As you read this note, pharmaceutical development and manufacturing are being redefined by collaboration, innovation, and the urgent need for agility. The throughline across this issue of 

® is unmistakable: success now depends on integration of systems, data, partnerships, and people.

Our cover story, “Customizable Relationships Enhance Speed to Market,” underscores this reality. As drug modalities become more complex, sponsor companies and CDMOs are moving away from traditional, transactional relationships. The new model is one of shared risk and long-term collaboration, driven by mutual investment in speed, quality, and innovation.

This spirit of innovation is reflected in the development space, where ocular drug delivery continues to challenge formulation scientists. As Cynthia Challener reports in “Advanced Solutions for Sustained Delivery of Ocular Therapies,” sustained-release technologies for eye care are gaining traction, improving compliance and outcomes in an area in which frequent dosing has long been a barrier.

“In-line UV Spectrometry Monitoring in Cleaning Validation” offers a timely look at how Pharma 4.0 principles are reshaping validation. The integration of in-line analytical tools enables real-time monitoring, greater data reliability, and stronger alignment with quality-by-design and digital manufacturing goals.

On the analytics front, “Overcoming PK/PD Modeling Challenges” explores how AI and machine learning are transforming PK/PD modeling. These tools enable faster, more accurate predictions of drug behavior, helping teams avoid costly delays and unnecessary experimentation.

We also examine the realities of small-batch fill/finish operations, including the technologies and process solutions emerging to meet the demands of low-volume, high-value production.

Finally, in “ICH Q12 and Post-Approval Changes,” Siegfried Schmitt sheds light on why streamlined post-approval change management remains elusive, and why it’s crucial for maintaining supply resilience.

Taken together, these articles offer a clear view of where pharmaceutical manufacturing is headed: toward smarter tools, deeper partnerships, and a renewed focus on compliance and quality at every stage of the product lifecycle.

Mike Hennessy Jr is Chairman and CEO of MJH Life Sciences®.

®
Vol. 49, No. 6
July/August 2025
Page: 8

When referring to this article, please cite it as Hennessy, M. The Future of Pharma: Connected, Continuous, and Compliant. 

Articles

Pharmaceutical development and manufacturing are evolving through collaboration, innovation, and agility. Success now hinges on integrating systems, data, partnerships, and people. The shift from traditional, transactional relationships to shared risk and long-term collaboration is crucial, especially as drug modalities grow more complex. Innovations in ocular drug delivery, in-line UV spectrometry for cleaning validation, and AI-driven PK/PD modeling are reshaping the industry. Small-batch fill/finish operations and streamlined post-approval change management are also critical for maintaining supply resilience and ensuring quality throughout the product lifecycle.

From the Chairman

Pharma manufacturing is headed toward smarter tools, deeper partnerships, and a renewed focus on compliance and quality at every stage of the product lifecycle.

The Future of Pharma: Connected, Continuous, and Compliant

Biopharmaceutical manufacturers rely heavily on non-specific, at-line analytical testing to confirm cleanliness of equipment surfaces through final rinse water analysis, potentially leading to false positives and problematic on-line or off-line testing. Spectroscopy methods, such as ultraviolet (UV) spectroscopy at 220 nm, can be used for continuous, in-line monitoring of the cleaning process. The sensitivity of the method can be improved by adjusting the sanitary flow path length. The authors performed interference and enhancement testing using a formulated alkaline and acid cleaner, as well as common biopharmaceutical process residues (such as monoclonal antibody drug substances, insulin drug product, and bovine serum albumin, which displays a cumulative effect like in total organic carbon analysis). Results showed that in-line monitoring capability of UV spectroscopy enables continuous monitoring of the entire cleaning cycle and applicability to quality by design, process analytical technology, process digitalization, and sustainability goals of a Pharma 4.0 manufacturing facility.

Submitted: March 27, 2025
Accepted: May 20, 2025

Demonstration of equipment cleanliness through analytical testing is a critical part of cleaning validation and contamination control strategies. Health authorities require that equipment is visually clean and contaminant residues are reduced to scientifically justified limits (1–4). Contaminants can include residual product or intermediates, cleaning residues, excipients, particulates, and endotoxins. The scientifically justified limits are based on toxicological evaluation and health-based exposure limits (5–9). The European Commission’s Annex 15, Section 10.6.1 states that biologics are “known to degrade and denature when exposed to pH extremes and/or heat;” these are common conditions in a cleaning process, and Section 10.6.2 supports non-specific methods, such as total organic carbon (TOC) and conductivity, when it is not feasible to test for specific product residues, such as when they are degraded (4). The incorporation of a scientifically justified (real-time, in-line) non-specific method such as conductivity or ultraviolet (UV) spectroscopy can aid in ensuring a state of control of a validated cleaning process by providing continuous process verification (10).

Equipment cleanliness requires that the validated cleaning steps have been followed and acceptable cleanliness has been demonstrated by analysis of samples through various techniques, including direct surface, swab, and rinse sampling (4,11). Each technique has advantages and disadvantages and can fit within the scope of a cleaning validation program. As a cleaning process matures into the continued monitoring phase, on-line rinse sampling (at-line or in-line) is advantageous, as it removes the requirement for collection and subsequent analysis of grab samples, decreases the turnaround time of the results, and improves the equipment release process. At-line sampling diverts an aliquot of the sample, often the final rinse water, to the instrument probe (12,13). In-line sampling involves having an instrument probe in the flow path of the fluid stream, providing continuous analysis (14,15).

Analytical methods for in-line and at-line rinse sampling include conductivity; TOC; chromatography methods, such as high-performance liquid chromatography (HPLC) or ultra-high-performance liquid chromatography (UHPLC); and spectroscopic methods, such as UV and fluorescence. The selection and eventual validation of the analytical method depends on the soils being cleaned, including the cleaning agent, the range of the analytical method, and analyte interferences with other components in the soil (16). The International Council for Harmonisation’s (ICH) Q2B document provides guidance on analytical method validation, which requires a specified analytical range, linearity, ruggedness, precision, accuracy, limit of quantitation (LOQ), limit of detection (LOD), and specificity for the analyte in the presence of expected components (17–19).

Conductivity is commonly used to demonstrate removal of cleaning agents but can have interferences with ionic species in buffers and some products. TOC is also a commonly used technique to show removal of product and cleaning agent and can have interferences with organic compounds, which are common in biopharmaceutical manufacturing. Elevated conductivity or TOC results require additional off-line testing to investigate the result and confirm the source of the contamination and risk to next batch or product, and patient.

UV spectroscopy is a common analytical technique used for monitoring chromatography and filtration steps in biopharma manufacturing, in cleaning processes of APIs, and in quality control for testing of raw materials, intermediates, and final product (15, 20–22). UV provides a semi-specific technique for detection of residual product and cleaning agent in cleaning applications.

UV analyses are performed by measuring transmittance of radiation through a sample and comparing against a blank solution. Absorbance of a sample is proportional to its concentration, and the distance the light must travel through the sample based on the Beer-Lambert law, A = εlc, where A is the absorbance, ε is the extinction coefficient, which is a sample specific constant describing how much the sample is absorbing at a given wavelength, l is the pathlength, or the distance traveled by light through the sample, and c is the concentration of the solution. The pathlength of the sample, which is typically a fixed parameter in an analysis, can be modified to change the sensitivity of the method. A 1 cm pathlength is common in laboratory testing. Increasing the pathlength to 10 cm increases the absorbance 10-fold and can consequently decrease the LOD and LOQ.

Every compound has a different spectrum based on the structure. Selecting a wavelength for detection and monitoring can vary based on the highest overall peak in the spectrum or localized maximum. Previous studies have explored detection of cleaning agents by coupling HPLC or UHPLC with a UV detector (23). In these studies, a wavelength of 224 nm was selected based on the alkaline and acidic cleaner; these patented formulations include a chromophore to help with UV detection, either with a standalone detector or coupled with liquid chromatography. These cleaning agents have higher absorbance at the lower range—190–200 nm. However, because many organic molecules also absorb at this lower range, the inevitable interference outweighs the benefits of a higher absorbance. The localized maximum at 220 nm provides greater specificity compared with other compounds expected in the cleaning process.

These formulated alkaline and acid cleaners are composed of multiple components. To leverage one assay, such as in-line UV analysis, for the removal of the formulated cleaner, the following information should be available:

concentration of the analyte in the formulation

rinse profile studies using specific and non-specific methods to demonstrate that all components rinse at the same rate

rinse recovery of the analyte from the surface materials

spray device coverage testing of the equipment and piping circuits

toxicity evaluation of the formulated cleaner.

These studies have been discussed in detail in literature supporting cleaning validation and surface analysis (11,17).

Cleaning processes can degrade therapeutic macromolecules with pH extremes and high temperatures (4). This degradation can render the product biologically inactive. Biologically inactive products may no longer pose a toxicological challenge, but the degraded product needs to be removed from the equipment surface. HPLC, coupled with UV or mass spectrometry (MS), can provide information on whether or not the product is degraded. This approach requires at-line or grab sampling analysis, in addition to the time needed to perform the testing. Non-specific methods, such as TOC and conductivity, are not capable of differentiating intact from degraded products. For example, the TOC of a biologic API will detect native and degraded compounds, unless the product is degraded to an inorganic carbon. Additional studies are needed to demonstrate that product is degraded at those cleaning conditions (24–27). When analyzing protein degradation, sodium dodecyl sulfate polyacrylamide gel electrophoresis provides evidence of degradation by measuring the molecular weight of the sample. A sample is treated with a cleaning agent under the specified concentration, temperature, and time. This sample is analyzed alongside an untreated sample; the responses are compared to verify degradation.

A series of experiments were conducted by the authors to determine the feasibility of using in-line UV spectroscopy for the detection of residual biopharmaceutical drug substance or product and cleaning agent using in-line and standalone instruments. To use in-line UV for cleaning applications, several studies were performed to demonstrate that measurement of the cleaning agent and product can be validated with UV spectroscopy; the combination of cleaning agent and product do not enhance or depress the response; both intact and degraded product, in the presence and absence of cleaning agent, can be detected; comparable responses are observed between in-line and standalone UV detectors; and the real-time, in-line monitoring of product and cleaner is possible with UV spectroscopy.

 Initial studies to determine the optimal wavelength and linear concentration range were carried out using a spectrophotometer (ThermoScientific GENESYS 50 UV-Vis) and 10 mm quartz cuvettes (Fisher Part # 14-958-112). Spectra were collected from 190–400 nm for ~1000 ppm solutions of each cleaner diluted in type 1 water.

The range of the formulated cleaners was qualified from 25–1000 ppm (alkaline cleaner) and 10–1000 ppm (acidic cleaner) by characterizing the linearity and precision (repeatability) of the UV response. Accuracy of the analysis for concentrations calculated from measured UV absorbances was studied by quantitation of prepared samples via an external standards method. Linearity and precision studies were carried out by triplicate preparation and analysis of calibration curves across the concentration range of interest. Separate sample preparations, either alternate lots or concentrations within the linear range, were then prepared, analyzed, and quantitated using these calibration curves to assess the accuracy of the method. The LOQ, LOD, and specificity of the method was inferred based on the linearity, accuracy, and precision studies.

 Model process soils were selected to encompass several product families in biopharmaceuticals that may use clean-in-place cleaning. A sample of bovine serum albumin (BSA), a standard for proteins in analytical methods, was purchased (EMD Millipore); samples previously studied for protein degradation (e.g., monoclonal antibody [mAb] and insulin) were also studied.

Each soil was diluted to concentrations across the analytical range studied for the alkaline cleaner and the UV response characterized. Additional preparations were made that contained 1:1 mixtures of the model soils and the alkaline cleaner. Spectra were collected for each solution, and absorbance at
220 nm monitored.

Effect of the degradation of the mAb on the UV measurement was studied by treatment of the mAb drug product with solutions of the alkaline cleaner at 1% and 3% concentration. Stock solutions were prepared and preheated to 60 oC. Once pre-heated, the mAb drug product was diluted with the degradation solutions 1:10 and temperature maintained for five minutes. To quench the reaction, the degradation solution was diluted to 100 mL with ambient temperature type 1 water.

For analysis via UV, solutions were diluted to cleaning agent concentrations ranging from 5–1000 ppm, and measurements made as described in the method development section.

In-line sensor–static measurement. A PX2 Photometer configured to monitor absorbance at 220 nm and a pathlength of 100 mm (10 cm) (EZ Cal Flow Cell) was provided for testing by Custom Sensors and Technology (Fenton, MO). Solutions of the alkaline and acid cleaner were prepared at concentrations ranging from 5–100 ppm. The measurement cell was configured with a fill port above the sensor and a drain port below to allow filling and draining of the chamber.

The sensor was blanked with type 1 water prior to sample solution absorbance measurement. UV absorbance was measured for approximately two minutes. The cell was rinsed with type 1 water between each measurement.

After data were collected with the PX2 photometer, the same solutions were analyzed on a spectrophotometer as previously described for comparison.

In-line sensor–dynamic measurement. The PX2 photometer was configured in the same manner as used during static measurement studies and was fitted on the drain port of a 60 L mixing vessel. Prior to testing, the sensor was blanked on deionized (DI) water from the source used to prepare cleaning and standard solutions.

The vessel was flushed with 10 ppm solutions of alkaline and acid cleaners for approximately two minutes via static spray ball, and the UV absorbance at 220 nm was monitored and compared with the established DI water baseline.

To study cleaning of the vessel, the interior surface was manually soiled with portions of the BSA and insulin samples characterized during the spectrophotometer studies. The vessel was then cleaned via a one-minute rinse with 1% (v/v) alkaline cleaner, immediately followed by a one-minute rinse with 1% (v/v) acid cleaner. The vessel was then rinsed with DI water. The real-time UV absorption at 220 nm was monitored throughout.

Spectroscopic method development and qualification.

 Example spectra used for wavelength selection are provided in

. While neither spectrum exhibits a true peak, a local maximum is observed at 220 nm for each cleaner. As most organic compounds have some UV absorption character at and below 200 nm, selecting a longer wavelength improves the potential specificity of the method. Additionally, each cleaning agent used contained an analyzable surfactant with a chromophore having a characteristic absorbance at 224 nm. For method development and qualification, cleaner concentrations were monitored via absorbance at 220 nm.

Using the collected linearity, precision, and accuracy data, the LOD and LOQ were established. The upper limit of the analytical range for each cleaner was
1000 ppm. A summary of the method qualification data is provided in 

 For the alkaline cleaner, an LOD of 5 ppm and an LOQ of 25 ppm were established. For the acid cleaner, the LOD and LOQ were 5 and 10 ppm, respectively. UV spectroscopy is a non-specific method, and other components can contribute a response. Specificity studies are needed for process residues as described in the following section. The data support that both cleaners can be validated per ICH Q2 parameters (18).

 The UV response at 220 nm for each soil was observed to be linear across a similar concentration range as the alkaline cleaner. For the cleaner and soil mixtures, an additive effect was observed for absorbance at 220 nm. Spectra demonstrating the additive effect are provided in 

. This additive effect has been previously observed and characterized during UHPLC studies for analytes in different formulated cleaners (23). Another localized maximum specific for downstream protein determination was observed at 280 and 310 nm by Westwood et al. and Rathmore, et al., respectively (15,20).

Linearity of the UV response was retained when the cleaners and process soils were characterized in mixed solutions and the absorbance of the cleaner/soil mixture remained within the dynamic range of the spectrophotometer used. Absorbance curves for an alkaline cleaner, an insulin drug product, and a mixture of both components are provided in 

The ratio of absorbance of the model process soil to cleaners ranged from 0.60 to 0.96, as shown in 

 The combination of the cleaner and process soil is additive; the combination of the components does not enhance nor depress the response. As a non-specific method, all the signal needs to be attributed to the single worst-case component. While this attribution may lead to a bias to failing, the additive interaction of the process soil and cleaner supports the use of UV spectroscopy for the detection of residual amounts.

Product degradation. An example spectrum of the combined cleaner and degraded mAb drug product at an approximate ratio of 3.4:1 is provided in 

. The additive effect on measured absorbance previously observed was maintained for the degraded mAb. Additionally, the linearity of the response was preserved, as the absorbance measured remained within the dynamic range of the detector, despite the significantly greater drug product concentration relative to cleaner concentration. A plot of absorbance versus degraded mAb and cleaner solution is provided in 

In-line sensor–static measurement. The mean absorbance result was calculated for each two-minute measurement and then plotted as a function of cleaner concentration. A linear regression was performed and compared with a linear regression analysis for absorbance results for the same solutions characterized via spectrophotometer. Linearity was achieved for each cleaner across the range investigated with significantly greater absorbance observed for the longer pathlength cell compared with the spectrophotometer/cuvette measurements. Plots are provided in

In-line sensor–dynamic measurement. The absorbance measured for the 10 ppm cleaner solutions were significantly greater than the DI water baseline, indicating that it should be possible to detect cleaner residues at a typical limit concentration. Absorbance results when measured on the spectrometer were 0.112 and 0.138 for the alkaline and acidic cleaners, respectively. When measured on the PX2 photometer, absorbances were 0.306 and 1.432 for the same solutions. The response for the acidic cleaner in the PX2 photometer is as expected given the 10x pathlength compared with the cuvette. However, the alkaline cleaner is not proportional, potentially due to being below the proposed LOQ. Additionally, because the process has not been fully optimized, foam in the line could reduce the effective pathlength.

For the insulin drug product testing, the process can be clearly visualized in the UV absorbance data. As the 1% cleaning solutions were flushed through the system removing the soil, absorbance values greater than 4.0 were observed for both cleaners. During the rinse immediately following the cleaning process, UV absorbance was observed to rapidly return to baseline (<0.02 absorbance) in under one minute, indicating clearance of both the drug product soil as well as any cleaning agent residue. The same process profile was observed for the BSA cleaning study. 

 shows the absorbance during the cleaning process steps.

Guidance for Industry: PAT–A Framework for Innovative Pharmaceutical Development

 was issued in 2004, and several theoretical and applied articles were published over the years utilizing current cleaning agents and on-line analytical technology (28–34). As the pharmaceutical industry strives toward Pharma 4.0 manufacturing and a digitalized cleaning process, the requirements for innovative formulated cleaners and in-line analytical sensors is paramount (35).

This article revisits the use of in-line UV spectroscopy with a sanitary flow cell at a specific wavelength to demonstrate cleaner removal. Interference and enhancement testing was performed using common biopharmaceutical process residues, such as native and denatured mAb drug substances, insulin drug product, and BSA, which displays a cumulative effect like TOC analysis. The in-line monitoring capability of UV enables real-time continuous monitoring of the entire cleaning cycle and applicability to quality by design, process analytical technology process digitalization, and sustainability goals of a Pharma 4.0 manufacturing facility.

The authors would like to thank John Gleeson and Frank Westwood of Custom Sensors & Technology (Fenton, MO, USA) for providing the prototypes and assisting with in-line testing using the sanitary flow cell with UV detector.

Guide to Inspections Validation of Cleaning Processes

Guide-0028 Cleaning Validation Guidelines.

http://www.Canada.ca/content/dam/hc-sc/documents/services/drugs-healthproducts/compliance-enforcement/good-manufacturingpractices/validation/cleaning-validation-guidelines-guide-0028/document/pub1- eng.pdf

Validation Master Plan Installation and Operational Qualification Non-Sterile Process Validation Cleaning Validation

EC. Annex 15, Qualification and Validation. 

Good Manufacturing Practice Medicinal Products for Human and Veterinary Use

ISPE Baseline Guide: Risk-Based Manufacture of Pharmaceutical Products (Risk-MaPP)

Guideline on Setting Health-Based Exposure Limits (HBELs) for Use in Risk Identification in the Manufacture of Different Medicinal Products in Shared Facilities

 (EMA, November 2014 and effective date: June 2015).

WHO. Working Document QAS/20.849, Draft Working Document–Points to Consider on Different Approaches–Including HBEL–To Establish Carryover Limits in Cleaning Validation for Identification of Contamination Risks when Manufacturing in Shared Facilities. May 2020.

Inspection of Health Based Exposure Limit (HBEL) Assessments and Use in Quality Risk Management (PI 052-1) 

SEI/ANVISA 1254417 Technical Note HBELs, December 2020

Current Step 4 version dated August 2009.

Rivera, E. and Lopolito, P. Evaluating Surface Cleanliness Using a Risk-based Approach. 

Dion, M.; Van Houte, O.; and Verghese, G. On-line TOC Monitoring in GMP Parts Washers. 

Bader, K.; Hyde, J.; Watler, P.; and Lane, A. On-line Total Organic Carbon (TOC) as a Process Analytical Technology for Cleaning Risk Management. 

Aramouni, N.A.K.; Steiner-Browne, M.; and Mouras, R., Application of Process Analytical Technology (PAT) in Real-Time Monitoring of Pharmaceutical Cleaning Process: Unveiling the Cleaning Mechanisms Governing the Cleaning-in-Place (CIP).

 Process Safety and Environmental Protection

 177, 212-222 DOI: 10.1016/j.psep.2023.07.010

Westwood, F.; Ponstingl, M.; and Dickens, J.E., Analytical Figures of Merit of a Dual-Wavelength Absorbance Approach for Real-Time Broad Protein Content Monitoring for Biomanufacturing. 

Journal of Pharmaceutical and Biomedical Analysis

Kaiser, H.J.; and Minowitz, M. Analyzing Cleaning Validation Samples: What Method? 

Kaiser, H.J. and Ritts, B. Validation of Analytical Methods Used in Cleaning Validation. 

 Cleaning Validation: Process Life Cycle Approach. Contamination Control,

Rathmore, N.; Qi, W.; Ji, W.C. Cleaning Characterization of Protein Drug Products Using UV-vis Spectroscopy. 

Zhang, C.; et al., Re-thinking Cleaning Validation for API Manufacturing. 

Sarwar, A.; et al., Investigation of an Alternative Approach for Real-Time Cleaning Verification in the Pharmaceutical Industry. 

, 145, 7429-7436. DOI: 10.1039/D0AN01219J

Gietl, M.; Meadows, B.; and Lopolito, P. Cleaning Agent Residue Detection with UHPLC. 

Kendrick, K.; Canhoto, A.; Kreuze, M. Analysis of Degradation Properties of Biopharmaceutical Active Ingredients as Causes by Various Process Cleaning Agents and Temperature. 

Sharnez, R.; Spencer, A., et al. Methodology for Assessing Product Inactivation during Cleaning: Part 1: Experimental Approach and analytical Methods. 

Sharnez, R. Degradation of Proteins during Cleaning and Sanitization. Part 1: Implications for Cleaning Characterization and Analytical Method Development. 

Houser, G.; Hadziselimovic, D.; Lopolito, P. Cleaning Process Design for Peptide Therapeutics. 

Guidance for Industry: PAT–A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance

Verghese, G. and Lopolito, P. Process Analytical Technology and Cleaning. 

Rathore, A.S.; et al. Case Study and Application of Process Analytical Technology (PAT) Towards Bioprocessing: Use of On-Line High-Performance Liquid Chromatography (HPLC) for Making Real-Time Pooling Decisions for Process Chromatography.

Rathmore, S.A. Case Study and Application of Process Analytical Technology (PAT) Toward Bioprocessing: II. Use of Ultra-Performance Liquid Chromatography (UPLC) for Making Real-Time Pooling Decisions for Process Chromatography. 

Read, E.K.; et al., Process Analytical Technology (PAT) for Biopharmaceutical Products: Part I. Concepts and Applications. 

Read, E.K.; et al., Process Analytical Technology (PAT) for Biopharmaceutical Products: Part II. Concepts and Applications. 

Hellings, M. and Vanbaelen, H. The Application of PAT for Cleaning and Cleaning Validation. 

Sharma, D.; Patel, M.; and Shah, A. A Comprehensive Study on Industry 4.0 in the Pharmaceutical Industry for Sustainable Development, Recent Advances in Viable and Sustainable Supply Chain Management. 

Environmental Science and Pollution Research

John Schallom is senior technical services Associate, STERIS. Brian Bosso is technical services manager, STERIS. Paul Lopolito is technical services director, STERIS. Katie Frey is formulation manager, STERIS. Amy Thanavaro is R&D scientific manager, STERIS.

In-line UV spectroscopy offers a promising solution for continuous monitoring of cleaning processes in biopharmaceutical manufacturing. By utilizing a specific wavelength, it enables real-time detection of residual cleaning agents and biopharmaceutical products, including both intact and degraded forms. This method supports the goals of Pharma 4.0 by enhancing process analytical technology, quality by design, and sustainability. The study demonstrated that UV spectroscopy can be validated for cleaning applications, providing a non-specific yet effective approach to ensure equipment cleanliness and compliance with regulatory standards.

Peer-Review Research

The authors performed interference and enhancement testing using a formulated alkaline and acid cleaner, as well as common biopharmaceutical process residues.

In-line UV Spectrometry Monitoring in Cleaning Validation

Personalized therapies have become a focus of the pharmaceutical industry with the advancement of cell and gene therapies, creating a need for specialized manufacturing processes and infrastructures. This new market of personalized treatments is also increasing the need for small batch sizes.

“Point-of-care production or hub-and-spoke models could become the norm,” David Phasey, Innovation Director at 3P innovation, said in an interview with 

® (1). “The automation of patient and manufacturing data will be key to this. The real question is whether the pharmaceutical industry is ready to adopt and accept this level of automation into a very slow-to-change industry. Can regulations keep up with technology and the opportunities it presents?”

Complexity often comes along with innovation. And the aspects of small-batch manufacturing for personalized medicine are no different. Processing speed, flexibility, and product yield are among these complex challenges.

“Every drop counts for high-value drugs, since even the slightest product loss has significant consequences related to the number of patients treated, as well as economic impacts, and must be avoided,” says Laura Moody, director of Product Management Pharma North America, Syntegon.

The challenges of small-batch manufacturing

Small-batch manufacturing comes with a distinct set of challenges, according to
Dr. Jitendra Amrutkar, Head–Process Technology & Support, ACG Engineering. Small batch means fewer doses and, therefore, a high cost per unit, Amrutkar adds, and these costs can be reduced by using modular systems and single-use technologies. The frequent changeover of products can also hit costs by creating downtime.

“There is clearly a trend toward smaller batch sizes of sterile product,” says Hanns-Christian Mahler, CEO, ten23 health. “This, of course, raises key questions on ‘yield’, as maximizing yield translates directly into the cost-of-goods for a given product. This is particularly important for such costly APIs as biologics.”

The manufacturing facility and processes must be adequately designed for small batches, stresses Mahler. “Specifically, ready-to-use (RTU) containers are convenient to avoid the need for large washing machines or sterilizing tunnels. However, formulation development and stability data are required to allow selection of an RTU container a priori,” he states.

There are also unique complexity considerations with personalized treatments, such as specialized materials and unique regulatory approvals, according to Dr. Amrutkar. “AI [artificial intelligence] and blockchain can help to overcome this issue by improving visibility and coordination,” he offers as a solution to supply chain concerns. For regulatory compliance issues, he recommends using digital records and adaptive pathways.

Automation has been an increasing tool for pharmaceutical manufacturing, but Dr. Amrutkar cautions that traditional automation systems are not suited for small batches. He recommends smart, modular automation and cobots, which offer flexibility.

A variety of process development approaches can help with the challenges of small-batch manufacturing, according to Dr. Amrutkar. He points to modular process design for flexible, scalable setups of products to support faster changeover and reduced downtime. A modular design may also make expansion easier. Virtual testing of processes before they are implemented can be facilitated by digital twins and simulation, Dr. Amrutkar says, which can reduce risk and improve efficiency. Continuous manufacturing can also streamline production by causing fewer interruptions and increasing turnaround times. Lastly, optimal process conditions can be identified by utilizing design of experiments.

“On the process side, suitable processing materials, such as tubing and filters, help to maximize extraction of the product,” Mahler explains. “Pharmaceutical manufacturers must consider ‘flush volumes’ that are required for the setup (e.g., to saturate sterile filters); how much volume other in-process controls (IPCs) require; and how the sampling volume may be reduced. Understanding the scale and batch size capabilities of a facility, including the lowest compounding volume that can be used, are key considerations.”

The evolution of human-centered to fully automated production in aseptic filling is increasing, according to Moody, with the use of “robotics for container transfer, fill/finish operations, and format part exchange within the isolator. A shift to gloveless systems further reduces the need for manual intervention,” she says.

“To avoid product loss, 100% IPC during the filling process ensures that almost every drop of product is filled,” Moody continues. “Moreover, new small- or even micro-batch solutions can support scale-up from manual clinical trial operations to automated production scale.”

Isolators and restricted access barrier systems can provide high contamination control and cost-efficiency for small-batch manufacturing by ensuring sterility in aseptic environments, says Dr. Amrutkar. To minimize product loss and ensure dosing accuracy, he points to micro fillers that can provide precision filling for low-volume, high-value biologics. Digital management of manufacturing and batch records can be achieved through manufacturing execution systems and electronic batch records. “They improve traceability, compliance, and data integrity, which is especially important for personalized medicine,” Dr. Amrutkar says. In addition, “ACG’s capsule filling and inspection systems are high-precision systems tailored for clinical and personalized applications. They are tailored for low-volume needs with integrated inspection to ensure quality assurance,” Amrutkar offers.

Flexible filling platforms are available for small- and micro-batch operations. Syntegon offers platforms that can process between 120 and 500 containers per hour and batches up to 3600 containers per hour. The company’s Versynta microBatch platform is a fully automated gloveless production cell with integrated air handling that was developed in partnership with Vetter, according to Moody.

ten23 uses ready-to-use (RTU) containers to operate at different sterile filling scales. In July 2025, the company announced it had joined the “Alliance for RTU” partnership, which intends to advance knowledge around sterile manufacture of RTU containers. The company’s role will be to contribute its own experience in development, sterile fill/finish, and testing of sterile drug products using RTU containers (2).

When it comes to fill/finish of small batches, scale related to unit operations needs to be appropriate, says Mahler, who says manufacturers should consider the following questions. “How do you mix and homogenize 1 liter of material for a commercial product? Is that in place? Which disposables do you use, and how can you minimize residual volumes on the line? Where and why do you pull samples for in-process testing or extended characterization, and how can these volumes be reduced?”

He adds, “One great example is the choice of adequate sterile filters: some filter materials tend to adsorb critical components of a biologics formulation and may require 1 or more liters of flush volume. Other filters will be saturated with 10 mL. That can be a huge cost driver, or saver.”

Targeted solutions can address challenges associated with the fill/finish of small batches, says Dr. Amrutkar. For sterility assurance, isolators and automated aseptic systems are key for managing contamination risk, he says.

Safeguarding the aseptic environment is key in fill/finish of small batches of biopharmaceutical products, Moody agrees. “Humans pose the greatest risk for product contamination, so operator intervention must be reduced to an absolute minimum or even completely avoided to reduce this risk,” she says. Annex 1 of the European Union’s good manufacturing practice guidelines (3) recommends the use of these barrier technologies.

Precision filling technologies and single-use systems can combat product loss. Adopting a risk-based digital validation approach can streamline repeated validation.

Fill/finish systems that are traditionally used in pharmaceutical manufacturing are often too large for filling small batches of product. Scaling down to miniaturized, single-use equipment can combat this, according to Amrutkar.

Small batches of products may require different container formats that complicate the setup of machines. “Implementing modular lines and quick-change tools can help simplify the process, increase flexibility and adaptability, and help eliminate bottlenecks,” Amrutkar says.

Small-batch manufacturing should be performed holistically with development, manufacturing, and testing approaches integrated, says Mahler, and the combination of formulation and primary packing should be done ‘wisely.’

“Think about potential failure modes and assess your process in development labs, assessing the choice of materials, failure modes and acceptable ranges for your operating parameters, to ensure there is no (relevant) impact on your product’s critical quality attributes,” Mahler concludes.

Haigney, S. New Modalities in Biopharmaceutical Development Transform Industry. 

Lavery, P. ten23 health Joins Gerresheimer, SCHOTT, Stevanato Group in ‘Alliance for RTU’. 

EC. Annex 1: Manufacture of Sterile Medicinal Products. 

®
Vol. 49, No. 6
July/August 2025
Pages: 16–17

When referring to this article, please cite it as Haigney, S. Flexibility Provides Solutions to Small-Batch Manufacturing Challenges. 

Advancements in cell and gene therapies have driven the pharmaceutical industry towards personalized treatments, necessitating specialized manufacturing processes and infrastructures. Small-batch manufacturing presents challenges such as high costs, processing speed, and product yield. Modular systems, single-use technologies, and automation are proposed solutions to these challenges. The use of AI, blockchain, and digital records can enhance regulatory compliance and supply chain coordination. Flexible filling platforms, precision filling technologies, and modular lines are essential for efficient small-batch production, ensuring sterility and minimizing product loss.

Manufacturing

Modular process design, single-use technologies, and flexible filling lines are some of the ways manufacturers can combat challenges involved in small-batch manufacturing.

Flexibility Provides Solutions to Small-Batch Manufacturing Challenges

® has covered thus far in 2025 that involve outsourcing in some way include artificial intelligence (AI), quality support expertise, process development optimization, and the future of antibody-drug conjugates (1–4).

The crucial nature of the relationship between sponsor companies and contract development and manufacturing organizations (CDMOs) came into full focus at the Drug, Chemical & Associated Technologies Association (DCAT) Week in March 2025, where India-based Shilpa Medicare announced that it was launching a full-service, “hybrid” CDMO that aims to adopt a dual approach: offering comprehensive discovery, clinical, and commercial outsourcing services, but also including commercially ready, “off-the-shelf” novel formulations for business-to-business (b2b) licensing (5).

The changing demands of customers, along with continuous advancements in modalities and technologies, are all trends in outsourcing that deserve a deeper look.

According to Sridevi Khambhampaty, CEO of Shilpa Biologicals, a fully owned subsidiary of Shilpa Medicare, the bio/pharmaceutical industry is constantly evolving both in terms of the technology that is driving innovation in the field, and in novel treatment modalities (6). Because of this, Khambhampaty said, the outsourcing market is continuing to grow, placing even more emphasis on the sponsor–CDMO dynamic.

“With this plethora of technologies and modalities, it's quite challenging for any company to have all of these under their roof,” Khambhampaty said (6). “So, the small biotechs which want to pursue several new ideas in the novel therapeutic modalities would like to use the CDMO services, because they obviously don't want to invest in all the capex [capital expenditure] required for taking their ideas to market.”

Novel modalities are not the only thing causing change. Smart technologies such as AI and machine learning are keeping outsourcing partnerships in a state of constant evolution, said Ashu Tandon, chief commercial officer at Aragen Life Sciences.

“I think both of these are in some way connected to a broader trend that I've been seeing in the industry, and that broader trend is essentially moving from what was historically a very transactional-based partnership or collaboration model to one where it is much more longer-term, much more integrated, [and] much more involved engagements that we see from customers, and obviously from our side as well,” Tandon said. “And all of these take into account the fact that companies are moving from a transactional relationship to one where they are heavily invested in working with Aragen, and some of our peers, to look at how we can bring their drugs more efficiently to the market.”

“The industry has seen a flood of several strategic alliances being announced, with organizations looking for first rights, resource prioritization, and/or dedicated slots for manufacturing,” Robert Cornog, senior director of product development of Quotient Services, said. “There are clear advantages to these partnerships including stability, predictability, and organizational alignment. However, the most successful organizations will be those that can uphold those strategic relationships without losing the operational flexibility to support clients, particularly those with low volume or niche drug programs.”

As both the market itself and the range of outsourced services that are desired have gotten bigger, said John McQuaid, president and managing director of Almac Pharma Services, the strategies of CDMOs have changed by necessity, including, as in Shilpa’s case, starting their own CDMO.

“What started as a largely tactical capacity player for large pharma [companies], and probably what was basic manufacturing and packaging services, I think it's really turned into something a lot more diverse and strategic in nature,” McQuaid said (6). “Today, CDMOs, we're important partners for both large and smaller pharma companies. It's not just capacity that we offer. It's also technical and scientific knowledge. We have specialisms and technology platforms, and in some cases, proprietary platforms of our own.”

Jagruti Patel, senior director of commercial development for Integrated Biologics at Lonza, told 

 that an increasing number of strategic partnerships are homing in on the chemistry, manufacturing, and controls (CMC) part of the process.

“What is really key is working with a CDMO who has a proven track record in this space,” Patel said. “They can provide you the scientific experts to work closely with you on the CMC journey. The scientific experts could design or develop a really tailored tech transfer package strategy, they can establish a design space for process parameters to allow for flexibility and establishing risk management tools like FMEA [failure mode and effects analysis] ... really pinpointing your critical quality attributes.”

Novel modalities are emerging, McQuaid said, but not only that—companies are finding that the ones driving the most activity have shifted over time.

To name one area, according to Cornog, Quotient Sciences’ Philadelphia-area drug product manufacturing sites recently made facility improvements to expand its capabilities for handling products containing highly potent APIs.

Shifts like this have matured relationships between sponsor companies and CDMOs from at one time being merely transactional to now being closer to true, evenly matched partnerships (6).

“When I started, [outsourcing activity] was dominated by small molecules, and whilst we still see strong demand in this area, we've seen higher percentage growth in areas such as biologics, vaccines, [and] cell and gene therapies,” McQuaid said (6). “We've got ADCs [antibody-drug conjugates] and of course most recently, peptides. Another trend we've definitely seen is the growth in personalized medicines. That's brought about by better drug target identification, [and] advances in genomics and biomarkers.”

Sometimes a change can come when least expected, as Tandon mentioned with one of Aragen’s clients who is a major player in the oral solid dosage market. He said the COVID-19 pandemic was the impetus for both sides to huddle up and re-examine their relationship.

“We both sat together and said there has to be a better way of discovering these new compounds, testing them, and getting them into the clinic. There just has to be a better way,” Tandon said, explaining that the two teams “essentially devised or drew out a process map ... from early synthesis, to all the testing that happens on the biology side, to all the efficacy studies, the animal toxicology studies, to essentially putting together a development candidate up for review by the internal committee.”

The nature of outsourcing partnerships may be changing, as McQuaid illustrated, but both he and Patel agree that there are simply more of these alliances being formed now than there used to be—with no end in sight.

“In 2024, we saw the CDMO share of installed mammalian capacity at around 49%, and that is expected to increase to around 56% by 2029, so as you see the CDMO share increasing, we also see a trend in accelerating strategic partnerships between CDMOs and our customers,” Patel said. “In addition to that, we're also seeing customers asking for more integrated solutions, and that, to me, is a no-brainer when you're looking for simplified logistics, accelerated timelines, [and] harmonized technologies.”

The emergence of personalized medicines is emblematic of a larger trend in customization of services that extend not just to the patient, but within outsourcing partnerships themselves.

“To cater to these diverse modalities, I think flexibility is the key, and being able to offer modular services is also one of the key things,” Khambhampaty said (6). “For example, at Shilpa, we managed to create multiple suites, which I think a lot of the CDMO industry is also adapting to—to be able to make plasmid DNA in one suite, make mRNA [messenger RNA] in one, and then make ADC conjugation in one, and so on and so forth.”

This ideally results, Khambhampaty said, in an increased ability for molecules to be advanced more quickly to the clinical stage, the area in which she sees most of the demand in the CDMO sector currently concentrated with respect to new modalities (6). And to attack that demand on a smaller scale, rather than relying on a large-scale facility, can prove advantageous in the long run.

“A one-stop shop is always welcome, just from the ease of coordination, because you don't have to deal with multiple partners to get a project done,” Khambhampaty said (6). “But the key advantage [to outsourcing] is that the various moving parts within a project can be handled much better. So, for example, delays, let's say, in certain upstream processes will impact your downstream and will impact your safe filling. But all of these slots, if they are under the same umbrella—if the same CDMO was doing your drug substance and your drug product—then obviously they will make adjustments to the timelines.”

“On the other hand, while large pharmas are capable of a huge amount of expansive capacity, they often don't have open capacity, and they want to pursue multiple molecules in their portfolio without having to invest on new capacity,” she continued (6). “So outsourcing is really the only way to get to fast clinical studies, even for the large biopharma [companies].”

Aragen’s COVID lightbulb moment paid measurable dividends, according to Tandon.

“The customer estimates that for each one of those candidates, by virtue of this process that we have put together, we have essentially shaved off about 12 to 15 months each in that whole cycle, from when you first look at target identification all the way to development and candidate nomination,” he said.

One newer focus in expediting drug development is addressing the youngest patient population, according to McQuaid, and that brings its own set of challenges.

“There's a growing demand for age-appropriate formulations, pediatric drug presentations, so we have to invest and try and get ahead in those areas,” he said (6). “When you look at the cell and gene therapies and biologics, they bring requirements. So, we're investing in storage and pack, label, and distribution solutions for cold chain products, ultra-low temperature products.”

And when time is of the essence, it may not be the most expeditious approach to have one single company handle everything; however, choosing a partner that has demonstrated experience in as many key areas of development as possible is a wise decision.

“It's really accelerated time to market that's certainly in the development sphere, that's what we hear,” McQuaid said (6). “It's definitely true that if you can bundle activities, if you can leverage a connected network of internal experts within the CDMO, you can eliminate risk, you can eliminate downtime.”

“CDMO-sponsor relationships will continue to evolve as sponsors look for regional global distribution, licensing, and commercialization partners,” Cornog said. “While it does support accelerating time to broader commercial markets, these partnerships also provide insight back into the development stages for incorporating region-specific regulatory requirements and mitigating any future post-approval changes.”

Geopolitical shifts change what clients want

The tariff policies of United States President Donald Trump’s administration have been the impetus for an entirely separate trend, albeit one whose story is not yet fully told, and won’t be as long as tax rates continue to be tweaked, imposed, or revoked.

Companies based in the US are taking a look at what services they can onshore or reshore, and companies with headquarters elsewhere in the world are rethinking their stateside relationships.

“We're also seeing an increase in demand for on- and near-shoring manufacturing,” Patel said. “Not only does it provide the customer leaner management and logistics, but it also means that they have minimal exposure to geopolitical shifts that they're seeing today.”

Cornog concurred, saying that Quotient Sciences is seeing evidence of the same pattern and that alliances close to home can have particular advantages.

“Having local partners means sponsors can better manage their risk and supply chains, avoiding disruption from geopolitical instability and tariff fluctuations while achieving better regulatory alignment and a more stabilized cost structure,” he said.

Tandon said China is a major area of focus after the Trump White House zeroed in there, as well as on Canada and Mexico.

“From a geopolitical standpoint, a lot of customers are looking for a non-China alternative,” Tandon said. “We've had a lot of global pharma companies, a lot of biotechs that historically have not really worked with service providers in India, come in and do a first round of projects, and many of them have scaled up with companies such as ours.”

The words “supply chain” became a somewhat dreaded refrain at various points of the COVID-19 pandemic, but in the bio/pharmaceutical industry, keeping the pipeline moving effectively has always been a top objective. And if turning to outsourcing keeps sponsor companies running as cleanly as they can, according to McQuaid, then they are in favor of it. Plus, he said, having the right amount of drug in the right place at the right time is the ultimate goal.

“We definitely see more and more clients with a really strong preference to co-locate manufacturing, packaging, release testing, and then the final QA [quality assurance] release and batch release capabilities,” he said (6). “I think for them, that reduces the supply chain burden on themselves, having to manage all those different factors. It can have a financial return in terms of reducing inventory levels—not having to have safety stocks in so many different places—and ultimately, simplifying and de-risking the supply chain.”

At the same time, quality standards, regulatory landscapes, and the challenges of new technologies also continue to evolve along with market demands. This includes the rise of the use of AI, which Khambhampaty said can certainly benefit from checks and balances.

“Now, with the advent of AI-based drug discovery, there are a lot of smart scientists who are coming up with designer medicines and virtual labs,” she said. “They do need to find a CDMO to develop their concept to reality.”

“I think ultimately, the clients and pharma companies are seeking best-in-class services,” McQuaid said. “So, I think as CDMOs, we have to be cognizant of that. I think we have to be very transparent about our specialisms. What are our strong points? And if there's an area that we can't do, we need to be upfront about that. No one wants to be experimenting on their product.”

Choosing to collaborate with a CDMO is a step more and more sponsor companies have been making in an attempt to speed up timelines of certain drugs they have in development without sacrificing quality. To ensure that, selecting a partner that not only has a flexible knowledge base, but can also reliably deliver on that expertise, is a crucially important decision that neither side of the equation is taking lightly.

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Outsourcing in the bio/pharmaceutical industry is evolving, driven by technological advancements and changing customer demands. The relationship between sponsor companies and CDMOs is shifting from transactional to strategic partnerships, emphasizing integrated, long-term collaborations. The rise of novel modalities, AI, and personalized medicines is reshaping the landscape, necessitating flexible and modular services. Geopolitical factors are influencing onshoring trends, while strategic alliances focus on accelerating time to market. CDMOs are adapting by offering comprehensive services, leveraging expertise, and ensuring supply chain efficiency to meet the growing demand for innovative drug development.

While a one-stop shop still has its advantages, sponsor companies and CDMOs are starting to see each other not as transactional relationships, but true partners with a common goal of getting drugs to patients faster.

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