LC/MS, LC/SQ
IndustriesPharma & Biopharma
ManufacturerAgilent Technologies
Importance of the Topic
Organic nonvolatile leachables from packaging or device components can compromise the safety and efficacy of ophthalmic drug products. Routine targeted screening in QA/QC laboratories ensures that potential extractables and leachables are detected and quantified at trace levels, protecting patient health and meeting regulatory requirements. Incorporating automated workflows and compliance features streamlines laboratory operations and enhances data integrity.
Objectives and Overview of the Study
This study aimed to develop and validate an automated targeted screening workflow for routine QC analysis of ophthalmic drug products using the Agilent LC/MSD XT and OpenLAB CDS. The approach focuses on identification and quantification of selected nonvolatile leachables, linking acquisition and processing methods to provide a fully compliant, 21 CFR Part 11–ready solution with minimal manual intervention.
Methodology
A set of eight leachable standards was selected based on prior high-resolution LC/Q-TOF data. Standard solutions were prepared in acetonitrile and mobile phase mixtures for spectral library creation. Ophthalmic formulations were diluted and centrifuged prior to analysis. A standard addition calibration was built using five concentration levels and an internal standard.
Instrumentation
- Agilent 1260 Infinity II LC system: binary pump (G7112B), vial sampler (G7129A), diode array detector DAD (G7117C).
- Agilent LC/MSD XT (G6135CA) with Agilent Jet Stream Source (G2735L) for SIM/SCAN acquisition in positive and negative modes.
- Agilent OpenLAB CDS Software v2.1 for data acquisition, processing, and compliance management.
Main Results and Discussion
System suitability tests demonstrated adequate retention, resolution, signal-to-noise ratio, and peak symmetry for key compounds. Automated targeted screening identified methyl-2-benzoyl benzoate and Irgacure 561 in the drug product by reference spectral matching and qualifier ion confirmation. Quantification via standard addition yielded concentrations of ~148.4 ng/mL and ~149 ng/mL respectively. Suspect screening against a custom NIST LC/MS library detected erucamide in the formulation. Custom calculators in OpenLAB CDS applied AET thresholds internally, avoiding data export and preserving data integrity.
Benefits and Practical Applications
- Streamlined workflows with linked acquisition and processing reduce manual handling and processing time.
- Combined UV, SIM, and SCAN data enhance confidence in compound identification and quantification.
- Built-in compliance tools—audit trails, e-signatures, and secure data storage—facilitate regulatory adherence.
- Custom calculators enable in-software AET assessment and automated reporting.
Future Trends and Possibilities
- Expansion of spectral libraries to cover broader classes of leachables and extractables.
- Integration with high-resolution MS and data analytics platforms for suspect and non-target screening.
- Use of machine learning to predict potential leachables based on polymer composition and formulation.
- Cloud-based data management for collaborative review and remote compliance monitoring.
Conclusion
The Agilent LC/MSD XT and OpenLAB CDS deliver a robust, automated workflow for targeted leachables screening in pharmaceutical QC labs. The method achieves reliable identification and quantification, while meeting stringent data integrity and compliance requirements. This approach enhances laboratory efficiency and supports confident decision-making in product safety assessments.
References
- Lateef, S. S. et al. Extractables and Leachables Detected in Ophthalmic Drug Products Using High-Resolution LC/MS/MS. Agilent Technologies Application Note, 2016.
- Glauner, T. et al. A Workflow for Target, Suspect, and Non-Target Screening by LC/MS Demonstrated for Water Treatment Effluents. ACS Symposium Series, 2016.
- Method Validation and Quality Control Procedures for Pesticide Residues Analysis in Food and Feed, SANCO/10684/2009, 2010.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.