When it comes to ensuring the safety of medical and pharmaceutical products, chemical characterization plays a key role, particularly through the analysis of extractables and leachables (E&L). A persistent challenge in this work is the significant variability in how different compounds respond during mass spectrometry (MS) analysis, making accurate quantitation both difficult and error-prone. This webinar explores how machine learning can predict relative response factors to improve quantitation accuracy and accelerate decision-making in E&L assessments.
Differences in physicochemical properties often lead to inconsistent detector response across compounds in LC/MS positive and negative ion modes, as well as GC-MS/MS workflows. Traditional response-factor estimation often relies on extensive empirical testing, which can delay development timelines and reduce efficiency in complex mixture analysis.
This webinar will examine how neural network models developed from compounds spanning diverse chemical properties can improve response-factor prediction and strengthen analytical confidence. The featured speakers will discuss practical modelling approaches, real-world applications and considerations for integrating predictive tools into E&L workflows to support more consistent quantitation strategies and regulatory alignment.
Register for this webinar to learn how machine learning response factor prediction improves E&L quantitation accuracy and strengthens analytical decision-making.
Speakers
Dr. Michael Louis, Scientific Director, Jordi Labs, an RQM+ Company
Dr. Michael Louis is the Scientific Director at Jordi Labs, an RQM+ Company, specializing in extractables and leachables (E&L), chromatography and advanced materials characterization. With more than 15 years of experience across academic and CRO laboratories, he applies QTOF-LC/MS, QTOF-GC/MS, HS-GC/MS and complementary spectroscopic techniques to solve complex analytical challenges ranging from product failure investigations to unknown-identification and data-driven material assessments.
Michael leads technical strategy for E&L studies, method development and regulatory-aligned analytical workflows and is dedicated to driving innovation and contributing to Jordi’s thought leadership and publication efforts in QTOF, HS GCMS and driven material assessments. Michael leads technical strategy for E&L studies, method development and regulatory-aligned analytical workflows, and is dedicated to driving innovation and contributing to Jordi’s thought leadership and publication efforts.
Message Presenter
Adam Eason, Senior Biocompatibility Consultant, Jordi Labs, an RQM+ Company
Adam Eason is an expert in a variety of chemical testing, including extractables and leachables, as well as polymer testing. He has over 10 years of increasing responsibility in academic, government and CRO laboratories.
Adam has a proven track record solving customers’ product failure analysis on sample types ranging from polymer resins to football helmets and windshields. With the support of a team of PhD Chemists and access to top-of-the-line instrumentation, including QTOF-LC/MS, QTOF-GC/MS, thermal analysis and spectroscopy techniques, Adam is always able to answer a customer’s “why” questions.
Prior to his current role, Adam worked as a Senior Study Director and as an Organic Chemist in drug development. In addition, he has performed environmental chemical analysis in both government-owned labs and CROs.
Message Presenter
Who Should Attend?
This webinar will appeal to the following:
Primary titles:
- Biocompatibility Engineers
- Toxicologists
- Analytical Chemists (LC-MS / GC-MS focused)
- Extractables & Leachables Specialists
- Materials Scientists
- Product Developers / Engineers
- R&D Specialists
- Project Managers overseeing development programs
- Quality Control Scientists
- Study Directors overseeing E&L programs
- Regulatory Affairs Specialists supporting ISO 10993 submissions
Industries:
- Large/ medium Medical Device Manufacturers
- Combination Product Manufacturers
- Pharmaceutical companies (container closure / packaging teams)
What You Will Learn
Attendees will:
- Learn how mass spectrometry response factor variability causes errors in E&L assessments
- Discover how neural network models predict relative response factors for LC/MS and GC/MS to improve quantitation accuracy
- Understand the role of machine learning in accelerating the identification and assessment of complex mixtures and unknown compounds
- Explore expert strategies for integrating chemical characterization into more efficient, regulatory-aligned analytical workflows
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RQM+
RQM+ is The MedTech CRO, accelerating innovation to patient impact. Our tailored solutions deliver regulatory and quality expertise, FDA-recognized laboratory services, clinical trials, and reimbursement strategies across device types and therapeutic areas to bring life-changing technologies to patients — faster, safer, better.
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