small batch manufacturing for increasingly smaller patient populations. He points to the emerging need to “tailor efficacy and limit side effects based on individual differences.”

But in the adeno-associated virus (AAV) manufacturing space, Langhauser reveals that current processes fall short. Manufacturers and equipment suppliers have been hard at work developing solutions, which include new engineered AAV serotypes, cell lines designed to produce AAV vectors, more efficient transmission systems and offline assays, and purification technologies designed specifically for viral vectors. Langhauser says that “the small intermediate volumes of the gene and cell therapy area are driving a clear need for equipment manufacturers to develop good manufacturing practice (GMP)-ready devices or solutions. And step by step, the manufacturers recognize that and develop solutions for the gene and cell therapy area.”

“What we still need,” Langhauser says, “are scalable single-use filtration solutions. [Because] a lot of filters are coming from the antibody world the first single-use filters are much too big for the advanced therapies space. We need smaller filters and filter holders in a single-use format. And to have a scale-down model of these filters for later robustness studies, we are up-scaling the filters more than necessary (the maximum capacity of these filters is not reached). So, we underload the filters even if we receive lower step yields.”

Avi Nandi, head of US Cell and Gene Therapy, SK pharmteco, also points to rising informational technology demands. “Manufacturers will need improved IT infrastructure to enable an integrated facility, accessible aggregate data repositories, automation and IT engineers, investment into analytical tools, and consider options to reduce overall [cost of goods sold] (like optimized suite design and process workflows to enable higher throughput operations as demands increase with more commercial approvals).”

In regard to the impact of new modalities, such as cell and gene therapies and mRNA, Fashola says, “The emergence of cell and gene therapies alongside mRNA vaccines has catalyzed substantial innovation not only in manufacturing technology but also in regulatory paradigms governing drug approval and market entry. Advancements are evident across scientific areas, particularly within cell and gene therapies, where techniques such as CRISPR [clustered regularly interspaced short palindromic repeats]-Cas9-mediated gene editing of stem cells are revolutionizing treatment modalities by correcting genetic mutations.”

“Furthermore,” he states, “mRNA technology has unveiled countless therapeutic possibilities, including vaccines targeting historically challenging diseases like HIV and cancer, thus representing a significant stride forward in biomedical intervention.”

Spurgin stresses the impact of cell-free DNA and bio-catalysis agents as critical raw materials for mRNA and cell and gene therapies. “Historically, plasmids have largely been derived from 

], which often requires significant development time and comes with a technology limitation (larger plasmids are more challenging to produce from 

),” he says. “The emergence of a cell-free plasmid DNA process significantly reduces those barriers. The same can be said about the emergence of enzymes and their use in manufacturing. They are making modalities such as xRNA more efficient, cleaner, and faster to manufacture.”

Advanced therapy medicinal products (ATMPs) can be more complex to understand and manufacture, specifies Nandi, who also points to more complexity in predicting clinical outcomes. ATMPs tend to have high cost of goods sold, aggressive timelines, and poorly understood product safety and efficacy. “As such, the technologies are diverse and rapidly evolving in response to improved understanding of these molecules with respect to product design, delivery vehicles, raw materials, cell lines, scalable technologies, analytical tools, etc.”

Nandi points to two main outcomes of ATMP development, the first being manufacturing success and the second being clinical data to validate manufacturing platforms. “We’re entering a time,” he says, “where clinical data, namely phenotypic determinants of response, will inform design of next-generation manufacturing technologies.”

In the continuous manufacturing space, Langhauser states that continuous processing for viral vectors is still in the beginning stage. “Companies are exploring the use of perfusion for intensifying the cell culture process prior to transfection. Making the transfection step continuous would be challenging, but for processes levering stable producer cells, running in perfusion mode is certainly possible. There is also potential for use of continuous chromatography techniques, while large-pore membrane and fiber-based media can enable process intensification, if not fully continuous operation. Some companies are already using single-pass tangential flow filtration to reduce process times and increase product recovery.” She stresses, however, that for continuous process development to be successful, one must have a “deep understanding” of the process. Process analytical technologies (PAT) and real-time monitoring are essential to keep continuous processes in control.

Spurgin concurs with the need for PAT and real-time monitoring. “Classical batched manufacturing contains a list of offline quality assays that gate manufacturing steps,” he says. “These transfers of samples and information are wasteful and slow and can negatively impact product quality where intermediates are unstable. Moving analytics from the lab and into the manufacturing stream aligns process steps with quality tests. Inline PAT can provide streamlined product characterization, real-time process monitoring and progression.”

The utilization of continuous manufacturing is on the rise, especially in the production of cell lines to create materials for vaccine and cell and gene therapy manufacture, according to Fashola. “This entails the use of continuous 

fermentation reactors that integrate with downstream processes for harvesting, lysis, purification, and filtration. Conversely, in the realm of mRNA vaccines, there is a concerted effort to enhance cost-effectiveness, throughput, and efficacy. To achieve these goals, continuous processes are being implemented from initial IVT [

 transcription] reaction through purification to encapsulation.”

AI has surged in a variety of industries in the past few years, including the pharmaceutical industry. Langhauser sees the technology growing in both drug development and manufacturing. “However, to be effective, AI systems must be constructed using large quantities of robust and truly representative data, otherwise any output they provide will be inaccurate and likely result in poor decision making,” she stresses. “As more processes are automated and the type of reliable data needed to build relevant AI models [are] generated, an inflection point will eventually be reached where AI systems will be able to predict everything from the general, such as the best combination of process steps, to the detailed, such as optimal process parameters, to the mundane, such as ideal preventive maintenance schedules.”

According to Spurgin, full-scale AI adoption still faces barriers. “AI is currently being leveraged across many early-stage drug discovery activities. The ability to select, screen, and characterize potential candidates was fairly easy to implement with no regulatory burden. It is different in the case of late-stage projects,” says Spurgin. However, he says that even though “AI’s most powerful use is in the manufacturing space,” regulators and manufacturers have been conservative with its implementation.

The perspective of regulators on the implementation of new and advancing technology is an important factor, agrees Langhauser. She believes that industry must show how technology can provide greater yield, improved quality, and faster time to market, all at a lower cost. “[FDA] is very interested in emerging technologies that will accelerate process development, improve quality, and lower costs,” she confirms. “The best approach is to collaborate with the agency, and if the new technology is provided by a supplier rather than developed in house, proactively seek to collaborate with the supplier as well as regulatory authorities so the technology that results truly is fit-for-purpose and regulators are aware, not only of the benefits, but of the entire effort involved in bringing the technology to the point where it is validated and proven to be appropriate for GMP manufacturing.”

“Product and manufacturing costs need to be carefully monitored and managed,” says Kellerhals, “to ensure continuing excellence and quality while being optimized for efficiency. Technology development is often faster than the regulatory environment, and in a risk adverse industry, adoption of new technologies can be challenging, and more so as you go from evolutionary new technologies to revolutionary new technologies.”

Kellerhals continues, “Decisions must be data driven—what are the advantages, what are the risks, what is the timing, and what are the quality and regulatory questions that must be addressed before a new technology is introduced and accepted.”

Advances in technologies can still lead to setbacks, warns Kellerhals. “Often, new analytical technologies provide breakthrough abilities to better develop or characterize new drugs, but there can be lags in time before those technologies or instrumentation are mature enough to be implemented in GMP settings,” he states. “This results in challenges implementing the newest or the best analytics in early phase clinical productions.”

“The biopharmaceutical industry is conservative in nature, so some technologies, particularly those that may raise questions from regulators, are slow to be adopted,” says Langhauser. “Manufacturers must weigh the risks associated with regulatory uncertainty against the benefits any new manufacturing technology may bring.”

“Looking specifically at technology challenges for viral vectors, the biggest hurdle for those companies using transient transfection, given the inherent nature of this process, is boosting the titer while simultaneously achieving selectivity for full capsids, and doing so at large scale,” Langhauser adds. “Progress has been made … but there is much more to do.”

. https://www.fda.gov/drugs/new-drugs-fda-cders-new-molecular-entities-and-new-therapeutic-biological-products/novel-drug-approvals-2023

Statista. Projected Top Therapy Areas Worldwide in 2027, by Spending. 

https://www.statista.com/statistics/281951/top-therapy-classes-in-developed-pharmaceutical-markets-by-spending/

When referring to this article, please cite it as Husni, D. The Growing Future of Drug Manufacturing. 

Articles

With an ever-growing market driving technological advances, there is always work to be done in drug manufacturing.

The Growing Future of Drug Manufacturing

Valerie Mulholland is a PhD Candidate, Pharmaceutical Regulatory Science Team (PRST), Technological University Dublin.

Anne Greene, PhD, is director PRST, Technological University Dublin.

 This article was peer-reviewed by a member of 

Submitted: June 11, 2023
Accepted: March 5, 2024

Cube wooden block with alphabet building the word RISK. Risk assessment | Image Credit: ©Dontree - stock.adobe.com

In November 2020, the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) announced it was appointing an Expert Working Group (EWG) to update the quality guideline, ICH Q9 

 (1). The concept paper, published in support of this announcement, noted a number of areas of improvement, one of which was risk-based decision-making (RBDM) (2). The concept paper stated that there was a “lack of clarity” on what good RBDM means, and that that there was a “breadth of peer reviewed research” in this area. The Pharmaceutical Regulatory Science Team (PRST), based in Technological University Dublin, embarked on an exploration of this research, and this paper presents some of the outputs of this study. The hope is to clarify or ‘demystify’ what RBDM is, and to offer some suggestions as to how to improve or enhance RBDM to improve quality risk management (QRM) effectiveness for the benefit of the patient.

There are many decisions made within a pharmaceutical product lifecycle and within a pharmaceutical manufacturing operation. Most of these decisions involve the consideration of risk, including risk to patient safety, product quality, and product availability. In this context, it is prudent to focus upon RBDM and to consider why it differs from other decision-making within a pharmaceutical quality system (PQS) and why, as is proposed by the ICH Q9(R1) concept paper, that by improving RBDM, the output of QRM processes might also be improved.

This paper is structured using the 5W1H method of problem definition (a tool with intriguing origins in a Rudyard Kipling poem [3]). The questions, illustrated in 

, are used to explore the subject of RBDM.

Figure 1: The 5W1H Problem Solving Method. [Figure courtesy of the authors]

 The most obvious answer to why one should focus on RBDM is because it is recommended in the updated risk management guideline ICH Q9(R1), which was published on Jan. 18, 2023 (4). This revision contains a new section, section 5.2, on RBDM. This alone should focus one’s curiosity on RBDM. However, the authors propose that by using another tool of problem solving, the 5Whys, perhaps further layers of ‘why?’ (at least three) are needed to fully appreciate the objective of adding RBDM to the revision.

Why add RBDM to ICH Q9(R1)? The ICH committee explained, in the 2020 concept document, why the topic of RBDM was under consideration. According to this document, it was determined that there was “a lack of clarity” with both the term and with the application. How this problem statement was determined is a little less clear.

However, the main reason for its inclusion might be that the full value of QRM, as envisaged when the original ICH Q9 was published in 2005, was not fully realized. The aspiration that QRM would enhance the effectiveness of the PQS remains a work in progress. This is evidenced by continued drug shortages, with quality problems (with both products, and the processes that manufacture them) identified as the highest contributory factor (5,6).

It is important to realize that effective QRM processes may, on rare occasion, result in unfortunate and unwanted outcomes, such as product quality issues or shortages. In these instances, it is important to demonstrate that the process (of QRM) was applied properly and diligently and that the decisions made were as informed as possible, given what was known or understood at the time. In other words, that the unwanted outcome is not a consequence of a lack of rigor. However, it does not appear that this is an easy matter to demonstrate. Kevin O’Donnell from the Irish Health Products Regulatory Authority (HPRA) noted that pharmaceutical companies “struggle to present evidence that their QRM activities are actually effective” (7). In the same publication, O’Donnell noted that, “While it is clear that the industry has done a lot of work in the area of QRM, it may have reached a plateau in that work, where advances in the area have stagnated to some extent.”

One area of QRM activity that heretofore has not received much attention is that of the decision-making within the process. The authors propose that, perhaps, this is the secret sauce to improve both the process and the output of QRM and address the shortfalls currently observed.

 As products, processes, packaging, and supply chains become more complex both technologically and logistically, the nature and likelihood of hazards, risks, and impacts, also becomes more complex. Most problems encountered in pharmaceutical operations are ‘tame problems’ (i.e., they can be described and resolved with the application of root cause analysis, the right knowledge and expertise, and the appropriate corrective and preventive actions) (8). This is not to imply that these problems are simple—both the problem and the solution can be complicated—but they fit within a ‘cause-and-effect’ paradigm.

Increasingly, however, some problems in modern operations display the characteristics of ‘messy’ or ‘wicked’ problems (9,10). Wicked problems are characterized by multiple contributary causes, with multiple knock-on effects. Consequently, the number and formality of risk analysis also typically increases, as the multiple contributary elements are analyzed. Consequently, the level of formality applied to the decision-making process should also increase. Decision complexity has also been described in terms such as convergent and divergent, where solutions either resolve into one solution or not (11).

It is in these areas of decision complexity, where formality becomes important. Research in the area of decision science informs us that humans, for many reasons, do not perform as rationally as they would like to think when faced with complex decisions (12). This is particularly true when these decisions are about risk and when there is a level of uncertainty involved (13).

Decisions in these contexts are often supported by much data, from multiple sources, a circumstance which humans often find overwhelming. In these cases, the instinct is to reduce the information to more easily interpreted formats such as graphs, charts, or dashboards. However, insights are often lost in these reductive representations.

Alternatively, complex decisions may be required in circumstances where there is little data. It has been established that when information is limited and uncertain, decision-making about risk requires the application of a different logic or mental reasoning, than those used to problem solve many routine PQS decisions (14). Typically, within the PQS, decisions rely heavily on factual evidence; therefore, deductive reasoning is widely used, and the skill of deduction is improved with much practice. However, RBDM requires inductive reasoning, which is called upon less frequently in routine PQS decision making, and therefore is not as well honed. The authors illustrate the two types of reasoning in 

, which shows the comparative characteristics of deductive and inductive reasoning processes (15).

Figure 2: The authors’ illustration of the difference between deductive and inductive reasoning. [Figure courtesy of the authors]

In data-deficient contexts, concern with respect to RBDM accuracy is further complicated when RBDM relies on knowledge acquired from experts via expert opinion (which gives rise to concerns of subjectivity), or from computerized algorithms, search engines, mathematical models, and more recently artificial intelligence (giving rise to concerns of representation), all of which, somewhat counter-intuitively, add to uncertainty rather than resolve it (16,17).

RBDM within QRM requires different mental abilities, which renders it a competency that may not be fully appreciated when important, complex, and uncertain risks are under analysis. Unless the skills are developed and honed, the more typical approaches and modes of reasoning, may overwhelm and mislead the decision-maker.

Why might improving RBDM improve QRM output? It is possible, that by appreciating the skills needed to optimize RBDM, that the quality of the decisions made in QRM might improve, thus improving the output and the effectiveness of QRM in supporting PQS decision-making. O’Donnell also observed that, “The emphasis has probably been more on the mechanics of risk assessment tools/scores rather than on the quality of decisions made based on the outcomes of risk assessments” (7).

As this is one aspect of QRM that has not been discussed and advanced, enhancing RBDM approaches are likely to realize improvement.

ICH Q9(R1) provides a definition of RBDM as, “An approach to, or a process of, making decisions that considers knowledge about risks relevant to the decision and whether risks are at an acceptable level” (4).

To fully understand the nature of a hazard (i.e., how it might arise in the future, and consequently how it might be prevented, mitigated, or controlled), the more complete the knowledge about that risk the better. Therefore, a critical input into a QRM process is knowledge. A supporting knowledge management (KM) process is needed to ensure that accurate and reliable knowledge is available for RBDM within QRM.

 (18) proposed that both QRM and KM were enablers of decision-making processes within the PQS. To date, QRM has probably evolved in organizations more rapidly than its twin enabler KM, Calnan 

 referred to the latter as the ‘orphan enabler’ (19).

 (20) proposed, using a framework referred to as the Risk-Knowledge Infinity (RKI) cycle, illustrated in 

, that these processes are both interdependent and iterative. This interconnection and its importance to QRM was discussed previously by the authors (21). The key takeaway is that robust QRM is founded on the availability of sound scientific knowledge of risk, while the output of QRM further informs the organization’s understanding of risk management and risk control. Both are essential requirements to support the risk-based decision maker (i.e., a strong understanding of the risk and the analysis of those risks).

Figure 3: The Risk-Knowledge Infinity (RKI) cycle proposed by Lipa et al. [Figure courtesy of the authors]

The skill of RBDM is to make good decisions about the control of risk, using what is known about that risk. When much is known, these decisions are not onerous.

However, when knowledge is limited, as is often the case in real-world situations, then RBDM is more uncertain and more challenging. In this circumstance, illustrated in 

, the decision maker has two options. The first is to delay the decision and to seek further knowledge. While this is perhaps the preferred option, it is not always possible. The second option is to improve the capability and accuracy of both the analysis of risk, and RBDM under uncertainty. In this circumstance, reliance on RBDM competencies becomes more critical, as the application of inductive reasoning skills is required.

Figure 4: The reasoning required for risk-based decision-making (RBDM) under uncertainty. [Figure courtesy of the authors]

A focus group, held by the authors in 2022, attended by senior quality professionals from the pharmaceutical industry, confirmed that there was confusion as to where RBDM is performed. The most common perception is that all decisions within the PQS are risk-based decisions, as most, if not all, involved some form of risk. While the underlying premise is true, it is not however an accurate perspective. Neither is it helpful.

If all decision-making processes within the PQS and QRM are considered to be similar, when in fact they are not, it is difficult to develop consistent and informed approaches. Decision types differ with respect to context, values, process, available tools, or as mentioned previously the reasoning, logic, and skills needed. If RBDM is to be improved, then a key starting point must be to recognize where it is occurring and, in that context, focus on its enhancement.

Through researching the term RBDM, and its use and application in other risk-sensitive industries, the authors found that the term RBDM is more commonly used to describe the technical characterization of risk, such as that conducted in the risk analysis phase of the QRM process. The term is used to refer, for example, to the decisions made with respect to risk analysis tools, scoring schema, acceptance criteria, control strategies, and review and monitoring mechanisms. The output of RBDM and QRM (i.e., an understanding of the ‘state-of-control’ with respect to risk) may then be used to inform and support PQS decision making, with the term risk-informed decision-making (RIDM) commonly used to describe this latter context (22).

A more bounded use of the term RBDM, confining it to the decisions made within the QRM process is recommended, thus allowing for the development of best practice, as advised by the revised ICH Q9(R1). Even in this context and within these boundaries, there are multiple decisions made within a single QRM process, and numerous QRM analyses and decisions may combine or compound to control a single product risk. This is particularly true in complex problem settings, with multiple stakeholders, dispersed operations, and long lifecycles. Therefore, even within this narrower interpretation of the term, there is still much complexity and several layers of decision-making.

When should formality be applied to RBDM?

It is clear from ICH Q9(R1) that all risk management decisions should be approached with some level of formality, but that the extent of that formality may vary along a continuum from low to high. As problems increase in complexity, so do the decision-making processes required to support them.

QRM, when performed during a pharmaceutical product lifecycle, can be an elongated process occurring at different times over a long timeframe, by different expert teams, in different operational functions with different geographies, cultures, or ownership. In such long horizon processes, early RBDM (e.g., those associated with the choice of formulation and materials) can be important, complex, and uncertain, and are often made with limited available knowledge. Yet such decisions may commit the entire product lifecycle to irrevocable pathways (i.e., it is difficult to reverse the decisions made). Often such irrevocable decision points limit the choices available to subsequent decision-makers, and thus they should be made with care.

The factors that might drive the process to the higher end of the scale and require higher formality are suggested by the authors as follows:

When the hazard or risk under analysis is important (i.e., has a high potential to impact the quality and/or the availability of the product and ultimately to compromise patient safety).

When the decision is complex due to the technical, logistical, or interdependencies in the risk or system under analysis. Complexity may also be contributed by differing stakeholder preferences or objectives.

When there is limited knowledge of the hazard, how it might arise, how frequently, and/or how it might be effectively controlled, all of which contribute to uncertainty with respect to QRM outcomes.

In cases such as these, higher formality is appropriate and more structured approaches to the RBDM process, such as those illustrated in 

, gives enhanced clarity and transparency into how decisions are made (23).

Figure 5: Authors’ illustration of higher formality applied to risk-based decision-making (RBDM). [Figure courtesy of the authors]

When taking higher formality approaches, ICH Q9(R1) recommends that RBDM be performed by cross functional teams. It is important that the understanding and analysis of risk is developed through the input of diverse views, opinions, and expertise. However, the hazards of multiple viewpoints and group decision-making must also be considered.

Formal and structured decision-making processes and tools attempt to control the challenges of multiple contributions and constrain issues such as subjectivity, biases, heuristics, cultural differences, internal and external politics, power imbalances, and differing priorities, risk tolerances, and acceptance criteria (24). Recognizing the role of the decision-maker and decision-making in the QRM processes ensures that these important steps are performed accurately. ICH Q9(R1) addressed the role of decision-makers, as follows (4):

take responsibility for coordinating quality risk management across various functions and departments of their organization.

assure that a quality risk management process is defined, deployed, and reviewed and that adequate resources and knowledge are available; and

assure that subjectivity in quality risk management activities is managed and minimized, to facilitate scientifically robust risk-based decision-making” (4).

Another consideration when decisions are important is the likelihood that decision-makers are senior in the organization and are not the same people as those performing the risk analysis. This introduces the importance of risk communication in QRM. Visualization and representation of the output of risk analysis, particularly when complex approaches are taken, should be such that the decision-maker is not misled with respect to any uncertainty associated with the analysis or with the output.

This, once again, raises the question of decision-making competency. Returning to the concept that RBDM is reliant on logic and reasoning that differs from other decision-making contexts, an understanding of the underlying skills and knowledge required to develop inductive reasoning and how to apply it to RBDM is warranted. These skills have been identified in order of influence, as numeracy, statistical numeracy, risk literacy, and problem solving (fluid intelligence) (25, 26).

The deductive decision-making approaches that are more typical in PQS decision-making are commonly less reliant on numeracy. Yet numeracy, and a knowledge of statistics, is a key asset in the interpretation of risk analysis, particularly where probability or modeling has been employed. A key argument for confining the concept of RBDM, to within the QRM process, is to develop and target the correct training and to practice RBDM competency to enhance improvement.

A final consideration when considering who performs RBDM is the assumption made in ICH Q9(R1) that decision-making is a human function. This assumption may not completely future proof RBDM. The rate of progress in the areas of data analytics, machine learning, and artificial intelligence is such that future decision-making about risk, particularly with respect to risk control, will be made by computerized agents, or by humans with increased reliance on computerized decision support systems. In these cases, an understanding of the underlying decision-making rules and the reasoning applied within any programs or algorithms used, is also key to accurate outcomes.

The risk analysis may suggest courses of action based on expected value (either cost or quality), as a balance of risk and benefits, or as risk reduction opportunities, expressed with respect to defined thresholds of acceptable risk, or in terms of avoidance of worst-case scenarios, often with little knowledge of the decision-makers preferences or risk tolerance (27). Therefore, the connection, communication, and understanding between the decision-maker and the risk analyst is important to recognize and define, irrespective of whether both are, or either is, human.

With all these considerations in mind, the authors researched RBDM in other sectors. The focus was on industries with high sensitivity to risk (e.g., nuclear, aviation, aerospace, oil and gas, etc.). This research informed the development of 21 attributes of good RBDM. These attributes are illustrated in 

. The attributes were then categorized as the characteristics of good governance and human related factors, of robust QRM, and of knowledge management (28).

Figure 6: 21 attributes of good RBDM, determined from a study of other risk sensitive industries. [Figure courtesy of the authors]

Further research into these attributes will ultimately allow for the development of a guidance or playbook on RBDM, but for now, the following four insights on how to enhance RBDM are emerging:

Decide the appropriate level of formality to support the RBDM.

Provide the best available knowledge to inform and support the decision.

If knowledge is limited, ensure the correct skills are in place to interpret any predictive analysis.

While the first three recommendations have been discussed in previous sections, the recommendation to review RBDM throughout a QRM process has not. However, a ‘lessons learned’ or review process is key to the improvement of any process or system and is an important element of a KM process. Like any skill, RBDM can benefit from the application of hindsight and reflection to determine if, with what was known at the time, the optimal decisions were made. Using this information, the process (of RBDM) can be improved with further enhancements, such as correct information flows, the right decision-makers, different tools, etc.

The concept of applying review node” to ’ process exists in other industries. Commonly at these reviews, the decision-maker determines whether the process has enough information and risk understanding to proceed to the next stage of the process with an acceptable assurance of success. These reviews also facilitate projects proceeding, but with certain ‘liens’ or assumptions, which are highlighted within the action plan for the next phase or phases until they are understood and acceptable.

For any company to improve its own decision-making capability, particularly under uncertainty, the introduction of key decision review points is a worthwhile consideration. The QRM process lends itself to natural pause points. Each review point can have an associated prompt list to assure that the understanding and control of risk is refined through the QRM process, bearing in mind that this may be over a long period of time. The concept of key decision review points is discussed in more detail in a previous publication by the authors (29).

RBDM is distinct from other types of decision-making within a PQS. As decision-making occurs in the context of risk characterization and control, factors such as prediction and probability are inherent. These factors create uncertainty, which is not an optimal context for human decision-making. Therefore, when decisions are important or complex, especially if the problems are messy or wicked, then applying the appropriate formality ensures a rigor to the decision-making process. Training to ensure that the competencies are available also provides greater assurance of successful outcomes. Supporting decision-makers with the correct knowledge is a further enhancement. Finally, reviewing RBDM in the context of QRM processes and outcomes allows for enhancements in future applications, thus fulfilling the opportunities of the RKI cycle.

 (ICH, 2005). https://www.ich.org/page/quality-guidelines

ICH. Final Concept Paper for the ICH Q9 (R1) Quality Risk Management, November 2020. https://www.ich.org

US Senate Committee on Homeland Security & Governmental Affairs. Short Supply: The Health & National Security Risk of Drug Shortages. March 2023.

O’Donnell, K. QRM in the GMP Environment beyond 2020: What Should We Strive For?, in 

An Audience with the International Regulators in the Manufacture of Medicine: QRM and KM

Rittel, H. W. J.; Webber, M. M. Dilemmas in a General Theory of Planning. 

Systems, Messes, and Interactive Planning, in Redesigning the Future

Skaburskis, A. The Origin of ‘Wicked Problems’. Plan. 

 9 (2), pp. 277–280, June 2008, DOI: 10.1080/14649350802041654.

Howard, R. A. Uncertainty about Probability: A Decision Analysis Perspective. 

Mushtaq, F.; Bland, A. R.; Schaefer, A.; Pourtois, G.; Stürmer, B.; and Krebs, R. M.; 

Holland, J. H.; Holyoak, K. J.; Nisbett, R. E.; and Thagard, P. R. Induction: Processes of Inference, Learning, and Discovery, First. MIT Press, 1989.

Hanea, A. M.; Hemming, V.; Nane, G. F. Uncertainty Quantification with Experts: Present Status and Research Needs. 

The Cambridge Handbook of Artificial Intelligence

Calnan, N.; Greene, A.; Kane, P. An Academic Perspective: Knowledge Management: The Orphan Enabler—Enabling ICH Q10 Implementation, in 

A Lifecycle Approach to Knowledge Excellence in the Biopharmaceutical Industry,

 Calnan, N.; Lipa, M. J.; Kane, P.; Cardoso Menezes, J. Eds., CRC Press, 2018, pp. 133–152.

Lipa, M.; O’Donnell, K.; Greene, A. Knowledge as the Currency of Managing Risk: A Novel Framework to Unite Quality Risk Management and Knowledge Management. 

Lipa, M.; Mulholland, V.; Greene, A. (editor). Improving Risk-Based Decision Making (RBDM) Effectiveness Through a Framework which Integrates Knowledge and Risk. 

 16 (2), February, Accessed: Feb. 28, 2022. [Online]. https://arrow.tudublin.ie/level3/vol16/iss2/2

Mulholland, V.; Greene, A.; Lipa, M. J. Steps Beyond Risk Assessment in QRM: RBDM, The Next Horizon. 

Mulholland, V.; Greene, A. Improving Risk-Based Decision Effectiveness: Determining the Level Of Formality. 

 3 (4), Accessed: May 14, 2023. https://kenx.org/kenx_insights/improving-risk-based-decision-making-effectiveness-determining-the-level-of-formality/

Mulholland, V.; Greene, A.; Lipa, M. Improving Risk-Based Decision Effectiveness: Addressing Uncertainty. 

3 (5), Accessed: May 14, 2023. https://kenx.org/kenx_insights/improving-risk-based-decision-making-effectiveness-addressing-uncertainty/

Cokely, E. T.; Ghazal, S.; Galesic, M.; Garcia-Retamero, R., & Schulz, E. How to Measure Risk Comprehension in Educated Samples. In R. Garcia-Retamero & M. Galesic (Eds.), 

Transparent Communication of Risks about Health: Overcoming Cultural Differences

Dieckmann, N. F.; Slovic, P.; Peters, E. M. The Use of Narrative Evidence and Explicit Likelihood by Decisionmakers Varying in Numeracy. 

29 (10), 1473–1488. DOI: 10.1111/J.1539-6924.2009.01279.

It is important to understand the differences between risk-based decision making and other decision making in a pharmaceutical quality system.

Steps Towards Demystifying Risk-Based Decision Making

Cynthia A. Challener is a contributing editor to Pharmaceutical Technology.

Multi-unit pellet systems (MUPS) and intelligently encapsulated mini-tablet systems (EMTS) have unique combinations of advantages compared to conventional oral formulations. The drug release from MUPS and EMTS can be modified by combining pellets or mini tablets with different polymer coatings to achieve the desired profile, allowing modulation of controlled and sustained release. Reduced dose dumping allows for more consistent drug release, lowers risk of gastrointestinal irritations, improves bioavailability, and causes less variation in drug absorption between individuals, which results in improved efficacy with reduced side effects. These strategies also work well with fixed-dose combination (FDC) formulations, allowing controlled release of multiple drug substances, even those that are incompatible with one another, at different rates. MUPS and EMTS even have potential to enable oral formulation of biologics and the formulation of personalized medicines with tailored dosing.

Granules, pellets, and mini tablets (diameter less than three millimeters) are subunits of oral solid dosage forms. They are mixed with excipients and then enclosed within hard gelatin capsules or compressed into tablets. MUPS comprise pellets consolidated into tablets, while EMTS comprise mini tablets encased in capsules. Orodispersible matrices can be used to address swallowing issues. Modification of release profiles is accomplished by coating the individual pellets or mini tablets with functional polymers or other materials. Coatings can also prevent different interactions between incompatible drug substances and provide taste-masking. Dosages are easily adjusted by changing the number of subunits contained in each tablet or capsule.

Therapies on the market formulated as MUPS or EMTS include drugs for problems of the gastrointestinal tract—including gastroesophageal reflux disease, gastric acid-related disorders, and peptic ulcers, high blood pressure, diabetes, and diseases that benefit from targeted delivery strategies, such as ulcerative colitis and gastric, intestinal, duodenal and colon cancers, according to Rao Voleti, senior principal scientist for drug products and pharma services at Thermo Fisher Scientific.

Most of the MUPS/EMTS that treat diseases and conditions related to excessive stomach acid production are based on proton pump inhibitors (PPIs), adds Joao Marcos Assis, global technical marketing manager at BASF Pharma Solutions. He also notes that certain psychiatric conditions, such as depression and anxiety disorders, can be treated with controlled-release MUPS formulations of antidepressant and anxiolytic medications, which provide more stable blood levels of the drug substances for improved symptom management.

Pain management medications and treatments for hormonal disorders and some respiratory conditions (such as asthma, chronic and obstructive pulmonary disease) can also benefit from the sustained-release properties of MUPS/EMTS, according to Assis.

Finally, MUPS and EMTS, observes Voleti, are extremely effective dosage forms for patients with swallowing difficulties (dysphagia) across a variety of therapeutic areas, including cardiovascular, neurological, metabolic disorders, oncology, and more.

A growing percentage of APIs in the development pipeline suffer from poor bioavailability, as well as other issues such as instability, narrow therapeutic ranges, and/or the need for specific release patterns. MUPS and EMTS formulations can help facilitate the delivery of these challenging APIs.

Instability, such as in the case of PPIs when exposed to acidic pH levels, can be overcome because of the protective coatings provided to the pellet or mini-tablet subunits within the formulation. “This approach helps enhance the overall shelf life of the formulation, ensuring the drugs remain stable and effective over time,” says Voleti. Similarly, he adds that multiple APIs can be combined in a single drug product even if they have the potential to interact chemically with one another, because the protective coatings prevent such interactions.

For APIs with narrow therapeutic indices, the ability to modulate release profiles ensures that the concentration of a drug substance is maintained within the desired therapeutic range (above the minimum effective concentration and below the toxic concentration) for a longer duration, ensuring a more effective treatment outcome, Assis comments. That translates to increased efficacy and enhanced safety, which can be difficult to achieve otherwise. MUPS/EMTS also allow for reduction of the high dosing frequencies often required for medications with narrow therapeutic windows, which can contribute to improved patient compliance, Assis adds.

Other drug types for which formulation as MUPS/EMTS leverage sustained release profiles include highly potent therapies and drugs with a short durations of action, according to Assis. The former require precise dosing and careful control of drug concentration, which can be achieved using a drug reservoir system like those found in MUPS/EMTS formulations. For the latter, Assis comments, a drug reservoir system may prolong the therapeutic effect by releasing the drug substance gradually.

In addition to making it possible to incorporate multiple APIs that have the potential to interact with one another, MUPS/EMTS formulations can also accommodate APIs with different solubility profiles, allowing for the formulation of drugs that may have varying bioavailability profiles, Voleti says. MUPS and EMTS are also useful when different release rates are required to meet specific pharmacokinetic profiles. In fact, Voleti notes that combining drugs with variable absorption rates in a single formulation can help achieve a predictable pharmacokinetic profile. Reducing the number of different drugs patients must take can also help boost medication compliance.

Given that MUPS/EMTS contain subunits that must be manufactured and then further processed into the final drug product, their development and production is more complex than those for basic tablets and capsules. Indeed, Voleti points to several technologies that may be used for the development of MUPS/EMTS, including extrusion-spheronization, hot-melt extrusion, spray drying plus compression, mini-tablet compression, drug layering, multi-layer coating, taste-masking, multi-population encapsulation, and others. “The development and commercialization of MUPS and EMTS formulations face several significant challenges for which strategic approaches are required,” he states.

Particular issues that must be addressed, according to Voleti, include ensuring the shelf life and stability of MUPS formulations; maintaining drug-excipient compatibility; preventing moisture ingress, oxidative degradation, and component interactions; achieving particle and functional coating uniformity; navigating and avoiding intellectual property infringement; and adhering to regulatory requirements.

Assis also emphasizes the fact that producing uniform pellets of consistent size, shape, and drug content can be challenging, and coating pellets to provide the desired controlled or delayed-release profiles—as well as doing so in a consistent manner can be complex. “Ensuring an even and consistent coating thickness and uniform coating distribution across all pellets is crucial for consistent drug release and [to] reduce batch-to-batch variability,” he says. That requires determination of optimal coating process parameters, which can be a lengthy effort.

Maintaining the integrity of the coating in subsequent processing steps, such as tableting and encapsulation, is also crucial, because coating damage or breakage can alter the release characteristics. “Since most MUPS comprise pellets with functional coatings, maintaining film elasticity and flexibility is crucial for retaining the intended functionality, and therefore overcoming challenges related to blending and tableting coated pellets is essential to prevent film breakage and segregation issues,” Assis contends.

All of these challenges can be magnified when scaling from the lab to commercial production, Assis adds.

Finally, Voleti points out that there is one key limitation of MUPS and EMTS formulations. “Large doses cannot be accommodated in these forms and may require multiple units for administration, which can impact patient acceptability and compliance,” he explains.

Beyond the challenges to MUPS/ENTS development outlined above, the need to consider several different factors when designing these formulations adds further complexity. The dose; desired release profile(s), including duration of action, lag times in release, and others; physicochemical properties of the APIs involved; the desired shape and size of the particles, which can impact properties processability, uniformity, and release; the manufacturing and filling processes; and the selection of optimum/appropriate coating technologies are examples highlighted by both Voleti and Assis.

The choice of pellets or mini-tablets must also be considered, Assis notes. Mini-tablets are produced using tablet presses with specific punches, which avoids the need for large investments in equipment. Their production involves few processes; they generally require less coating material than pellets; and they have a greater capacity to incorporate active ingredients, according to Assis.

However, due to the size of the punches, the drug and excipient mixture must have high compressibility to mitigate high compression forces, as well as excellent flow to avoid weight and dosage variations, Assis observes. The larger size of mini-tablets also means it can be difficult to incorporate them into tablets, and thus hard gelatin capsules are typically preferred.

Other factors noted by Assis as important to consider during development of MUPS/EMTS formulations include the attributes and proportions of other tablet ingredients and whether taste-masking will be needed. Cushioning excipients in particular, he says, can impact tablet compression, while differences in the particle sizes of these excipients and coated pellets can lead to segregation risks and dose uniformity concerns. “Selecting appropriate diluents (major components of cushioning excipients) and other additives is relevant for successful formulation development of MUPS, especially those containing functional coated pellets,” Assis concludes.

Excipients, in fact, play a crucial role in determining the performance of MUPS/EMTS formulations. In addition to coating materials and cushioning agents, they can include diluents and fillers, binders, surfactants, solubilizers, and stabilizers. “By incorporating these excipients into the formulation, developers can enhance functionality and performance, ensuring optimal drug delivery and stability,” Voleti contends.

It is important to keep in mind, emphasizes Assis, that MUPS and mini tablets require highly compressible and flowable excipients to maintain the film integrity of pellets, reducing compression force and table weight variability.

Diluents and fillers, such as microcrystalline cellulose (MCC), sugar, starch, mannitol, and lactose, are frequently employed to increase the bulk volume of the formulation, while binders such as hydroxypropyl cellulose, hydroxypropyl methyl cellulose, and polyvinyl pyrrolidone are commonly used to improve the cohesion and compressibility of the formulation, according to Voleti.

MCC, observes Assis, is a versatile diluent known for its compressibility, lubrication properties, and low moisture content that is widely used in MUPS, primarily because it presents excellent compressibility properties due to its high plasticity, allowing for easy formation of tablets with high hardness and low friability. “MCC also offers good binding capabilities, yet can help in the disintegration of tablets, ensuring rapid drug release and absorption,” he notes.

Crospovidone (cross-linked polyvinylpyrrolidone) is another excipient highlighted by Assis that has both disintegrant and binding properties, both of which are dependent on particle size. “Smaller crospovidone particles with high surface areas provide high compressibility, improving tablet hardness. Thus, super-fine crospovidone (Type B) is recommended for orodispersible tablets (ODTs),” he says.

Mannitol, meanwhile, is the diluent of choice for ODTs, according to Assis. This sugar alcohol offers high stability, fair compressibility, low hygroscopicity, and pleasant taste. It can act as a bulking agent and contribute to rapid tablet disintegration. Due to its poor binding ability, though, it generally must be used with other functional excipients such as binders and disintegrants.

Of binder options, Assis comments that hydroxypropyl cellulose can be used in tableting as a dry and wet binder at low concentrations (2 to 6 weight/weight %), but at higher concentrations can impact tablet disintegration. Copovidone can be used up to 10 weight/weight % and offers excellent dry binding properties, high plasticity, and low hygroscopicity, according to Assis. “Finer versions with high surface areas and high binding capacities are ideal for MUPS because much less material (1 to 5%) is required,” he comments.

An important trend regarding excipients using MUPS/EMTS formulations is increasing application of coprocessed excipients, which combine two or more excipients without changing their chemical composition but with improvement of physical properties. In addition to improved performance characteristics, coprocessed excipients often provide better processability along with time and cost savings.

“Coprocessed excipients are ideal for MUPS/EMTS formulations because they often exhibit better flow characteristics compared to individual excipients, leading to improved uniformity, reduced risk of segregation during compressing, and enhanced compressibility, allowing for easier tablet formation and better tablet hardness, which results in improved mechanical strength at low compression forces for reduced risk of pellet breakage and tool damage,” explains Assis.

Common coatings include ethyl cellulose, acrylic polymers, hydrophilic polymers, and lipid-based materials, with different grades employed to achieve different modified drug release characteristics, taste-masking, and protective properties, Voleti observes.

Examples of acrylic polymers noted by Assis include methacrylic acid-ethyl acrylate co-polymer (1:1) for film coating to create of enteric pellets, min-tablets, tablets, capsules, granules, and crystals and diethylaminoethyl-methacrylate and methyl methacrylate copolymer for taste-masking. He also highlights polyvinyl acetate plus povidone (polyvinylpyrrolidone) 30, which is available as an aqueous dispersion, for sustained-release formulations. In many coating formulations, Assis also emphasizes the importance of using appropriate plasticizers at the right concentrations for a given polymeric material to maintain flexibility during processing and thus prevent coating damage.

Finally, Voleti cautions that some excipients are to be avoided. They include those with known toxicity and safety concerns, those that are incompatible with the specific API of interest or the chosen manufacturing process, and those known to cause sensitivities for individuals in the target patient population.

In silico solutions accelerate development

Computer algorithms designed to aid formulators in the identification of optimum excipient combinations and concentrations, as well as formats for specific drug substances, are helping to reduce the number of physical experiments that must be conducted, saving time, money, and resources. “By leveraging in silico solutions, researchers and developers can streamline the formulation development process, making it more efficient and effective in creating optimal MUPS and/or EMTS formulations as well as reducing development time and conserving valuable API,” Voleti says.

Tools for accelerating the development of optimal MUPS/EMTS formulations include both computational modeling techniques enabled by artificial intelligence (AI) and machine learning (ML) that help in the design and optimization process, Voleti comments. More specifically, the behavior of excipients, processing parameters, and formulation variables can be predicted computationally, enabling the formulation design to be fine-tuned for optimal performance.

In addition, in silico techniques can be used to simulate drug-release kinetics from MUPS/EMTS, taking into account factors such as composition, environmental conditions, and predicted release profiles, according to Voleti. He points to tools such as GastroPlus (Simulations Plus), which considers the absorption, distribution, metabolism, and excretion characteristics of APIs and formulations, and the AI/ML predictive platform Quadrant 2 (Thermo Fisher Scientific) as valuable for predicting and overcoming solubility and bioavailability challenges.

Accelerated stability and assessment programs, meanwhile, provide the capability to predict stability and degradation pathways and select suitable formulation components and packaging configurations to enhance stability, Voleti observes. Compaction simulation modeling is also used to predict compression/compaction characteristics, ensuring scalability and process reproducibility, which helps to optimize the manufacturing process and shorten tech-transfer times, Voleti adds.

Comprehensive development strategy essential

Given the complexity of MUPS/EMTS formulations and the numerous challenges to realizing effective and optimal products, a strategic approach to their development is essential. Assis recommends a multi-pronged approach that leverages comprehensive pre-formulation characterization, quality-by-design and design-of-experiment (DoE) principles, robust manufacturing processes, coating optimization, and the use of advanced analytical techniques.

“Thorough pre-formulation characterization of the API and excipients is needed to understand their physicochemical properties, compatibility, and potential interactions, while a DoE approach enables systematic evaluation of formulation and process parameters and their impact on pellet/mini-tablet properties and performance in an efficient and targeted manner. That information can be used to implement appropriate process controls and quality assurance measures to minimize batch-to-batch variability and ensure reproducibility,” Assis explains.

Coating optimization is equally important, according to Assis, because it ensures a robust process that results in uniform coating distribution and proper adhesion, which are essential to achieving consistent drug release profiles. Finally, he notes that use of analytical techniques such as near-infrared reflectance and Raman spectroscopy and scanning electron microscopy provides valuable insights into formulation performance and aids in troubleshooting and optimization.

A comprehensive development strategy for MUPS/EMTS formulations should also encompass, says Voleti, the adoption of appropriate scale-up principles to ensure consistent performance and maintain product quality when scaling to commercial production; performance of stability studies to evaluate the chemical, physical, and microbial stability of the formulations; investigation of the intellectual-property landscape to identify potential infringement issues; a robust regulatory strategy that considers regional requirements, intended markets, and product classifications; and implementation of a patient-centric design strategy that includes a thorough literature review and evaluation of formulation excipients, coating materials, polymers, and formulation approaches.

Indeed, patient centricity has become an increasingly important aspect of drug development, as regulatory authorities seek to decrease medication nonadherence through introduction of drug products that consider patient concerns about ease of use, convenience, dosing frequency, and other factors.

MUPS and EMTS are by design patient-centric, says Voleti, as they offer flexibility in developing tailored release profiles to meet specific patient requirements when they are developed as modified-release dosage forms. “These formulations are adaptable to various patient groups, including pediatric, geriatric, and general populations. The flexibility of dosing, taste-masking, and improved palatability attributes all contribute to enhancing patient adherence to their medication regimen[s],” he explains.

Other advantages that MUPS/EMTS formulations offer include increased ease of swallowing and the ability to provide combination therapies through fixed-dose combinations that leverage synergistic effects and minimize the pill burden associated with long-term treatments. They can also be used for oral formulations with special applications, such as gastro-retentive and mucoadhesive therapies, and are readily adapted for alternative routes of administration such as rectal or vaginal, according to Voleti.

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

®
Vol. 48, No. 4
April 2024
Pages: 18–22

When referring to this article, please cite it as Challener, C.A. Development of Mini-Tablet and Multi-Unit Pellet Systems. 

Advanced oral dosage forms allow for modulation of controlled- and sustained-release profiles.

Featured Content

Behind the Headlines Episode 27

Ask the Expert

Drug Digest September 2025

Enhancing Bioanalysis and Drug Development with Advanced Tools and Technologies

Top Trends Reshaping Pharma R&D