Behind the Headlines Episode 27

Ask the Expert

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

Drug Digest September 2025

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Top Trends Reshaping Pharma R&D

Feliza Mirasol is the science editor for 

The opening of a new solutions center in Bengaluru, India, by Illumina, a US-based company specializing in DNA sequencing and array-based technologies, in August 2023 not only expands Illumina’s capabilities in genomics, but also expands access to genomics in that country.

The new center houses a fully equipped laboratory with the latest next-generation sequencing and array technologies. It is also fully resourced with field applications and service engineers that can offer broad genomics capabilities. The center will also provide training and education to increase technical expertise and access to genomics locally.

The new center is a permanent facility on the ground in Bengaluru for Illumina, which has spent the past 16 years working in partnership with Premas Life Sciences, an India-based contract research organization and provider of niche technologies in genomics, cell biology, and biopharma. With the help of the new solutions center, Illumina will continue collaborative work with Premas to grow the genomics market in India, according to an Aug. 17, 2023 company press release.

"Expanding Illumina's presence in India allows the company to collaborate and be part of a vibrant biotech ecosystem with skilled labor, strong research and development resources, and supportive government policies," said Gretchen Weightman, senior vice-president, Asia Pacific, Middle East & Africa, Illumina, in the company press release. "In our 25th anniversary year, it's a very exciting time to be growing our physical presence in India to drive access and the further adoption of genomics to transform human health, particularly in oncology and infectious disease."

Illumina’s business in India is led by Abhishek Gupta, country manager, and, according to Weightman in the press release, "Abhishek brings vast knowledge and experience to Illumina India, and we look forward to supporting him and the team as they collaborate with and support our customers." said Weightman.

The new solutions center also presents the opportunity to pursue equitable access and more diverse data in India. "Democratizing genomics and making it available to the many and not just the few will take a collaborative approach. We must better reflect diversity in genomic data and drive awareness for, access to, and adoption of genomic technologies, through partnership," Weightman said in the release.

Articles

Illumina’s new solutions center in Bengaluru, India, will expand access to genomics in the country.

Illumina Establishes New Center in India to Expand Genomics Capabilities

Optibrium announced on Aug. 31, 2023 the acquisition of BioPharmics to further expand the 3D drug design and modelling offering and to focus on research and development and application science, according to the press release.

BioPharmics developed a series of industry-leading algorithms and software for 3D ligand-based and structure based computational drug design, including software for 2D to 3D ligand conversion and conformer generation, molecular docking, molecular similarity, and binding affinity prediction. Additionally, these highly performant products have all been analyzed and their results demonstrated in numerous peer-reviewed papers, specifically published jointly with key pharmaceutical industry partners, according to the release.

“After years of close collaboration, we are delighted that Optibrium was chosen to support BioPharmics’ continued scientific innovation and expanding customer base,” said Dr Matthew Segall, CEO, Optibrium in a press release. “We are delighted to welcome Ajay and Ann to the team. Their extensive experience in computational chemistry and biology, alongside BioPharmics’ world-leading software for 3D ligand- and structure-based design, will bring Optibrium to the forefront of these essential technologies for small molecule discovery and design.”

Dr Ajay Jain, founder and CEO of BioPharmics, added that their team believes that there is no better team to continue the powerful software developments that BioPharmics has introduced over the years. “I look forward to working as part of the Optibrium team to expand their internal expertise in 3D drug design, as well as on future drug discovery innovations,” he said in a press release.

Optibrium announced on Aug. 31, 2023 the acquisition of BioPharmics to further expand the 3D drug design and modelling offering and to focus on research and development and application science.

Optibrium Acquires BioPharmics

Analytical testing forms a vital part of the development lifecycle of bio/pharmaceutical drugs as it provides assurances of the safety and effectiveness of the products prior to patient use. As industry focuses on more complex molecules, growth within the analytical testing services sector is inevitable. In fact, according to recent market research, the sector is expected to experience compound annual growth of 11.4% between 2022 and 2027 (1), largely driven by the swell of biologics and biosimilars in development.

Another aspect altering the analytical testing landscape has been the COVID-19 pandemic, which significantly boosted demand for clinical services as numerous companies raced to develop safe and effective vaccines and medicines to treat the disease.

Since the start of the COVID-19 pandemic, there has been a greater level of investment into analytical testing and services, points out Kishore Hotha, vice president, Global Head of Analytical Research & Development at Veranova.

“The shift to remote work has also impacted the industry, prompting the development of remote analytical testing technologies to support remote operations,” Hotha adds. “Moreover, the pandemic has accelerated the utilization of artificial intelligence (AI) and machine learning (ML) in analytical testing. These technologies offer automation, improved accuracy, and efficiency in testing processes while enabling the identification of potential drug-related issues. Additionally, there has been a heightened emphasis on personalized medicine, which involves tailoring drugs and treatments to an individual’s genetic makeup and medical history.”

In terms of identifying genetic markers associated with diseases and targeted therapies, Hotha feels the changes should persist in the post-pandemic era, as the pharmaceutical industry develops novel drugs and treatments to address unmet patient needs. “Overall, the COVID-19 pandemic has therefore catalyzed advancements in analytical testing, promoting innovation and enhancing the industry’s ability to deliver safe and effective pharmaceutical solutions,” he says.

A prime example of innovation that is helping to expedite testing processes is the rising use of robotics and AI, according to Hotha. These kinds of technological advances benefit both the patient and the pharmaceutical company when utilized properly.

“Labs are implementing new processes in analytical drug testing to enhance safety, efficacy, and efficiency. These include using robotics for automated tasks, cloud-based data storage and analysis, AI, and machine learning (ML), and personalized medicine approaches,” Hotha says. “Robotic systems automate tasks like pipetting and centrifugation, improving accuracy, efficiency, and cost-effectiveness. Cloud-based systems enable seamless data sharing and collaboration, enhancing testing accuracy and efficiency while facilitating the development of novel methods. AI and ML aid in developing new testing techniques, identifying potential drug issues, and improving result interpretation.”

In the case of personalized medicine, testing needs to be individualized to the patient, taking into account genetic makeup and medical history, specifies Hotha. “[Automated] processes foster safer and more efficient drug development, making testing more affordable and accessible. Labs can accelerate testing, improve accuracy, and reduce costs by leveraging automation, data-driven analysis, and tailored approaches,” he emphasizes.

Efficiency: cost versus development time?

For Hotha, analytical drug testing services continue to be highly beneficial for pharma companies, particularly in the face of emerging trends in the industry. He explains that the increasing demand for personalized medicine, which focuses on tailoring drugs and treatments to individual patients based on their genetic makeup and medical history, has created a significant need for robust analytical testing.

“These services play a crucial role in identifying genetic markers associated with various diseases, enabling the development of targeted therapies,” Hotha comments. “Furthermore, there is a growing emphasis on safety and efficacy in drug development. Analytical drug testing services ensure that drugs are safe and effective before administering them to patients. They help assess pharmaceutical products’ quality, purity, and stability, ensuring that they meet regulatory standards and minimize potential risks.”

In addition, researchers are working on treatments for more intricate diseases, which is leading to an increasingly complex drug development landscape, Hotha continues. “Analytical drug testing services play a vital role in unraveling the complex mechanisms underlying these diseases and aiding in developing effective treatments. Through advanced analytical techniques and data-driven approaches, these services enable scientists to gain insights into the intricate aspects of drug behavior and optimize their therapeutic interventions,” he says. “Analytical drug testing services remain indispensable for pharma companies to develop high-quality, targeted therapies that meet the evolving needs of patients and regulatory requirements.”

Contract development manufacturing organizations (CDMOs) and contract manufacturing organizations (CMOs) are a major component to vaccine and therapy development, as well as fill/finish operations, toxicity testing, and cost control. In terms of analytical testing, CDMOs/CMOs are hoping to enhance their testing services and make the changes necessary to do so, according to Hotha.

Hotha points out that there are some fundamental approaches to improve efficiency, accuracy, and customer satisfaction, including investment in advanced technologies, expanded testing capabilities, focus on quality systems and compliance, and collaboration/partnerships. For example, expanded testing capabilities hope to cater to broader client needs, he reveals.

In terms of collaboration and partnerships, Hotha adds that specialized testing laboratories collaborate well with CDMOs/CMOs. “Collaborations enable CDMOs/CMOs to offer comprehensive solutions and access a broader range of testing services, contributing to their competitiveness,” he says.

“Success for CDMOs/CMOs in the testing services realm is achieved through a combination of factors,” Hotha continues. “A robust infrastructure, skilled personnel, adherence to strict quality standards, and customer-centricity are critical. CDMOs/CMOs consistently deliver high-quality testing services within defined timelines and budgets and tend to excel in the industry. Flexibility and adaptability in tailoring testing services to meet specific client requirements are highly valued. These strategic initiatives enable them to provide comprehensive, reliable, and customer-centric testing services, positioning them as preferred partners in the pharmaceutical industry to transform molecules into medicines.”

Testing can differ depending on the size of the molecule and the phase of development. The variances may also be based on the drug’s nature, therapeutic area, regulatory guidelines, and individual company strategies. Therefore, flexibility and adaptability in testing methodologies are critical to meet the specific needs of different molecules and development stages.

Large-molecule testing, involving biologics like proteins and antibodies, present more complex challenges than small-molecule testing, according to Hotha. “Large-molecule analysis requires specialized techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy for structure and composition identification. Sample preparation for large molecules is more challenging due to their instability and susceptibility to degradation, necessitating specific preservation methods. Data analysis for large-molecule testing is also more intricate, as these molecules often have multiple subunits with varying biological activities,” he explains.

As for early phase versus late-phase development, Hotha emphasizes how different the testing requirements can be in each phase. “In early-phase development, the focus is on safety, toxicity, and dosage optimization. Analytical methods concentrate on identifying and characterizing drug candidates, stability assessments, and early safety evaluations using qualified analytical test methods with minimum requirements,” he adds. “Late-phase development involves comprehensive testing to meet regulatory safety, efficacy, and quality standards. This includes extensive validation, impurity profiling, stability studies, and method transfer/validation for commercial production.”

The future of analytical drug testing services

In Hotha’s opinion, the future of testing services holds significant promise for the pharmaceutical industry, with new analytical methods of technologies and more collaborations among analytical testing labs with other stakeholders and pharmaceutical companies to further improve the accuracy, efficiency, and reliability of drug testing. “Improvements in technology, automation, and data analytics will enhance the speed and precision of testing processes, leading to quicker turnaround times for results and faster decision-making in drug development,” he summarizes. “Integrating advanced analytical techniques such as mass spectrometry, high-throughput screening, genomic analysis, and imaging will provide a comprehensive understanding of drug properties and mechanisms of action. This knowledge can drive the discovery of new therapies and the optimization of drug formulations.”

Healthcare Analytical Testing Services Market by Type (Biomarker Testing, Stability Testing, Raw Material Testing, Batch-Release Testing, Cleaning Validation), End User (Pharmaceutical Companies, Medical Device Companies, CRO), and Region—Global Forecast to 2027

The focus in labs is leaning more heavily toward automated processes while at the same time maintaining efficiency, safety, and a personalized experience for the lab worker.

The Changing Analytical Landscape

ten23 health, a contract development and manufacturing organization (CDMO), announced a capacity expansion for the manufacture of sterile drug product at its Visp facility, according to a press release.

Due to customer demand for sterile fill and finish services, the expansion will head to VIVA 1, Visp Valais, Switzerland, at a sterile manufacturing facility. Following successful completion of the GMP inspection by Swissmedic and an obtained GMP license, the new storage areas are set to become operational in September 2023. Additionally, the output of ten23’s existing sterile manufacturing facility in Visp will be gradually increased by a further 50% capacity by hiring more staff to operate an additional shift.

According to the press release, further expansions of the pharmaceutical development and manufacturing services of ten23 are happening at the BASE and VIVA facilities to continue to support complex sterile product development, testing, and manufacturing. Two additional filling lines for sterile commercial supplies of ready-to-use syringes, cartridges, and vials and liquid or freeze-dried clinical and commercial vial supplies will all be a part of VIVA 2. This project is signed for manufacturing in 2024 and 2025.

“We are thrilled to offer our customers additional sterile manufacturing capacity for sophisticated and highly precise Drug Product-presentations such as syringes and cartridges, increased capacity until the two new production lines becoming fully operational.” said Professor Hanns-Christian Mahler, PhD, CEO of ten23 health, in a press release. “With recent demand increases for clinical as well as commercial drug launches, our customers are keen to take advantage of increased capacity from the existing VIVA 1® facility, before the new plant VIVA 2® will be utilized for larger scales.”

Further expansions of the pharmaceutical development and manufacturing services of ten23 are happening at the BASE and VIVA facilities to continue to support complex sterile product development, testing, and manufacturing. 

ten23 Expands Sterile Manufacturing Capacity at VIVA 1 Facility 

In today’s biologics/contract research organization (CRO) labs, more data than ever are being generated on protein characterization, thanks to advanced and more thorough analytical technologies. Managing these volumes of data, especially in the clinical phases of drug development, has become a real challenge for researchers.

Clinical trial data are at the heart of how biopharma companies develop new therapeutics for commercial launch, but developing a new drug and bringing it to market can take a decade or more and cost upwards of a billion dollars (1). Outsourcing clinical trial services has become a common practice to save a biopharma company on cost and time, but the practice brings up risks in data transfer as well as data management.

Laboratory issues can result in a delay of data receipt as well as poor quality of data, which can lead to rejection or rework. Data entry issues, delays in responses to data queries, errors during data transfer and merger, and discrepancies due to poor database setup can all also be the cause of delays (1).

A discussion with David Hardy, PhD, senior manager, Data Analytics and AI Enablement, Digital Science Solutions, Thermo Fisher Scientific, explores best practices for how to approach data management in today’s biopharmaceutical lab and highlights some effective strategies for distilling meaningful interpretation from these data.

 Although solutions such as laboratory information management systems (LIMS) and the electronic lab notebook (ELN) have helped to address the vast amounts of data being generated in biologics/CRO labs, what are the biggest challenges facing LIMS and ELN?

 The biggest challenge when it comes to LIMS and ELNs is ensuring that these systems fit seamlessly into laboratory processes to make sure they are used throughout an organization, at which point they can be better used to unlock deeper data-driven insights. Usability can also be a challenge of many LIMS and ELN solutions, but it is critical for company-wide, successful adoption.

Another important challenge is that, while LIMS and ELN can help ensure data quality after data capture, they can do little to rectify errors made through poor quality input data. To help improve data quality at the point of data generation, labs should seek to use automation wherever possible.

 Do automation and digitalization truly offer solutions that allow scientists to analyze these data in a meaningful way, or are there as much cons as there are pros to using such advanced technologies for the data scientist?

 The pros and cons of using automation and digitalization tools to analyze large amounts of data are the same across all applications, including biologics. For example, biologics labs still need to conduct initial validation of their tools and constantly check them, requiring close collaboration between the laboratory and data scientists. However, over time, the pros of advanced digitalization and automation tools—greater accuracy, reproducibility, efficiency, and deeper insight—vastly outweigh any initial cons.

Importantly, even with advanced technologies, scientists face the hurdle of understanding their data and which data fields to use. Then, they need to be clear on which model best suits the problem they’re trying to solve. This isn’t always easy but analytics solutions are striving to make this simpler.

 How has the user (i.e., the scientists) experience been affected or changed by the amount and quality of data being generated and the ability to manage that data?

 By their nature, scientists are data savvy. However, with the sheer amount of data that labs generate, as well as the need to manage these data with advanced technologies, scientists have had to become more tech savvy. For example, most scientists have the knowledge and skills to check and analyze their data using languages such as R, Python, and tools such as KNIME [Konstanz Information Miner]. Given the growing importance of these skills, they are now widely taught to undergraduate students.

Scientists have also embraced ‘big data,’ adopting new technologies to such an extent that big data isn’t the obstacle it once was. Given the increasing importance of technology in handling and processing such data, scientists now commonly work alongside their data science, IT [information technology], and TechOps [technical operations] colleagues to find the optimum and most cost-effective solution, which was less common in the past.

Beyond data capture, storage, and analysis, labs increasingly need to be able to use their data to their full potential. Accordingly, we’ve seen scientists increasingly focus on the FAIR (findable, accessible, interoperable, and reusable) data principles. Data [are] only truly useful if [they meet] these requirements.

 What would you say are some key best practice habits or techniques that scientists can employ to managing these data?

 Scientists can—and should—do several things to maximize their ability to manage these data. First, they should embrace automation, as it’s a scientist’s best friend. With more automation, scientists get free time to focus on more important, value-adding activities.

Scientists should also keep in mind that managing all of these data is a team sport. Data Science, IT, and TechOps teams are there to help, so scientists should leverage their expertise and support to maximize their chances of overcoming data challenges.

Finally, scientists should keep up to date on the latest technologies for managing and analyzing data—the field is advancing very rapidly, and taking your eye off the ball, even briefly, can lead to missed opportunities.

 What are some effective strategies that scientists can use to ensure that they are processing quality lab data and not just noise (are there such strategies)?

 As the saying goes, ‘garbage in, garbage out.’ That is to say that the root of good quality data is good input—good experiment design followed by good execution. Scientists can achieve these in several ways.

For example, they can adopt electronic tools such as laboratory execution systems (LES), which help by ensuring scientists follow methods and procedures correctly. LES and LIMS can also flag anomalous result values that fall outside a given specification range, helping to ensure data quality.

Scientists should also look to adopt artificial intelligence (AI) technologies, as they can greatly help in improving data quality. But this doesn’t have to be an overwhelming task. It can help to start with a small project and build from there. For example, a lab might start by using an AI-based approach to identify systematic errors, before gradually expanding its remit and functionality. It’s important to engage the data science team early and draw on their experience as you embark on this new and exciting journey.

1. Johnson, J.; Kanagali, V.; Prabu, D. Third Party Laboratory Data Management: Perspective with Respect to Clinical Data Management. 

 (1), 41–44. DOI: 10.4103/2229-3485.124573

Advanced analytical tools generate more data in today’s labs than ever before.

Dealing with Data: How to Keep It Manageable

On Aug. 28, 2023, Embark Laboratories announced it has been acquired by Novo Nordisk, including its lead metabolic program, in addition to entering a three-year research and development collaboration to discover and develop novel pharmaceuticals to treat obesity and related comorbidities, according to the press release.

Under the acquisition agreement for Embark Biotech, Novo Nordisk receives the full rights to develop and commercialize the lead program. Additionally, the research and development collaboration with Embark Laboratories provides Novo Nordisk with the option to acquire selected assets based on the Embark Biotech findings across several indications, including obesity and type 2 diabetes, according to the release.

“Novo Nordisk has been engaged in obesity research for 25 years, and we continuously search for new ways to address this serious chronic disease. We are excited about the opportunity to advance Embark Biotech’s lead program and look forward to co-creating novel treatments for cardiometabolic diseases with Embark Laboratories to complement our in-house R&D,” said Brian Finan, vice president of Obesity Research at Novo Nordisk, in a press release.

“There is a clear strategic fit between the novel biology we have discovered and Novo Nordisk’s expertise and focus on developing new drugs in the cardiometabolic space. We are thrilled to pass on the baton for our lead metabolic program to Novo Nordisk. This deal and Embark’s success are direct outcomes of the unique and innovative ecosystem in Denmark that has been cultivated by the BioInnovation Institute and the University of Copenhagen and through initiatives from the Novo Nordisk Foundation and the Innovation Fund Denmark,” said Zach Gerhart-Hines, chief technology officer at Embark Laboratories in the release.

Novo Nordisk receives the full rights to develop and commercialize the lead program. 

Novo Nordisk Acquires Embark Biotech

Zevra Therapeutics and Acer Therapeutics announced on Aug. 31, 2023 that they have entered a definitive agreement where Zevra would acquire Acer in a merger transaction having a total potential value for Acer stockholders of up to $91 million, according to a press release.

Additionally, additional cash payments are possible in relation to the Contingent Value Rights with respect to milestones involving Acer’s early-stage program ACER-2820 (emetine). Zevra also purchased Acer’s secured debt at a discount from Nantahala Capital through a series of transactions in capital efficient structure, according to the release. Both companies have a focus to developing and commercializing treatments for rare diseases with a strong focus on patients and supporting communities with little to no existing therapeutic options.

“We believe that Acer’s portfolio of rare disease programs, including the recent US commercial approval of OLPRUVA for urea cycle disorders UCDs, is a perfect strategic fit for Zevra and creates significant opportunity for us to positively impact patient lives while creating shareholder value,” said Joshua Schafer, chief commercialization officer and executive vice president of Business Development of Zevra Therapeutics, in a press release. “We are excited about Acer’s clinical programs and are confident in the potential of OLPRUVA to bring UCD patients a more convenient and cost-effective treatment option over current therapies. Acer would bring unique rare disease operations and capabilities that would serve as a foundation to support the commercialization of Zevra’s pipeline as it advances.”

“This merger would support Zevra's vision of becoming a leading rare disease company bringing life-changing therapies to patients with a significant unmet need,” said Christal Mickle, Zevra’s interim chief executive officer and chief development officer in the press release. “The commercial launch of OLPRUVA in the US requires a small, highly-focused commercial team, which is complementary to what we intend to build for arimoclomol, our product candidate for the treatment of Niemann-Pick disease Type C (NPC). We believe there is potential to realize significant synergies across our commercial organizations as both UCDs and NPC are metabolic related conditions and there is overlap among those physicians that treat both disorders.”

Both companies have a focus to developing and commercializing treatments for rare diseases with a strong focus on patients and supporting communities with little to no existing therapeutic options.

Zevra Therapeutics to Acquire Acer Therapeutics 

In this episode of the Drug Solutions podcast, Jill Murphy, Editor, speaks with Dr. Graziella Piras, senior director of Strategic Marketing at 908 Devices, about drug development, specifically related to monitoring bioprocess parameters and other important technologies important to moving the process forward.

Graziella has over 15 years of experience in developing products, applications, and solutions for upstream bioprocessing. Before joining 908 Devices, she held various positions in marketing and R&D at Thermo Fisher Scientific, leading projects to support the Cell Culture and Cell Therapy business.

Graziella obtained her Ph.D. in Biochemistry & Molecular Biology in Belgium. She did her postdoc studying the role of epigenetic regulation on cancer and development at the National Cancer Institutes in Maryland.

 presents the Drug Solutions podcast, where the editors will chat with industry experts from across the pharmaceutical and biopharmaceutical supply chain. Join us as experts share insights into your biggest questions—from the technologies, to strategies, to regulations related to the development and manufacture of drug products.

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Drug Solutions Podcast: Breaking Through the Barriers of Drug Development

balance scale with pills| Image Credit: ©Alexander - Stock.adobe.com

Excipients are the ingredients of a therapeutic that change an API into a medicine and perform roles such as preservatives, diluents, buffers, binders, and drug release controllers. These excipients work in combination with the API to ensure the benefit of the drug product, according to the International Pharmaceutical Excipient Council of the Americas (IPEC-Americas). The high levels of excipients in drugs, compared to the API, mean the quality of these substances are just as important as the active ingredient. “Such excipient performance expectations as enhancing drug bioavailability, enhancing drug stability, providing controlled and sustained-release characteristics, enabling dosage form processability are but a few of the crucial roles excipients provide to ensure the drug performs as intended over its shelf life,” says IPEC-Americas.

“Excipients used in drug products may be compendial (i.e., there is a monograph for the excipient in a recognized pharmacopeia) or non-compendial.For blended excipient mixtures and co-processed excipients, unless there is a monograph for that exact blend or co-processed mixture, they are classed as non-compendial, even if all the components individually have pharmacopeial monographs,” says IPEC-Americas.

Low-quality excipients may be unsafe and present risks to the patient, including exposure to toxic substances such as benzene and diethylene glycol.“Any low-quality ingredient or adulteration that could compromise drug product quality, safety, or performance could lead to undesirable consequences, such as adverse events, lack of efficacy of the drug, hospitalizations, or at worst, death,” stresses IPEC-Americas.

According to Subba Reddy Inta, vice president and head-Quality, Dr. Reddy’s Laboratories, North America Generics, excipients may interact with the API and, therefore, lower the titer or assay. Impurities may also be generated, or the absorption, distribution, metabolism, and excretion (ADME) may be altered.

According to Catherine Sheehan, Senior Director at the US Pharmacopeia (USP) and Otilia Koo, Chair, USP Complex Excipients Expert Committee and Executive Director, BMS, ensuring the safety of excipients is extremely important. Excipients often make up the majority of a drug’s composition, Sheehan and Koo reveal, and perform a variety of functions such as maintaining pH and stability and making the drug palatable via tastemasking, coating, and coloring. Sheehan and Koo also point to the complex supply chain of excipients that lacks regulatory oversight.

“Unlike APIs, there are times when the quality of excipients is not given the necessary level of importance because excipients are inactive ingredients. Unfortunately, the impact of this can be devastating, for example, the recent deaths of reportedly 300 children in as many as seven countries due to diethylene glycol (DEG) and ethylene glycol (EG) contamination in cough syrups and oral analgesics for children,” say Sheehan and Koo.

® spoke with Sheehan and Koo to find out more about the regulations involved in excipient quality. In addition, 

 What are the USP requirements for excipients?

 Pharmacopeias worldwide contain standards and test methods to test for several excipients required for determining their quality. The 

United States Pharmacopeia–National Formulary

] General Notices 3.10. Applicability of Standards requires excipients recognized in 

to be prepared according to recognized principles of GMP [good manufacturing practice] and from ingredients complying with specifications designed to ensure that the resultant substances meet the requirements of the compendial monographs. In addition, 

 contains general information chapters on GMP requirements for bulk pharmaceutical excipients <1078>, Good distribution practices for bulk pharmaceutical excipients <1197>, and Significant change guide for bulk pharmaceutical excipients <1195>.

USP is a member of the Pharmacopeial Discussion Group (PDG) with representatives from the 

 (including the very recent addition of a pilot membership for the 

 as it prepares for global expansion), with WHO [World Health Organization] as an observer, to retrospectively harmonize standards for excipients monographs, general chapters, ICH [International Council for Harmonisation] Q4B chapters, and biotechnology chapters. The 

 has over 500 documentary standards for excipients, including high-risk for adulteration (e.g., EG/DEG) excipients such as Glycerin, Propylene Glycol, Maltitol Solution, Hydrogenated Starch Hydrolysate, and Sorbitol Solution.

According to General Notices 3.10. Applicability of Standards, standards for excipients recognized in the 

 are expressed in the excipient’s monograph, applicable general chapters, and General Notices. The identity, quality, and purity of excipient standards are determined by the official tests, procedures and acceptance criteria, and other requirements incorporated in the monograph, in applicable general chapters, or in the General Notices.In addition,

 excipient monograph standards have over 320 

 to support the test methods included in excipient monograph standards.

What are the requirements for complex excipients such as polysorbates?

 excipient standards contain standards that include test methods and acceptance criteria required for determining their quality. Excipients can be small molecules with a very well-defined chemical structure that can be characterized well analytically. Many are mixture-based products (e.g., fats and oils). Some may come in multiple grades that can be natural or synthetic or semisynthetic. Some are more complex, like polysorbates and some may vary in degree of characterization.

Polysorbates (PS) are considered complex excipients and are amongst the most versatile surfactants in pharmaceutical use used across almost all routes of administration and dosage forms. [These complex excipients] are also used as emulsifiers, solubilizers, and stabilizers. Some of the PS are well characterized in traditional routes of application in terms of their chemistry. However, they need additional characterization in some of the newer applications, such as when used in therapeutic biological drugs (e.g., in preventing protein aggregation and denaturation and stabilizing therapeutic proteins formulations).

One of the main challenges with complex excipients such as PS is identifying appropriate test methods for analyzing their complex composition and setting appropriate and meaningful specifications. The composition of such excipients can vary by inherent variations in the source of the raw materials used to manufacture the excipient and the manufacturing process. Further, their performance is highly dependent on their composition. Thus, these excipients should have standards for not only their identification, and levels on impurities, but also their composition.

One such example is the use of the fatty acid composition tests and specific tests on fats and fixed oil content in current 

 monographs of PS 20, 40, 60, 80. USP is also considering strengthening the quality control of PS by adding a direct assay testing procedure to determine the content of intact PS. Another example of a complex polymeric type of excipient is Lactide and Glycolide polymer for which a new monograph proposal was published in USP 

 and includes tests for monomer ratio and terminated group.

“In comparison to APIs, the repercussions of low-quality excipients can be equally significant. While APIs are the active components responsible for the therapeutic effect of a drug, excipients act as essential delivery vehicles and support structures. Substandard excipients can adversely affect the API’s stability, safety, and performance, rendering even a high-quality active ingredient less effective or potentially harmful,” caution Aryo Nikopour, VP, Global Market-Pharmaceuticals, and Shiri Hechter, senior manager, Scientific and Technical Services, both with Nelson Labs. Nikopour and Hechter also point to the business risks of poor-quality excipients, such as recall of products, legations, and damage to the company or brand reputation. But IPEC-Americas states the finished drug may be impacted regardless of the API.

Excipients are usually sourced by either the sponsor company or the contract manufacturing organization (CMO) from ingredient manufacturers and then used in the final product. The sponsor company and the CMO are responsible for ensuring the quality of the final pharmaceutical product. So, how may a sponsor company and/or a CMO ensure that the excipients purchased from third-party vendors are safe and best suited for the dosage form they are creating?

According to Catherine Sheehan, senior director at the US Pharmacopeia (USP) and Otilia Koo Chair, USP Complex Excipients Expert Committee and Executive Director, BMS, excipients should be sourced from qualified suppliers and sponsors should also evaluate those suppliers. Additionally, sponsors should check that the supplier has a testing program in place. Sponsors should also know who the original manufacturer of the ingredient is if it is not the supplier and an original manufacturer’s certificate of analysis should be obtained. Furthermore, each shipment of incoming raw materials should be tested for applicable standards and regulations.

According to IPEC-Americas, it is important to make sure the manufacturer of the excipient is producing the excipient under good manufacturing practices (GMPs) appropriate for excipients with the intent of that ingredient being used in pharmaceuticals. “Finally, for excipients not purchased directly from the manufacturer or a manufacturer authorized distributor, it is important for sponsors to understand the full supply chain back to the manufacturer,” says IPEC-Americas.

A comprehensive risk assessment that begins with a questionnaire is also imperative. “Ingredient samples are requested and received for assessment against specification acceptance criteria. Excipient manufacturers whose products are used for the first time should be audited either directly or by an accredited third party acquainted with pharmaceutical and excipient manufacturing requirements such [as] the appropriate level of GMP,” according to IPEC-Americas. Assessment of the manufacturer’s standard operating procedures (SOPs), batch records, and other procedures and documents should also be performed.

In addition to GMPs, according to IPEC-Americas, “Compendial excipients conform to the appropriate monograph using the compendial methods or validated equivalents. Non-compendial excipients should
be adequately characterized and properly vetted through a risk assessment to ensure the excipient meets specified quality requirements,” says IPEC-Americas.

Key elements of a quality management program, according to Nikopour and Hechter, include supplier qualification and auditing, quality agreements with suppliers, risk assessments, testing of raw materials, and change control management. In addition, stability testing, documentation, and quality matrices should be performed. “By implementing a robust quality management program encompassing the above elements, pharmaceutical manufacturers can ensure that the excipients used in their products are of high quality and safe for patients,” say Nikopour and Hechter.

Received excipient materials should go through testing and analysis, says Nikopour and Hechter. Samples should be tested regularly to determine that they meet quality specifications.The US Pharmacopeia–National Formulary (USP–NF) provides methods for testing compendial excipients.

To test non-compendial excipients, IPEC-Americas says that suppliers should develop validation methods that show that the quality and composition of their products are consistent from batch to batch. Inta points out that additional test methods may be needed based on the functional requirements of the sponsor. “Sometimes the supplier develops the different grades of a material to meet the formulation development requirement,” he says.

Manufacturers can use many of the analytical techniques used in chemical analysis for testing excipients, according to IPEC-Americas. These include infrared spectroscopic techniques (FTIR, NIR), atomic absorption (AA), inductively coupled plasma (ICP), mass spectrometry, X-ray crystallography, pH, conductance, Karl Fischer water determination, as well as the many compendial test methods (LOD, ROI, etc.). “In addition to chemical analysis, functional performance can be assessed by a variety of methods; however, functionally related characteristics (FRCs) can pose some challenges if not considering context of use.Not all FRCs will be applicable to all materials or cases,” says IPEC-Americas.

“When a compendial monograph does not exist, excipient users should determine if other regulations, compendia, or guidelines can be used to characterize suitable quality,” say Nikopour and Hechter.

According to IPEC-Americas, no formal regulatory process exists for evaluation a novel excipient outside of the drug product. However, for novel excipients that have yet to be used in a drug formulation, Nikopour and Hechter suggest following IPEC recommendations for safety evaluation of a novel excipient (1). FDA also provides guidance on safety testing for novel excipients (2).

According to IPEC-Americas, “often, sponsors don’t do all they should to qualify an excipient. However, because they don’t, that means they may accept low quality materials without knowing it ... low quality excipients may be the wrong grade of product (not intended for use in pharma), adulterated, the result of supply chain failures or from manufacturers who intentionally do not follow GMPs or regulations.”

Low-quality excipients present as much of a risk to patients as low-quality APIs, especially because they may impact the efficacy of the API. They are the support system and play a significant role in ensuring drugs are safe and work as intended. It is imperative that both sponsor companies and ingredient manufacturers have the appropriate management plan in place to perform the vital risk assessments, testing, and
verification of excipients.

The International Pharmaceutical Council Excipient Safety Guide for Pharmaceutical Excipients

Guidance for Industry, Nonclinical Studies for the Safety Evaluation of Pharmaceutical Excipients 


Vol. 47, No. 9
September 2023
Pages: 12–16

When referring to this article, please cite it as Haigney, S. In Equal Measures: The Importance of Excipient Quality. 

Excipients should be treated equally when it comes to quality management, risk assessment, and testing.

In Equal Measures: The Importance of Excipient Quality

Adam C. Fisher, Phd, is Director of Science Staff, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, FDA.

Hollywood has long presented artificial intelligence (AI) as a futuristic concept far from reality, but technology has now eliminated the gap between science fiction and science fact. AI is here and here to stay; 50% of global healthcare companies plan to implement AI strategies by 2025 (1). For pharmaceutical manufacturers, AI has the potential to revolutionize process design and control, and thus bring benefits to patients and challenges to regulators.

Owing to its fictionalized past, the term AI can mean wildly different things to different people. FDA’s Center for Drug Evaluation and Research (CDER) describes AI rather inclusively as “a branch of computer science, statistics, and engineering that uses algorithms or models that exhibit behaviors such as learning, making decisions, and making predictions” (2). The National Academies of Sciences, Engineering, and Medicine issued a report on innovations in pharmaceutical manufacturing that highlighted AI’s potential role in the measurement, modeling, and control used for pharmaceutical manufacturing (3).

AI offers potential benefits to pharmaceutical manufacturers in the form of optimized process design and control, and smart monitoring and maintenance, to drive continuous improvement. AI in concert with other innovative technologies might advance pharmaceutical quality, build more resilient supply chains, and improve the availability of medicine for patients (4). In anticipation of these benefits, FDA is proactively preparing for the arrival of AI technologies in pharmaceutical manufacturing.

AI is an enabler of Industry 4.0, the fourth industrial revolution characterized by integrated, autonomous, and self-organizing production systems (5). The Industry 4.0 paradigm brings the hope of a well-controlled, hyper-connected, digitized ecosystem and supply chain. The COVID-19 public health emergency seems to have accelerated the development of Industry 4.0 technologies, such as AI, that might respond to rapidly changing supply and demand and reduce dependence on human intervention.

So how might manufacturers deploy AI in process design and control?

 AI models employing machine learning might use process development data to more quickly design and identify optimal process parameters or scale-up strategies, reducing development time and waste.

Advanced process control might allow for dynamic control of a manufacturing process which, in combination with real-time sensor data, might be used to develop process controls that can precisely predict the trajectory of a process. Pharmaceutical manufacturers are expecting to adopt advanced process control approaches that combine AI techniques with chemistry and physics knowledge to improve manufacturing efficiency and output.

 AI methods might be used to better monitor equipment and detect changes from optimal performance. AI-detected deviations might trigger maintenance activities in a manner that minimizes process downtime.

AI methods integrated with process performance metrics might offer better trend monitoring, even across products or locations, and consequently allow for proactive corrective and preventive actions to address manufacturing discrepancies before they impact the supply chain, or worse, cause drug shortage.

The potential use of AI to monitor quality doesn’t even end at the process. AI might also be used to monitor a product’s quality after manufacturing, for example, for the integrity of its packaging or presence of particulates. A vision-based quality control system might use AI to analyze images of packaging, labels, or glass vials to detect deviations (6). Beyond the product itself, AI might be used to identify cluster problems from consumer complaints and deviation reports that might contain large volumes of unstructured text. Though the potential applications of AI in pharmaceutical manufacturing will continue expanding, whether a manufacturer employs AI or not, high-quality drugs should be consistently available to patients.

CDER established a Framework for Regulatory Advanced Manufacturing Evaluation (FRAME) initiative to prepare a regulatory framework to support the adoption of advanced manufacturing technologies that could benefit patients, such as AI. FDA recognizes potential benefits, and risks, of AI throughout the drug product lifecycle. As some manufacturers look to employ AI in their manufacturing processes, the regulatory framework will need to enable the timely adoption of these technologies while also keeping patients safe. CDER recognizes the need to better understand how this new manufacturing paradigm could impact pharmaceutical operations and regulation. The regulatory strategies of the past might not work as effectively in an AI-enabled Industry 4.0. However, regulators do not develop and implement manufacturing technologies. There is a need for the stakeholders developing these technologies to provide FDA a better understanding of where and how AI innovations might be used in drug manufacturing. Industry and regulators will not be able to address the issues related to AI by working separately; true innovation requires science-based collaboration.

In March 2023, CDER released a discussion paper to solicit public and stakeholder input on AI in drug manufacturing to better identify areas of policy consideration for AI technologies (2). This discussion paper proposed areas of consideration based on CDER’s evaluation of the existing regulatory framework: standards for developing and validating AI models, clarification on regulatory oversight for AI in pharmaceutical manufacturing, maintenance of cloud applications and continuously learning AI systems that adapt to real-time data, and data management practices commensurate with the volume of data generated.

FDA’s public workshop on the use of AI in drug Manufacturing on September 26–27, 2023, in conjunction with the Product Quality Research Institute, was designed to provide another opportunity for stakeholders to discuss key topics with regulators, such as:

Artificial Intelligence in Process Development, Process Monitoring, and Commercial Batch Trend Monitoring

Artificial Intelligence and the Use of Big Data and Data Management within the Pharmaceutical Quality System

Lifecycle Approaches to Management of Artificial Intelligence.

Discussions on topics like these will help further inform the evaluation, development, and implementation of a regulatory framework that considers the benefits and risks of AI.

Like industry, regulators can employ AI to improve processes. In fact, FDA currently uses AI for translating documents, screening adverse event reports, and forecasting the volume of incoming regulatory submissions. In the future, both manufacturers and regulators might benefit from the extensive data and analysis provided by the expanded use of AI. International regulators have projected using AI to detect false or misleading drug information, scan scientific literature, identify safety signals, and respond to public inquiries (7).

While there are potential benefits of AI, there are also risks. Access to high-quality data is a fundamental requirement for effective AI training or learning. AI can be particularly sensitive to the characteristics of the data used for training, testing, and validation. The process analytical technologies providing data to AI systems must be accurate and representative. For learning purposes, data must represent not only process successes but also process failures. It will be critical to ensure that data used for AI training or learning are fit for use based on quality, reliability, and representativeness.

Humans, and not machines, are ultimately responsible for assuring that high-quality drugs are available to patients. Humans must be able to interpret the information generated by AI enough to ensure, for example, adherence to current good manufacturing practice requirements. Even with the best intentions, there are risks for unintended consequences. Might some even use AI for unethical outcomes?

Still, continued technology advancement is undeniable. There’s already talk of an Industry 5.0 paradigm which focuses on man and machine working together, instead of separately, and considers the manufacturer’s impact on the workforce and environment (8). In looking ahead, it feels only appropriate to ask the uber popular AI chatbot, ChatGPT, how things will turn out, “Will AI improve pharmaceutical manufacturing?” “Yes, AI has the potential to significantly improve pharmaceutical manufacturing.”

The combined efforts of regulators, industry, and scientists can now help to realize this potential while safeguarding against risks to patients.

USM. Top 5 AI Use Cases in Pharma & Bio Medicine. 

FDA. Artificial Intelligence in Drug Manufacturing. 

National Academies of Sciences, Engineering, and Medicine. Innovations in Pharmaceutical Manufacturing on the Horizon: Technical Challenges,
Regulatory Issues, and Recommendations. The National Academies Press online, DOI:10.17226/26009 (2021).

Arden, S. et al. Industry 4.0 for Pharmaceutical Manufacturing: Preparing for the Smart Factories of the future.

FDA. Artificial Intelligence/Machine Learning Assisted Image Analysis for Characterizing Biotherapeutics. 

International Coalition of Medicines Regulatory Authorities. Horizon Scanning Assessment Report–Artificial Intelligence (2021).

https://research-and-innovation.ec.europa.eu/research-area/industrial-research-and-innovation/industry-50_en

Adam Fisher, PhD is Director of Science Staff and Immediate Office within the Office of Pharmaceutical Quality at the Center for Drug Evaluation and Research at FDA.


Vol. 47, No. 9
September 2023
Pages: 32–34

When referring to this article, please cite it as Fisher, A. The Future is the Present: Artificial Intelligence in Pharmaceutical Manufacturing. 

FDA is anticipating how AI may advance manufacturing and improve supply chain security.

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