Non-Targeted Identification of Extractables and Leachables from Medical Device Polymers Using ESI and SICRIT-LC/QTOF with LabSolutions Insight Profiler

Significance of the topic

Extractables and leachables (E&L) from polymeric medical devices can present toxicological risks and therefore require comprehensive chemical characterisation to support biological risk assessment and regulatory compliance (e.g., ISO 10993 series). Non-targeted high-resolution mass spectrometry workflows improve the chance of detecting unexpected or low-abundance migrants from device materials and processing aids, enhancing patient safety and material qualification.

Objectives and study overview

• Demonstrate a non-targeted LC/QTOF workflow to identify extractables and leachables from four medical polymer foams (mattress, silicone foam, polyesterurethane, polyetherurethane) extracted in water or isopropanol.
• Compare conventional electrospray ionization (ESI) with a dielectric-barrier discharge soft ion source (SICRIT DBDI) to expand detectable chemical space.
• Automate feature detection, alignment and suspect/library screening using LabSolutions Insight Profiler with public and commercial compound lists and spectral libraries.

Methodology

• Sample preparation: Five technical replicates per polymer and solvent; blanks prepared with the same solvents for background comparison.
• Chromatography: UHPLC separation on a C18-type column with a gradient from 20% to 100% methanol (0.1% formic acid in water as A), 0.4 mL/min flow, 40 °C, small injection volume (0.5 µL) and solvent rinse to minimise carryover.
• Mass spectrometry: LC coupling to a QTOF (LCMS-9050) acquiring TOF MS and data-independent acquisition (DIA) MS/MS over m/z ranges covering low to intermediate masses; both positive and negative ion modes were used.
• Ionization strategies: Direct comparison of ESI and SICRIT (DBDI) to capture polar and non-polar analytes respectively; SICRIT promotes multiple gas-phase ionisation pathways (proton transfer, radical cation formation, charge-transfer/photoionization) to enhance coverage of hydrophobic compounds.
• Data processing: LabSolutions Insight Profiler executed a single batch workflow for feature detection, alignment, statistical filtering (features required in ≥4/5 replicates for further consideration), suspect screening and MS/MS library searching. Suspect lists included the ELSIE list (EPA CompTox), FDA-CLAP and NIST 2023; spectral matching used NIST 2023 and MassBank.

Instrumentation used

• UHPLC: Nexera X2 with a Shim-pack XR-ODS III column (2.0 × 150 mm, 2.2 µm); column oven 40 °C; flow 0.4 mL/min; mobile phases water + 0.1% formic acid and methanol; gradient to 100% B over ~8–18.5 min.
• QTOF mass spectrometer: LCMS-9050 acquiring TOF MS (m/z 70–1250) and DIA MS/MS (m/z 40–1250) with 41 windows (~35 Da isolation), collision energy spread 5–55 V, total cycle ~1.125 s.
• Ion sources: Conventional ESI (± ~4.5 kV, interface ~300 °C) and SICRIT DBDI (1.8 kV, ~4.5 kHz, interface ~500 °C) to compare ionization response across chemical classes.
• Software/databases: LabSolutions Insight Profiler for automated batch processing; suspect screening against ELSIE, FDA-CLAP; spectral libraries NIST 2023 and MassBank for MS/MS confirmation.

Main results and discussion

• Distinct E&L profiles were observed across foam types: mattress, polyesterurethane and polyetherurethane were dominated by common polymer additives (antioxidants, plasticisers, amines, fatty acid amides, slip agents, flame retardants, surface modifiers), while silicone foam was dominated by cyclic and linear siloxanes plus other additives.
• Using LabSolutions Insight Profiler enabled integrated feature detection, alignment and suspect/library screening in a single automated batch, with reproducibility filtering (≥4/5 replicates) and volcano-plot comparisons versus blanks to prioritise relevant signals.
• MS/MS library matching (NIST 2023, MassBank) increased reporting confidence for identifications such as hindered phenolic antioxidants (Irganox-type), fatty acid amides (erucamide, oleamide), surfactants (N‑lauryldiethanolamine), plasticisers (dibutyl adipate, diisodecyl phthalate) and cyclic siloxanes (e.g., deca-/tetra-/hexa-methylcyclo-siloxanes).
• SICRIT extended analytical coverage into lower-polarity and intermediate m/z ranges and improved detection of hydrophobic E&L compounds that gave poor ESI response. Examples with markedly higher response in SICRIT included Irganox 1135, tetradecamethylcycloheptasiloxane, 2,6-di-tert-butyl-4-methoxyphenol and dibutyl adipate.
• Comparison to blanks identified signals uniquely present in extracts, supporting the differentiation of true E&L compounds from background contaminants and solvent-born artefacts.

Benefits and practical applications

• Single-method automated processing streamlines non-targeted E&L screening, reducing manual data handling and improving throughput for screening campaigns.
• Combining complementary ionisation techniques (ESI + SICRIT) increases chemical coverage, particularly for mid-to low-polarity migrants that may be missed by ESI alone.
• Integrated suspect screening against curated lists and spectral library matching supports prioritisation of analytes for follow-up identification, risk assessment, and potential quantitation.
• Workflow is applicable to material compatibility testing, product release screening, investigation of unexpected clinical failures, and regulatory submissions requiring material characterisation per ISO 10993-18.

Future trends and potential applications

• Broader adoption of hybrid ion sources and multilayered ionization strategies (ESI, DBDI, APCI, etc.) to maximise detection of structurally diverse migrants.
• Standardisation and harmonisation of suspect lists and reporting thresholds to aid inter-laboratory comparability and regulatory acceptance of non-targeted E&L workflows.
• Increased use of DIA strategies combined with expanding high-resolution spectral libraries and machine-learning algorithms to improve automated identification confidence and reduce false positives.
• Development of quantitative follow-up methods (targeted LC-MS/MS) for prioritized E&L findings and linking chemical identification to toxicological assessment and extractables/leachables risk models.
• Integration of ambient ionisation and non-chromatographic approaches for rapid surface screening and targeted follow-up of high-risk compounds.

Conclusion

A combined LC/DIA-QTOF strategy using complementary ion sources (ESI and SICRIT DBDI) and automated batch processing with LabSolutions Insight Profiler provides a robust, higher-coverage non-targeted workflow for identification of extractables and leachables from medical device polymers. SICRIT notably enhances detection of hydrophobic, low-polarity E&L species that may be under-represented by ESI, while integrated suspect screening and MS/MS library matching streamline prioritisation for toxicological assessment and regulatory reporting.

References

• Shimadzu application note: Non-Targeted Identification of Extractables and Leachables from Medical Device Polymers Using ESI and SICRIT-LC/QTOF with LabSolutions Insight Profiler, Shimadzu Corporation, 2026 (05-SCA-210-100-EN).
• NIST 2023 Mass Spectral Library.
• MassBank spectral repository.
• EPA CompTox Chemicals Dashboard — ELSIE chemical list.
• FDA Center for Devices and Radiological Health — CLAP (FDA-CLAP) suspect lists.