Pharmaceutical Technology Is Now PharmTech: A Sharper Name for a Smarter Industry

Navigating FDA Shakeups and Obesity Drug Wars

Behind the Headlines Episode 28

Ask the Expert

Closing the Gap in Modern Process Control and Automation for QC/QA

Drug Digest December 2025

How It Helps Avoid Facility and Equipment Problems

A “Plan, Prevent, Prove” Approach

Raphael Bar, PhD, rbar@netvision.net.il, is a consultant at BR Consulting in Ness Ziona, Israel.

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.

®
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? 

Articles

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?

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On June 10, 2024, FDA’s Center for Drug Evaluation and Research (CDER) announced that it is publishing a notice in the 

 on June 11, 2024 (1) introducing the Emerging Drug Safety Technology Meeting (EDSTM) program. The meetings, which will be administered through CDER’s Emerging Drug Safety Technology Program (EDSTP), will provide those involved in pharmacovigilance activities (e.g., manufacturers, academia, contract research organizations, vendors, software developers) the ability to interact with CDER staff regarding the use of artificial intelligence (AI) in the advancement of pharmacovigilance.

The EDSTM program will facilitate learning and discussion regarding the application of emerging pharmacovigilance technologies and the verification and validation of these models. The EDSTP is a central point of contact for these discussions between industry and FDA that will enable knowledge management and transfer within the agency. EDSTP will also work to understand the scope of the use of AI and other technologies in pharmacovigilance and look for regulatory policies.

“FDA expects increased communication with industry and/or other relevant parties during EDSTMs will accelerate our understanding of how AI-enabled tools are being used for PV, their associated risks and benefits, and barriers to implementation. We encourage interested parties to visit the 

 for more information about the program, including information on eligibility and selection criteria and how to request a meeting,” the agency stated in a press release.

“FDA plans to leverage these learnings to help inform potential regulatory and policy approaches, within the use of emerging technology in PV. The EDSTM program is not an avenue to seek regulatory advice on compliance with pharmacovigilance regulations. Rather, we expect that the information gained during this program will help CDER consider providing regulatory advice on specific technologies to facilitate their adoption when appropriate,” the agency states in the unpublished document (2).

Applicants may request EDSTMs on a rolling basis if they have at least one approved application with CDER, such as a new drug application, abbreviated new drug application, or biologics license application. Other individuals supporting industry pharmacovigilance activities may also request an EDSTM. These EDSTMS will be reviewed quarterly, and CDER will select up to nine participants that meet submission eligibility criteria.

“FDA has a longstanding commitment to ensure medicines marketed in the United States are safe through continued surveillance and research following approval. In the postmarket setting, regulated industry is obligated to review all adverse drug experience information received or otherwise obtained and submit timely reports to FDA,” the agency states in the document (2). “Both industry and regulatory authorities face challenges with timely and efficient collection, processing, and evaluation of single and aggregate patient safety data compounded by ever-increasing case volumes. Advances in emerging technology have the potential to address some of these challenges by creating more efficiencies within a PV system. For example, early adopters of AI are leveraging these emerging technologies to automate fundamental tasks (e.g., adverse event intake, data entry, and processing) with the intention to drive down associated administrative burden and costs. These technologies can also make safety surveillance more efficient and effective by capturing, aggregating, and analyzing larger and more diverse data sets.”

1. FDA. Hearings, Meetings, Proceedings, etc.: Emerging Drug Safety Technology Meetings, Program Announcement. 

https://www.federalregister.gov/public-inspection/2024-12770/hearings-meetings-proceedings-etc-emerging-drug-safety-technology-meetings-program-announcement


2. FDA. Emerging Drug Safety Technology Meetings; Program Announcement. [Docket No. FDA-2024-N-2332]. June 10, 2024. 

https://public-inspection.federalregister.gov/2024-12770.pdf

The new meeting program will create a dialogue around AI and be administered through CDER’s Emerging Drug Safety Technology Program.

CDER Announces Emerging Drug Safety Technology Meeting Program

In early June 2024, FDA and the US Pharmacopeial Convention (USP) both published reports on drug shortages as of the end of 2023. The Center for Drug Evaluation and Research at FDA published its 11th annual report to Congress on drug shortages on June 6, 2024, in which the agency stated it had worked with manufacturers to prevent 236 drug shortages in 2023 (1). According to FDA, drug shortages decreased from 251 in 2011 to 55 in 2023.

“Although the number of new drug shortages has declined since 2011, shortages continue to pose a real challenge to public health, particularly when the shortage involves a critical drug, such as those used to treat cancer, to provide parenteral nutrition, or to address other serious medical conditions,” the agency stated in the Executive Summary of the report.” In the past calendar year, FDA has seen manufacturers in the United States and abroad continue to experience quality issues as well as struggle with capacity constraints. Additionally, as demand increased for numerous drugs over the last several years as a result of the COVID-19 pandemic, the flu season, and the respiratory virus season, FDA has seen further strain on drug availability and the pharmaceutical supply chain.”

The USP report released on June 4, 2024, 

USP Annual Drug Shortages Report: Economic Factors Underpin 2023 Shortages, 

includes drug shortage trends up to the end of 2023 in the US (2). These trends were based on use of USP’s Medicine Supply Man tool, which uses artificial intelligence and predictive analytics to predict supply chain risks. One such trend found by USP is that shortages are lasting more than three years compared to two years in 2020. Shortages are also impacting a variety of therapeutic classes with 53% being new generic sterile injectable drugs. 

According to the USP report, the supply of a medicine is at risk when one or more of the following factors are in play: low prices, complexity of manufacture, geographic concentration, and quality problems. Drugs with lower prices had an increased discontinuation rate of 40% in 2023 for one year. Sterile injectable drugs that were in shortage were almost 8.5 times lower in price than those not in shortage.

Sterile injectables also have a higher manufacturing complexity, making them even more vulnerable to shortages. Antibiotics, which sometimes require separate dedicated facilities, and APIs that require complex chemical synthesis are also at risk.

Limited locations for API and finished dosage production also contribute to shortages according to USP, but it is quality concerns that can plague manufacturers the most. When regulators discover quality problems at facility inspections or a recall must be made, manufacturers must inform regulators of the possibility of a shortage that may result from these quality control actions. “Quality comes at a price,” said Vimala Raghavendran, vice president for Informatics Product Development at USP, in a press release (3). “The economics of generic drugs often leave manufacturers with razor-thin margins, making it challenging to prioritize investment in modern machinery or to elevate standards of quality. Without sufficient profitability, the cycle of innovation and improvement becomes difficult to sustain.”

“As we navigate the complex landscape of drug shortages, it is paramount to shift the market into a stable state,” said Anthony Lakavage, senior vice-president for Global External Affairs at USP. “Economic pressures, especially the very low prices that generics manufacturers recover for many medicines, along with contracts that are frequently broken, have left our generic medicine supply chain fragile. Unexpected shocks can break the system and disrupt the supply of quality medicines. This worrisome trajectory leads to more frequent drug shortages, prolonged scarcity, and more people at risk of not getting the medicines they need, when they need them.”

Report to Congress. Drug Shortages CY 2023

https://www.fda.gov/media/179156/download

 USP Annual Drug Shortages Report: Economic Factors Underpin 2023 Shortages. USP.org

. June 2024.
3. USP. U.S. Drug Shortages Reach Decade-high and Last Longer. Press Release, June 4, 2024. https://www.usp.org/news/us-drug-shortages-reach-decade-high-and-last-longer

USP and FDA publish reports detailing drug shortage numbers and challenges through 2023.

Drug Shortage Reports Emphasize Continuing Problems

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

AI-Enhanced Medicine Pill Concept for Future Healthcare. Pill symbolizing integration of artificial intelligence in the development of future healthcare and advanced treatments | Image Credit: ©PSCL RDL- stock.adobe.com

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. 

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

Using Advanced Algorithms to Solve Formulation Challenges

Feliza Mirasol is the science editor for 

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). 

Editor’s note: this article was published in the Pharmaceutical Technology Europe June 2024 issue.

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

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. 

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

Evaluating the Use of Continuous Chromatography

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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 

Lonza’s Joe Garrity and Jerry Jiang discuss the importance of not only automating CGT manufacturing, but also standardizing across processes.

The Need for Automated and Standardized CGT Manufacturing (BIO 2024)

While cell and gene therapy (CGT) manufacturing must remain flexible out of necessity, it is also important to standardize processes at an industry level while establishing aseptic-friendly automated operations. Standardization, in particular, is important from a scaling perspective, says Joe Garrity, senior director and head of Autologous Cell Therapy, Lonza.

During BIO 2024, Garrity pointed out the many challenges incurred on the cell therapy side. “It stems from supply chain to operations to clinical sites. There's just so much that needs to go into, specifically, autologous cell therapies, with the batch quantities going into the hundreds and thousands that we're seeing from some of [the] large drug developers.” Thus, he says, standardizing the manufacturing process allows for robustness and process control across the board.

Garrity also notes, however, that even with standardization, “it's not a one size fits all”. Instead, he says, “[much of the time,] it's a little bit of a one size fits most, and you're going to have to be relatively variable, but in the end, the overall standardization of the manufacturing process and the intent of that remains the same because it's better control at scale. Once you find something that really funnels that process robustness and that scalability, you … stick with it so it's reproducible time and time again.”

In discussing whether it’s possible to have manufacturing processes that are both standardized and flexible, Jerry Jiang, clinical application specialist, Personalized Medicine, Cell and Gene Therapy, Lonza, says, “Definitely. One of the things that we really have to start standardizing is the release criteria and the quality of the cells that are being put into the patients. [The] material that comes in is going to be different, but standardizing what we expect the cells to do and behave and what they look like is going to be a huge part of what the standardization process needs to overcome right now.” However, flexibility remains in the details. “[T]he standardization is the same, but the flexibility of the process allows these different companies to optimize the process with their ‘secret sauce’ that will really differentiate their treatment from all the other treatments out there,” says Jiang.

“We definitely need to standardize the way we are inspecting and checking the cells before it goes into a patient, but the flexibility allows each company to … show off their technology and allow for them to shine with the advancements that they've made,” Jiang adds.

Click above to view the full interview. BIO 2024 occurred on June 3–6 in San Diego, Calif.

Lonza’s Joe Garrity and Jerry Jiang discuss the latest trends and challenges in commercializing new CGTs. 

Trends and Obstacles in the CGT Field (BIO 2024)

Cell and gene therapies (CGTs) remain an important focus in the biopharma industry. During BIO 2024, Joe Garrity, senior director and head of Autologous Cell Therapy, and Jerry Jiang, clinical application specialist, Personalized Medicine, Cell and Gene Therapy, both at Lonza, discuss the latest trends and hurdles in the CGT space.

“Moving from the 2017 timeframe into 2020, we saw a heavy focus on a [significant amount of] money floating around focusing on autologous cell therapies and how we can better provide these life changing therapies to patients,” Garrity says. From the autologous cell therapy perspective, efficacy has been achieved, but the challenge remains that an autologous cell therapy is one manufacturing batch, or one dose, per patient. “The scaling is a little bit of a challenge,” Garrity says, noting, “This is where the allogeneic approach has taken over, and in the cell therapy space, we've really seen that shift … seen [focus] go from two-thirds autologous to one-third allogeneic to almost a 50/50 split.”

Garrity expects this trend to continue to where the industry may see a rise in allogeneic cell therapies, from a molecule number standpoint. “We're seeing a [bigger] influx of allogeneic cell therapies trying to provide a secondary option to commercially viable CAR-T [chimeric antigen receptor T cell]/CAR-NK [chimeric antigen receptor natural killer cell] drug products,” he states.

“At the end of the day it’s really about providing access and availability of cell therapies to those who really need it,” Jiang adds. “The cell therapy production process can be complex, and current solutions are not sufficient to be able to scale to the patient demand. So, as a result, new technologies are being developed to help reduce timelines and cost and improve scalability.”

Another issue Jiang points out is the difficulty in finding technicians who are able to work with and produce these therapies. “We've seen [many] different manufacturers try to figure out different ways of scaling down … either making the process faster or taking out other aspects of their manufacturing process to really streamline this process, as well as just reducing the costs [of these] therapies.”

Click the video above for the full interview. BIO 2024 occurred on June 3–6 in San Diego, Calif.

industry experts discuss the current outsourcing landscape in the post-COVID world 

Changes and Trends in the Outsourcing Landscape

The outsourcing landscape has seen many changes in recent years coming out of the COVID pandemic. Driven by a burgeoning pipeline of clinical-phase therapeutic candidates and the practical need for more advanced analytics, the contract services industry is hustling to meet the expected growth of new, more complex therapeutics to hit the market over the next decade. In this episode of 

 Video series, industry experts discuss the current outsourcing landscape in the post-COVID world and the changes the pandemic has enforced in the demand for outsourced bioprocessing services.

Eric S. Langer, president and managing partner, BioPlan Associates

Eric S. Langer has over 25 years experience in life sciences market assessment, valuation, marketing, management, and publishing. He been senior manager at biopharmaceutical supply companies and is an experienced biotechnology strategist. His team has advised hundreds of companies on marketing strategy development, valuation, pricing, and message strategy. Langer has also developed strategic plans based on quantitative analysis of market trends and buyer needs in valuation services, pricing, and analysis. He teaches graduate biotechnology marketing at Johns Hopkins University and biomedical valuation to the National Institutes of Health Graduate School

Jordi Robinson, chief commercial officer, Navin Molecular

Jordi Robinson has nearly 30 years of experience in the pharma and specialty chemicals industries, and is currently chief commercial officer at Navin Molecular, with responsibilities for all customer-facing activities, including business development and project management. Prior to joining Navin Molecular, he worked for six and a half years leading the European business development team for global contract development and manufacturing organization, Asymchem Laboratories, and has also held commercial and technical roles at Robinson Brothers and Endeavour Speciality Chemicals. He has a bachelor’s degree in chemistry from the University of Central Lancashire, UK.

Drug Digest is a tech talk video series with the 

® editors, who interview industry experts to discuss the emerging opportunities, obstacles, and advances in the pharmaceutical and biopharmaceutical industry for the research, development, formulation, analysis, upstream and downstream processing, manufacturing, supply chain, and packaging of drug products.

Biopharma Drug Development and Manufacturing

Videos

In this episode of Drug Digest, industry experts discuss the current outsourcing landscape in the post-COVID world and the changes the pandemic has enforced in the demand for outsourced bioprocessing services. 

Drug Digest: Changes and Trends in the Outsourcing Landscape

Lars Petersen, CEO, FUJIFILM Diosynth Biotechnologies discusses the company’s strategic goals and meeting market demand for mammalian cell culture capacity.

Demand Remains Strong for Mammalian Cell Culture Capacity (BIO 2024)

Demand for mammalian cell culture capacity remains strong and is growing, notes Lars Petersen, CEO of FUJIFILM Diosynth Biotechnologies, during BIO 2024. The company’s main strategic goals for this year centers around meeting this demand. “We are starting up a facility right now in Denmark (1), which is maybe the highest priority,” Petersen says, who also emphasizes that the company has “multiple CAPEX [capital expenditures] projects that we need to finish up.”

“In general, we are we shifting the business after COVID, after some of the financial challenges, to [focus on] what demand is most important … and we see a lot of new interest coming in. Being ready for that [demand] … is the most significant goal of the year,” Petersen says.

As for the company’s expansion of its Holly Springs, N.C., mammalian cell culture facility (2), Petersen explains that this expansion “has really been driven by demand … Demand is high.”

The market for mammalian cell culture needs more capacity, according to Petersen. “There's so much volatility shift and demand from new products coming in, shifting the market from innovators to CDMOs [contract development and manufacturing organizations] [for] new modalities [in treating diseases] like Alzheimer's. The pressure is on [for] other modalities that all end up with higher demand,” he says.

In terms of the future of therapeutic modalities, Petersen sees antibody drug conjugates making a comeback after about a decade and, conversely, a bit of slowdown in messenger RNA. “All these modalities, they really are difficult to foresee,” he observes. However, he expects that monoclonal antibodies will remain a major therapeutic modality for potentially the next 10–15 years, at least.

Click the video above for the full interview. BIO 2024 is being held in San Diego, Calif., on June 3–6.

1. FUJIFILM Diosynth Biotechnologies. FUJIFILM Diosynth Biotechnologies Breaks Ground For Major Expansion of Its Large Scale Biologics Production Facility in Denmark. Press Release, March 3, 2021.
2. FUJIFILM. FUJIFILM to Invest Additional $1.2 Billion to Expand its Large-Scale Cell Culture CDMO Business in North Carolina. Press Release, April 11, 2024.