The Quantitation Problem at the Heart of E&L Programs
Relative quantitation is the standard approach in extractables and leachables assessment (E&L) testing, and for good reason. Formal quantitation of every compound found in a medical device extract is neither cost-effective nor operationally feasible. But relative quantitation carries the inherent limitation of response factor variability. Two compounds at identical concentrations can produce dramatically different signals in mass spectrometry, and without a reliable way to account for that variability, quantitation errors compound into risk assessment gaps.
This webinar addresses that problem directly, presenting the science behind Lumo™, Jordi Labs’ machine learning framework for predicting response factors in LC/MS and GC/MS workflows.
What You’ll Learn
- Why mass spectrometry response factor variability creates quantitation errors in E&L programs
- How Lumo™ uses a multilayer perceptron neural network to predict response factors for LC/MS (positive and negative ion modes) and GC/MS
- How pre-classification by chemical substructure improves model prediction accuracy, and how built-in flagging keeps expert review in the loop for compounds outside the model’s confident range
- What the verification data set showed
- How ML-assisted response factor prediction reduces calibration burden, shortens turnaround time, decreases costs, and improves scientific defensibility across the E&L workflow
Who Should Watch
Biocompatibility engineers, toxicologists, analytical chemists working with LC/MS or GC/MS, E&L testing specialists, study directors, and regulatory affairs professionals supporting ISO 10993-18 submissions.
Lumo™ is a proprietary tool developed by Jordi Labs, an RQM+ company, and is applied within established E&L workflows. The methodology supporting Lumo™ has been published in the PDA Journal of Pharmaceutical Science and Technology.¹
References
1. Deng, Y., Grice, A., Louis, M., et al. (2026). Neural Network Prediction of Response Factors for Extractables and Leachables in Pharmaceuticals and Medical Devices. PDA Journal of Pharmaceutical Science and Technology. https://journal.pda.org/content/early/2026/01/30/pdajpst.2025-000061.1
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