The Use of Near-Infrared (NIR) Spectroscopy for Raw Material Identification by a Contract Pharmaceutical Manufacturer
Applications | 2007 | Thermo Fisher ScientificInstrumentation
Near-infrared (NIR) spectroscopy is increasingly promoted by regulatory guidance as a fast, non-destructive, and broadly applicable technique for raw material identification in pharmaceutical manufacturing. Implementing NIR for incoming material control directly addresses major operational pressures in production facilities: growing material diversity and volume, regulatory requirements for traceability and validated methods, and the need to reduce lab workload and turnaround times while maintaining GMP compliance.
This case study describes how Abiogen Pharma S.p.A., a medium-sized pharmaceutical manufacturer in Pisa, Italy, replaced time-consuming individual pharmacopoeial tests with a single Thermo Scientific Antaris FT-NIR analyzer for routine raw material identification. Main objectives were to reduce analysis time and cost, avoid hiring additional staff, streamline logistics and planning, and preserve regulatory compliance under GMP requirements (including raw material identification documented per Chapter 5.30 of the GMP guidelines). The study documents implementation choices, validation practices, measured time savings (with an example on metformin hydrochloride), and return on investment.
Abiogen evaluated three potential analyzer locations: warehouse (no sampling required per GMP), dispensing area (also no sampling but potential workflow interruption), and QC laboratory (specialist staff but sampling and transport needed). The company chose installation in the raw materials warehouse to maximize efficiency and avoid sample transfer steps. Key implementation steps included:
The deployed instrument was the Thermo Scientific Antaris FT-NIR analyzer (Fourier-transform NIR). Abiogen had prior experience with Thermo Scientific instrumentation (a Nicolet FT-IR and an Evolution UV-Vis) and leveraged vendor training and support services for implementation and operator qualification.
Abiogen reported substantial efficiency gains after implementing FT-NIR for raw material identification:
Practical advantages observed at Abiogen include:
Abiogen’s experience illustrates several broader trends and opportunities for NIR in pharmaceutical operations:
Implementing an FT-NIR analyzer for incoming raw material identification enabled Abiogen to meet GMP identification requirements while significantly reducing analysis time, operational costs, and laboratory workload. Locating the analyzer in the warehouse maximized efficiency by eliminating routine sampling steps, and a structured validation and governance approach ensured regulatory compliance. The investment delivered payback within approximately 18 months and positioned Abiogen to extend NIR use across the production line.
NIR Spectroscopy, Software
IndustriesPharma & Biopharma
ManufacturerThermo Fisher Scientific
Summary
Significance of the topic
Near-infrared (NIR) spectroscopy is increasingly promoted by regulatory guidance as a fast, non-destructive, and broadly applicable technique for raw material identification in pharmaceutical manufacturing. Implementing NIR for incoming material control directly addresses major operational pressures in production facilities: growing material diversity and volume, regulatory requirements for traceability and validated methods, and the need to reduce lab workload and turnaround times while maintaining GMP compliance.
Objectives and overview of the case study
This case study describes how Abiogen Pharma S.p.A., a medium-sized pharmaceutical manufacturer in Pisa, Italy, replaced time-consuming individual pharmacopoeial tests with a single Thermo Scientific Antaris FT-NIR analyzer for routine raw material identification. Main objectives were to reduce analysis time and cost, avoid hiring additional staff, streamline logistics and planning, and preserve regulatory compliance under GMP requirements (including raw material identification documented per Chapter 5.30 of the GMP guidelines). The study documents implementation choices, validation practices, measured time savings (with an example on metformin hydrochloride), and return on investment.
Methodology and implementation strategy
Abiogen evaluated three potential analyzer locations: warehouse (no sampling required per GMP), dispensing area (also no sampling but potential workflow interruption), and QC laboratory (specialist staff but sampling and transport needed). The company chose installation in the raw materials warehouse to maximize efficiency and avoid sample transfer steps. Key implementation steps included:
- Selection of initial spectral library: 10–11 representative APIs and excipients were imported to maximize early ROI; the library is continuously expanded and maintained.
- Staffing and governance: instrument supervisor in the chemical control department oversees validation and routine operation; warehouse staff trained to operate the analyzer with oversight.
- Validation and qualification: Abiogen developed a rigorous protocol for validation runs and instrument qualification to meet GMP expectations.
- Supplier and vendor support: Thermo Fisher provided pre-installation training in a demo lab, factory visits, and after-sales courses to support implementation and operator training.
Used instrumentation
The deployed instrument was the Thermo Scientific Antaris FT-NIR analyzer (Fourier-transform NIR). Abiogen had prior experience with Thermo Scientific instrumentation (a Nicolet FT-IR and an Evolution UV-Vis) and leveraged vendor training and support services for implementation and operator qualification.
Main results and discussion
Abiogen reported substantial efficiency gains after implementing FT-NIR for raw material identification:
- Time savings: For a representative raw material (metformin hydrochloride), hours spent on identification using conventional pharmacopoeial methods (AIC testing) rose from ~364 hours to ~1,095 hours annually between 2001 and 2006 due to increased volumes and batches. NIR analysis reduced the per-year identification hours for this material to approximately 48.5 hours in 2001 and about 146 hours in 2006, demonstrating a sizable relative reduction in analyst time versus classical methods.
- Throughput and scalability: The total number of different raw material batches handled by Abiogen roughly doubled over five years while the diversity of material types tripled. NIR allowed Abiogen to scale identification throughput without proportionally increasing lab headcount.
- Cost and ROI: Abiogen calculated a payback period of about 18 months for the Antaris investment, principally driven by avoided labor costs, reduced sampling and transport, and faster material release.
- Operational impact: Locating the analyzer in the warehouse eliminated the need to sample each container for testing, reduced handling and chemical reagent usage, and streamlined the incoming-material workflow. The warehouse placement required targeted training and the appointment of an instrument manager to ensure correct operation and compliance.
- Regulatory compliance: By validating the NIR method and maintaining a controlled spectral library, Abiogen met GMP expectations for raw material identification and traceability. The company followed regulatory guidance that recognizes NIR as a suitable technique for material ID and assay (e.g., EMEA guidance, European Pharmacopoeia, USP).
Benefits and practical applications
Practical advantages observed at Abiogen include:
- Marked reduction in analyst time per material and per container, accelerating material release.
- Avoidance of hiring additional QC personnel despite increasing sample volumes.
- Lower operational costs from reduced reagent use, less sample handling, and minimized transport between warehouse and lab.
- Improved planning and logistics since materials can be verified on arrival in the warehouse and integrated into production without delay.
- Centralized spectral library management supporting consistent, repeatable identifications across numerous APIs and excipients.
Future trends and potential use cases
Abiogen’s experience illustrates several broader trends and opportunities for NIR in pharmaceutical operations:
- Distributed NIR deployment: Installing multiple analyzers at strategic points in the production line (warehouse, dispensing, in-process control) can further reduce bottlenecks and enable near-real-time decision-making.
- Library expansion and chemometrics: Growth of validated spectral libraries and advanced chemometric models (classification and quantitation) will increase the share of materials and attributes analyzable by NIR.
- Supplier-side qualification and PAT integration: Combining supplier self-qualification, on-site NIR checks, and process analytical technology (PAT) can yield end-to-end material assurance with fewer destructive lab tests.
- Digital records and regulatory submissions: Standardized NIR validation packages and digital traceability records ease regulatory review for method replacements or variations.
- Automation and remote monitoring: Integration with laboratory information management systems (LIMS) and automated decision rules can reduce human intervention and further improve throughput while preserving audit trails.
Conclusion
Implementing an FT-NIR analyzer for incoming raw material identification enabled Abiogen to meet GMP identification requirements while significantly reducing analysis time, operational costs, and laboratory workload. Locating the analyzer in the warehouse maximized efficiency by eliminating routine sampling steps, and a structured validation and governance approach ensured regulatory compliance. The investment delivered payback within approximately 18 months and positioned Abiogen to extend NIR use across the production line.
Reference
- Chapter 5.30, Good Manufacturing Practice (GMP) guidelines.
- EMEA, Note for Guidance on the Use of Near Infrared Spectroscopy by the Pharmaceutical Industry and the Data Requirements for New Submissions and Variations.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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