Analytical Strategies for Aseptic Processing

Aseptic processing must be conducted in a manner that assures sterility (1). Analytics play an integral role in each step of an aseptic process as they are required to properly characterize the product and assess and understand its safety profile and quality to ensure they align with strict regulatory standards (2). Raw materials and buffers must be tested, utilities (steam/gas, water-for-injection) are routinely monitored, and a wide variety of analyses are performed during formulation/compounding and fill/finish activities, including pre-use post-sterilization integrity testing (PUPSIT), and pre/post-use filter integrity tests, environmental monitoring, and container closure integrity (CCI) testing.

The degree of analytical testing varies from one unit operation to another based on process step criticality, time limitations, scale of production, and product application, according to Rajiv Gangurde, vice-president, technical operations, cell and gene therapy at Parexel. Some testing, notably environmental monitoring, is performed in advance of process initiation as a preventive measure. Quality control (QC) release testing confirms sterility, endotoxin levels, particulates, identity/purity/potency, and CCI.

What analytical methods are widely used during aseptic processing?

Several analytical techniques are used during aseptic processing. Marie-Sophie Quittet, Strategic Projects Manager at Adragos Pharma, highlights the following:

• Raman and near-infrared spectroscopy deliver fast, non-invasive identification and concentration verification for raw materials, buffers, and protein solutions, reducing both cycle times and sampling risk.
• Tunable diode laser absorption spectroscopy and other related laser headspace analytics enable quantitative, 100% residual oxygen/moisture checks, which is tightly linked to product stability and CCI performance.
• Deterministic CCI (high-voltage leak detection, vacuum/pressure decay) provides sensitive, scalable integrity testing with strong regulatory acceptance.
• Automated visual inspection, increasingly aided by advanced image analysis, yields consistent particle/defect detection with lower false rejects versus manual inspection.
• Biofluorescent particle counters add near-real-time viable air insight to complement traditional environmental monitoring.
• Core QC methods including high-performance liquid chromatography (HPLC)/ultra-performance LC, ultraviolet-visible, osmolality, pH, total organic carbon, and sub-visible particle analysis such as micro-flow imaging, remain indispensable for product release, providing specificity and precision for identity, purity, potency, and particles across small-molecule and biologic injectables.

How do regulations drive analytical strategies?

Regulations set the framework and pace of adoption of analytical methods and technologies, according to Quittet. That is why, notes Scott Goldstein, vice president of strategic partnerships with Argonaut Manufacturing Services, a strong quality and regulatory team is instrumental in assuring the facility, analytical technologies and environmental monitoring are aligned with constantly changing regulatory requirements for aseptic processing.

As an example, Quittet points out that Annex 1 of the European Union’s good manufacturing practice guidelines (3) emphasizes a holistic contamination control strategy, using barrier technologies, continuous environmental monitoring, PUPSIT, trending, and strong data integrity, which all drive closed, real-time analytical methods. In the United States, FDA’s aseptic processing guidance (1), ISO 14644 (4), and the Pharmaceutical Inspection Co-operation Scheme (PIC/S) (5) reinforce cleanroom classification, environmental monitoring, and process control basics.

Method validation and lifecycle management are governed by the International Council for Harmonisation’s (ICH) Q2(R2)/Q14 (6), while ICH Q8–Q10 (7) and Q9(R1) (8) emphasize quality-by-design (QbD) and risk management. United States Pharmacopeia (USP) chapters—<71> sterility (9) and <85> endotoxin including recombinant Factor C as a validated alternative (10), <787>/<788> particulates (11,12), <1207> CCI (13), <1223> rapid microbiological methods (14), and <1229> sterilization (15)—define baseline expectations.

“Regulators expect scientific justification for alternative/rapid methods, robust electronic records and cybersecurity, meaningful trending with timely action, and formal governance for models/algorithms within validated, change-controlled systems, including periodic performance verification and management review,” Quittet concludes.

What are the essential attributes of analytical methods used in aseptic processing?

The essential attributes of analytical techniques used for release, characterization, in-process control(s), and stability testing during aseptic processing of drug substances (DS) and drug products (DP) that ensure both high performance and regulatory compliance can be, says Gangurde, divided into three main categories. The methods used should be reliable, robust, reproducible and amenable to method qualification and validation; selected and developed to assess safety, quality and efficacy; and include the use of appropriate reference standards and materials, particularly for determining critical attributes such as titer and potency of the DP. Furthermore, methods must minimize the risk of sample contamination, while delivering fast, reliable decisions, Quittet observes.

According to Quittet, preferred attributes should:

• include closed or noninvasive operations that are compatible with isolators/restricted access barrier systems (RABS), single-use assemblies, and exposure to vaporized hydrogen peroxide (VHP)/H₂O₂
• be rapid or provide real-time results with sensitivity and specificity matched to the critical attribute (e.g., headspace oxygen, sub-visible particles, low bioburden/endotoxin) and robust against matrix effects and process drift
• integrate seamlessly with supervisory control and data acquisition/DCS distributed control system/manufacturing execution system/electronic batch manufacturing record, enabling automated, secure data capture, and alarm management
• be maintainable in Grade A/B conditions, resilient to cleaning/decontamination, scalable across sites, and supported by credible vendors with global service and spares.

What factors are important when selecting and transferring methods for aseptic processes?

Method selection primarily depends on the quality and efficacy requirements of the material/product in question. Other important factors, according to Gangurde, include ease of development, tech-transfer requirements, availability and procurement of raw materials, and the equipment needed. He also notes that wherever applicable, orthogonal methods should be selected and applied.

Leveraging experience to determine the optimal starting point can be a real differentiator in assuring appropriate methods are identified and evaluated prior to method development and qualification of analytical testing, according to Goldstein.

When transferring a method, there are additional considerations. “When a drug developer is transferring a method to a contract manufacturer, it has the responsibility to ensure the method is robust and accurate and able to detect any stability issues, anticipate any problems that may exist or arise with the method, and be confident the contract manufacturer has the ability to effectively implement it,” explains Quittet.

Which advances are enhancing the monitoring and control of aseptic processes?

The pharmaceutical industry is highly innovative, and numerous advances in both general technologies and specific analytical techniques are helping to improve the monitoring and control of aseptic processes.

With respect to more general developments, Gangurde points to single-use systems, which eliminate the need for extensive cleaning and sterilization between batches and minimize cross-contamination risks; barrier isolators and restricted access barrier systems, which create physical barriers to minimize microbial contamination; microfluidic devices, which enable rapid microbial detection, supporting real-time decision-making and reducing operational bottlenecks (16); and process analytical technologies, which enable real-time monitoring and control of critical process parameters and integration of QbD design principles into manufacturing (17). Real-time monitoring of cleanrooms (18) and use of big-data analytics (19) are also providing invaluable insights.

“These and other advancements collectively improve the efficiency, sterility, and safety of aseptic processes in biopharmaceutical manufacturing,” contends Gangurde.

Goldstein highlights some specific techniques as being highly impactful. “Real-time viable and non-viable particulate monitoring has been key to assessing issues that might arise during aseptic processing and allows for quicker and more efficient investigation techniques,” he notes. “In addition, fully automated sampling allows for drastic reduction in potential operator contamination during these sampling steps, helping to speed up the process and release of the product while assuring the highest level of quality,” he continues. Automation and digitalization of analytics for aseptic processing are also supporting more rapid testing (17).

What role will AI and ML play in aseptic processing analytics?

AI and machine learning (ML) not only will be important for the future of aseptic processing analytics; they are already in use today. For instance, AI has started to become integrated into filling lines, according to Goldstein, but is not yet making an impact with QC techniques. Both AI and ML are being used to improve monitoring and control of aseptic processes, Gangurde agrees. AI-driven predictive maintenance, automated environmental monitoring, and process control applications are prime examples.

In the latter case, ML is being used to optimize process parameters in real-time, providing data on product quality. Operators can also simulate and test process changes before implementation, which helps with tech-transfer, adaptation, and scaling of processes (20). In addition, ML is being applied in visual inspection systems, notes Quittet, where it is used to limit the rejection rate of good vials and accelerate the release of product batches.

Companies such as GlaxoSmithKline, Pfizer, Merck, Rocher, and Novartis have all implemented AI-driven programs in aseptic processing applications (21).

Looking forward, Gangurde believes an increased dependence on AI and ML is inevitable, as both can improve the overall process of drug development to bring therapies to patients in need. “AI will make a big impact in the automation of aseptic processes and minimizing risk to the patient,” Goldstein adds.

References

1. FDA. Guidance for Industry: Sterile Drug Products Produced by Aseptic Processing —Current Good Manufacturing Practice (Rockville, MD, November 2004).
2. O’Connor, R. Aseptic Processing: A Primer. BioPharm International 2023 26 (1). https://www.biopharminternational.com/view/aseptic-processing-primer
3. EC. Annex 1, Manufacture of Sterile Medicinal Products. EudraLex, The Rules Governing, Medicinal Products in the European Union. Volume 4, 2010.
4. ISO. ISO 14644-1:2015 Cleanrooms and Associated Controlled Environments Part 1: Classification of Air Cleanliness by Particle Concentration, Edition 2, 2015. https://www.iso.org/standard/53394.html
5. PIC/S. PIC/S Guide to Good Manufacturing Praxtice for Medicinal Products Annexes, Annex 1 (Manufacture of sterile medicinal products) July 2018. https://www.fda.gov.ph/wp-content/uploads/2022/12/PE-009-14-GMP-Guide-Annexes.pdf
6. ICH. Q14 Anaytical Procedure Development, Q2(R2) Validation of Analytical Procedures Step 2 version (ICH. 2022).
7. ICH. Q8, Q9, Q10, Questions and Answers Volume 4 (ICH, 2010).
8. ICH. Q9(R1) Quality Risk Management Step 5 version (ICH, 2023).
9. USP. General Chapter <71>, Sterility Test. USP–NF (US Pharmacopeial Convention, Rockville, MD, 2009).
10. USP. General Chapter <85>, Bacterial Endotoxins. USP–NF (US Pharmacopeial Convention, Rockville, MD, 2017).
11. USP. General Chapter <787>, Subvisible Particular Matter in Therapeutic Protein Injections. USP–NF (US Pharmacopeial Convention, Rockville, MD, 2014).
12. USP. General Chapter <788>, Particulate Matter in Injections. USP–NF (US Pharmacopeial Convention, Rockville, MD, 2007).
13. USP. General Chapter <1207>, Sterile Product Packaging–Integrity Evaluation. USP–NF (US Pharmacopeial Convention, Rockville, MD, 2016).
14. USP. General Chapter <1223>, Validation of Alternative Microbiological Methods. USP–NF (US Pharmacopeial Convention, Rockville, MD, 2015).
15. USP. General Chapter <1229>, Sterilization of Compendial Articles. USP–NF (US Pharmacopeial Convention, Rockville, MD, 2022).
16. Mirasol, F. How Miniaturized Analytics Are Transforming Aseptic Bioprocessing Control. BioPharm International, 2025 38 (8). https://www.biopharminternational.com/view/how-miniaturized-analytics-are-transforming-aseptic-bioprocessing-control
17. Challener, C.A. Advances in Digitalization and Automation of Aseptic Processing. Pharmaceutical Technology, 2025, 49 (8), pp. 18-20. https://www.pharmtech.com/view/advances-in-digitalization-and-automation-of-aseptic-processing
18. Spencer-Jolliffe, N. Continuous Monitoring Expands Aseptic Knowledge and Data in Real Time. Pharmaceutical-Technology.com. April 3, 2024. www.pharmaceutical-technology.com/features/continuous-monitoring-expands-aseptic-knowledge-and-data-in-real-time/
19. Advanced Analytics: Driving Cleanroom Excellence in Pharmaceutical Manufacturing. Cleanroom Technology, July 12, 2024. https://cleanroomtechnology.com/advanced-analytics-driving-cleanroom-excellence-in-pharmaceutical-manufacturing
20. Vuolo, M.; Koeth, C.; and Wherry, R.J. Enhanced Intervention Detection in Aseptic Fill Using AI/ML. ISPE Pharmaceutical Engineering, 2023, May/June. https://ispe.org/pharmaceutical-engineering/may-june-2023/enhanced-intervention-detection-aseptic-fill-using-aiml
21. “How AI & Machine Learning Are Transforming Aseptic Processing,”Blog post. https://www.vonlanthenevents.com/en/ai-transforming-aseptic-processing (accesssed Jan. 15, 2025).