Over-Extraction in Medical Device Testing – The Hidden Risk of Following the Rules Too Closely

Why does Over-Extraction Mislead Results?

ISO 10993-18 defines the framework for chemical characterisation of medical devices. The intention is clear: to protect patients by identifying potential leachables and extractables. In practice, however, the outcome of testing often depends heavily on the selected extraction approach. Standardised solvent-based methods can yield results that differ significantly from what occurs during actual clinical use. Strong solvents such as ethanol or hexane are able to extract high-molecular-weight compounds and penetrate deeply into polymer matrices, processes that do not reflect physiological reality. Materials like HDPE may therefore appear “toxic” under laboratory conditions, although patient exposure under normal use is negligible. 

How do Solvents Affect Outcomes?

To address such discrepancies, we harmonised methods and combined best practices from multiple laboratories. This approach substantially reduced interlaboratory variability. For comparison, a recent study reported differences in extractable profiles of up to 240% under nominally identical conditions. By introducing a unified fragment database, method-specific protocols, and explicit uncertainty factors for the Analytical Evaluation Threshold (AET), reproducibility and comparability improved, providing a more robust basis for safety evaluations. 

Why do Extraction Parameters Matter?

Extraction parameters themselves are equally decisive. Duration, temperature, and solvent-to-surface ratios can alter the extractable spectrum dramatically. Even relatively small deviations, such as performing the test at 50 °C instead of 37 °C, can inflate results several-fold. Quite often, we at SGS receive urgent requests to conduct an extraction study on short notice, as the previously generated extraction profile failed to meet the requirements. In many cases, this is due to the wrong extraction technique that was chosen by the sponsor in the initial request. Designing scientifically justified extraction studies is therefore not trivial. Without experience, even minor adjustments can lead to major discrepancies. 

How does Over-Extraction Impact Submissions?

Beyond inflated extractable profiles, over-extraction causes another serious issue: replicate analyses cannot be meaningfully aligned. Instead of generating consistent datasets, degradation products broaden the outcome. In the case of triplicates, this may result not in confirmation of reproducibility but in three divergent datasets. The regulatory implication is significant: authorities receive a report with a wide variety of degradation products that do not appear reconcilable. This undermines confidence in the study, raises doubts about the validity of the extraction conditions, and creates a credibility risk for the entire submission. A more thoughtful design from the outset avoids such inconsistencies, ensuring coherent data and a credible report. Otherwise, companies face repeat testing, wasted resources, and potentially delayed approvals due to rework. These are not abstract concerns but concrete business consequences that should be avoided.

How Precise is LC-MS Quantification?

Another underestimated challenge lies in the measurement uncertainty of LC-MS itself. Typically, uncertainty is calculated statistically across the different response factors of diverse analytes. In practice, the relative standard deviation (RSD) obtained for a statistically significant number of analytes with diverse chemical structures almost always exceeds 1. This implies an uncertainty greater than 100%, which makes it mathematically impossible to calculate a meaningful uncertainty factor (UF). As a fallback, a default UF of 10 is often applied. However, according to ISO 10993-18 (2020), such uncertainty levels mean that no toxicological risk assessment (TRA) can reliably be performed based on these values. This limitation is in stark contrast to the regulatory expectation: since the FDA recommendation of 20 September 2024 (“Chemical Analysis for Biocompatibility Assessment of Medical Devices”), LC-MS has been highlighted as a preferred standard method. In reality, though, the intrinsic variability makes it unsuitable for quantification in its raw form. Alternative approaches are required. Our solution is to apply a scientifically justified model based on comparable compound classes for quantification. By anchoring unknowns to structurally and analytically similar compounds, the uncertainty of quantification shrinks significantly – restoring the reliability of LC-MS as a decision-support tool in chemical characterisation. 

What do Regulators Expect Today?

Regulators are increasingly aware of these challenges. Both the FDA and European notified bodies expect extraction conditions to be clinically justified, rather than following prescriptive protocols without context. Effective communication between regulators and applicants is essential but often insufficient. As a result, companies sometimes initiate broad analytical programs prematurely, without considering how aggressive solvents may degrade polymer materials. The outcome is predictable: hundreds or even thousands of peaks are identified, many of which reflect only solvent-induced artifacts rather than clinically relevant risks.

How can Leaders Avoid Delays?

Over-extraction misleads rather than informs. Chemical characterisation should focus on clinically relevant outcomes, not artifacts of aggressive laboratory conditions. Applying a risk-based approach, supported by practical experience, performing the right assumptions for the evaluation of the results and open communication with regulators, ensures that results are consistent, meaningful, and defensible. This protects not only patients but also the credibility of the data package, avoids unnecessary retesting, and prevents costly approval delays.

References

• PubMed https://www.sciencedirect.com/science/article/abs/pii/S0731708524005387?via%3Dihub
• PubMed https://www.sciencedirect.com/science/article/abs/pii/S0273230022000514?via%3Dihub

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