Location: Salon Bonaventure, Hotel Level

Chris McCudden, Ph.D., DABCC, FACB, FCAC University of Ottawa Dr. McCudden is a Clinical Biochemist at the Ottawa Hospital in Ontario, Canada. He is a Professor and Vice Chair of the Department of Pathology & Laboratory Medicine at the University of Ottawa. He serves as the Deputy Chief Medical Scientific Officer and Medical Director of Informatics and Information Technology for the Eastern Ontario Regional Laboratory Association. He serves as Board Secretary for the Association for Diagnostics and Laboratory Medicine. Dr. McCudden's academic interests include automated chemistry, data analytics & machine learning, quality improvement, plasma cell dyscrasias, and audit and feedback for laboratory stewardship. Relevant Financial Disclosures (within past 24 months, reported on May 14, 2026) No relevant financial relationship(s) to disclose.

Summary:
Coding tools have progressed at warp speed, moving rapidly from syntax troubleshooting to autonomous multi-agent workflows, the potential for AI in programming is spectacular. People with experience writing programs will be curious about the capabilities of AI tools, those who don't write code will wonder if they should ever learn, and everyone will want to understand the risks and benefits. This workshop will focus on "Vibe Coding", using AI tools to rapidly develop, prototype, and iterate software. Participants will hear about and discuss the realm of the possible, explore different AI coding tools, and consider if, how, and when an AI-developed application should be developed securely, safely, and effectively. Through the workshop, the group will create a new application, tackling technical and validation challenges, while identifying and mitigating potential risks and failure modes.

Syllabus:

• Landscape of AI tools for coding: from chatbots to multi-agent frameworks
• Vibe coding, who, what, when, where, why, how
• Failure modes, ethics, risks
• Guardrails, best practices, and safety
• From idea to implementation, vibe coding an app

Objectives:

1. Differentiate vibe coding from traditional software development
2. Describe how AI tools can be used for coding
3. Identify risks and benefits of using AI to write code
4. Critically evaluate a vibe-coded application

Location: Montreal 4

Paula Ladwig, MS, MLS(ASCP) Mayo Clinic Paula M. Ladwig, MS, MLS(ASCP), is a Principal Developer with the Clinical Mass Spec Development Laboratory and an Assistant Professor in the Department of Laboratory Medicine and Pathology at Mayo Clinic in Rochester, MN. She has over 15 years of experience in LC-MS LDT development and validation. Her interests include the implementation of therapeutic drug monitoring of monoclonal antibody therapeutics by LC-MS methods. Relevant Financial Disclosures (within past 24 months, reported on Feb 27, 2026) No relevant financial relationship(s) to disclose.

Michelle R. Campbell, M.S., MLS(ASCP)MB(ASCP),SC(ASCP) Mayo Clinic Relevant Financial Disclosures (within past 24 months, reported on Jan 05, 2026) No relevant financial relationship(s) to disclose.

Summary

Liquid-chromatography mass spectrometry (LC-MS) is utilized in many larger clinical laboratories, reference laboratories or research laboratories for developing assays for new biomarkers, for analytes for which alternative technologies lack specificity, or for high volume assays requiring greater throughput. In the life cycle of a new assay, CLSI guidance documents are used by laboratory developed test (LDT) developers to meet regulatory and accreditation requirements during the design, development, validation and implementation of LDTs into the clinical lab setting. These same documents may also be useful for researchers to use for good practice study design, clinical trials and/or publishing study results. Since these consensus-driven documents are developed to be broadly applicable, they can be challenging to navigate, may not fully address technology-specific study design considerations, use terminology and examples not common to the general laboratory and may not be specific or applicable to LC-MS. In response, CLSI has undertaken a strategic re-envisioning of the Method Evaluation (formerly referred to as Evaluation Protocol) category of documents.

This workshop will showcase improvements that CLSI is implementing to improve the experience for those who utilize their documents. The presenters will provide before-and-after examples, in an interactive format with the audience, to demonstrate how CLSI can better support those who work with LC-MS technology. Finally, the workshop will also consist of interactive brainstorming between the presenters and audience on topics such as gaps seen with current CLSI documents and how researchers and LDT developers who utilize LC-MS may take advantage of the new CLSI model to propose new targeted or niche-scoped guidance, examples, and tools.

Syllabus

• Short overview of CLSI with a focus on guidance documents and tools specific for Method Evaluation and LC-MS technology.
• Exploration of the updated Method Navigator tool to showcase its utility as a resource to find CLSI guidance to support regulatory and accreditation requirements throughout the Test Life Phases Model.
• Introduction to a new framework for CLSI Method Evaluation guidelines designed to provide more concise, phase- and technology-specific guidance using examples for linearity and method comparison studies.
• Review of recently published Method Evaluation documents of interest to LC-MS researchers and LDT developers.
• Open discussion on applying CLSI guidance in practice and identifying opportunities for improvement to CLSI’s current Method Evaluation portfolio.

Objectives

1. Describe recent improvements in CLSI Method Evaluation documents and tools that support LC-MS users to include both researchers and developers of LDTs.
2. Compare historical CLSI guidance approaches with the new, targeted strategies.
3. Use the CLSI Method Navigator tool to identify guidance documents relevant to each phase of the laboratory test life cycle.
4. Identify gaps in current guidance and discuss opportunities to enhance CLSI guidance for LC-MS technology.
5. Develop targeted study designs for LC-MS using the updated CLSI framework.

Location: Montreal 5

	Margret Thorsteinsdottir, PhD University of Iceland Professor in Pharmaceutical Analytical Chemistry at the Faculty of Pharmaceutical Sciences, University of Iceland and R&D Director of ArcticMass LTd, Reykjavik, Iceland. Dr. Thorsteinsdóttir received her PhD from Uppsala University, Sweden in 1998. From 2000 to 2009 she was the managing director of Bioanalytical Laboratories at deCODE Genetics, Reykjavik, Iceland. She has extensive experience in development of analytical methods for metabolite profiling and quantification of clinical biomarkers in various biofluids utilizing chemometrics with the goal of improved clinical management of patients towards personalized patient care. Her current research interest includes studies of lipid metabolism in cancer cells and profiling plasma derived biomarkers for early detection of BRCA-related breast cancer. She is responsible for implementation of clinical mass spectrometry for support of diagnostics and therapeutic drug monitoring in collaboration with ArcticMass and the Landspitali University Hospital, Reykjavik, Iceland with major focus on quantitative targeted proteomics for clinical diagnosis. She is a principal investigator of the Icelandic Research Rannis projects, profiling metabolites for breast cancer diagnosis and search for novel biomarkers for early breast cancer diagnosis by metabolomics. Dr. Thorsteinsdóttir is a principal investigator for the Marine Biotechnology ERA-net project CYNOBESITY and the Horizon 2020 project MossTech, with the main task to isolate, identify and structurally characterize bioactive compounds from cyanobacteria, Icelandic mosses and liverworts. She is one of the founders of Females in Mass Spectrometry (FeMS), she is a vice-leader of the working group clinical significance and applications of (epi)lipidomics in the pan-European network, EpiLipidNET and vice-chair of the Nordic Metabolomics Society. Relevant Financial Disclosures (within past 24 months, reported on Mar 12, 2025) No relevant financial relationship(s) to disclose.
	Finnur Freyr Eiriksson, PhD University of Iceland / ArcticMass Relevant Financial Disclosures (within past 24 months, reported on Mar 04, 2026) No relevant financial relationship(s) to disclose.
	Mark Kushnir, PhD ARUP Institute for Clinical & Experimental Pathology Mark Kushnir is Scientific Director of Mass Spectrometry R&D at ARUP Institute for Clinical and Experimental Pathology and Adjunct Professor at the Department of Pathology, University of Utah School of Medicine. Mark received PhD in Analytical Chemistry from Uppsala University (Uppsala, Sweden); his main areas of interest include development, application and clinical evaluation of novel mass spectrometry based clinical diagnostic methods for small molecule, protein and peptide biomarkers. He is author/coauthor of over 110 scientific peer reviewed publications. Relevant Financial Disclosures (within past 24 months, reported on Apr 13, 2026) Salary ARUP Laboratories Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Using Generic Terms? NO Conflict mitigation NOT REQUIRED.

Summary

Syllabus

• Design of Experiments (DoE) – Get it right from the beginning
• Basic concept and assessment of DoE
• Optimization of sample preparation and LC-MS/MS clinical assay by DoE
• Evaluation of robustness of an analytical method by DoE

Objectives

1. Explain basic principles and concepts of experimental design.
2. Discuss different types of experimental designs.
3. Discuss interpretation of the results and implications of the findings.
4. Provide examples of experimental design application in the process of method development and evaluation.

Location: Montreal 6-8

	Salvatore Sechi, PhD NIDDK/NIH DR. Sechi is the program director for proteomics and systems biology at the NIDDK/NIH. His responsibilities include the oversight of a research program on the application of structural biology and proteomics to diabetes, endocrinology, and metabolic diseases. The structural biology component comprises studies that are aimed at characterizing the 3-dimensional structure and function of proteins, and studies related to folding, stability, and novel structure design. The proteomic component focuses on characterizing the proteome or subset of the proteome, with the main goal of furthering our understanding of disease etiology and pathophysiology. For this purpose, researchers within this program often aim to identify protein biomarkers and examine signal transduction pathways and networks. Typically, large-scale approaches such as protein arrays or mass spectrometry are applied within these types of projects. The samples used can include biofluids or biopsies from human specimens as well as animal and cell models. The portfolio also involves computational and bioinformatic studies that address proteomic issues as they relate to diseases of interest to the NIDDK. The systems biology program that Dr. Sechi manages comprises research projects that study how the higher-level properties of complex biological systems arise from the interactions among their parts. Within this new discipline, researchers often use high-throughput technologies (e.g., genomics, proteomics, epigenomics, and metabolomics) and integrate the resulting data sets to develop models of complex biological systems. Within this program, researchers aim to characterize molecular pathways that lead to diabetes and develop predictive models. Relevant Financial Disclosures (within past 24 months, reported on Feb 27, 2026) Stock/Bonds GE HealthCare Technologies, Merck, Organon, Pfizer, Viatris Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.
	Andy Hoofnagle, MD, PhD University of Washington Dr. Hoofnagle's laboratory focuses on the precise quantification of recognized protein biomarkers in human plasma using LC-MRM/MS. In addition, they have worked to develop novel assays for the quantification of small molecules in clinical and research settings. His laboratory also studies the role that the systemic inflammation plays in the pathophysiology of obesity, diabetes, and cardiovascular disease. Relevant Financial Disclosures (within past 24 months, reported on Feb 27, 2026) Grant/Research Support Waters, Inc. Discussing Products? YES, presenter will present educational content related to products/services of one or more ineligible company(ies) listed above. Using Generic Terms? YES Conflict mitigation IN PROCESS.
	Wei-Jun Qian, PhD PNNL Dr. Wei-Jun Qian is a bioanalytical chemist whose research centers primarily on the development and applications of mass spectrometry-based approaches for better quantify the dynamic changes in protein abundances and protein post-translational modifications in biological and clinical applications. Dr. Qian is currently a Staff Scientist at the Integrative Omics group in the Biological Sciences Division at PNNL, where he has worked since 2002. Dr. Qian has received several prestigious honors, including a National Institutes of Health Director’s New Innovator Award (2009), and a Presidential Early Career Award for Scientists and Engineers (PECASE) in 2011. His current research involves the development of chemical proteomic approaches for site-specific quantification of cysteine-based redox modifications and more sensitive selected reaction monitoring (SRM)-based targeted quantification techniques with applications in pancreatic islets, diabetes, and oxidative stress-related disease areas. In addition to research, Dr. Qian is actively involved in training and mentoring postdoctoral researchers and intern students. Relevant Financial Disclosures (within past 24 months, reported on Feb 27, 2026) No relevant financial relationship(s) to disclose.
	Jun Qu, PhD SUNY,Pharmaceutical Sciences Department Jun Qu is a professor in the Department of Pharmaceutical Sciences of SUNY-Buffalo, and the director of Proteomics and Pharmaceutical Analysis Group in NY Center of Excellence in Life Sciences. His research focus is the development of protein bioanalysis strategies, both on global and targeted level, for quantitative investigation of pharmaceutical/clinical systems. Qu lab is also one of the leaders in LC-MS-based characterization of protein drugs and their targets in pre-clinical models. Relevant Financial Disclosures (within past 24 months, reported on Jul 17, 2025) No relevant financial relationship(s) to disclose.
	Michael MacCoss, PhD University of Washington The focus of the MacCoss laboratory is in the development and application of cutting-edge mass spectrometry-based technologies for the analysis of complex protein mixtures. Dr. MacCoss’ primary area of expertise is in protein biochemistry, nanoflow liquid chromatography, mass spectrometry instrumentation, and computational analysis of mass spectrometry data. He has ~30 years of mass spectrometry experience that bridges the fields of protein mass spectrometry, isotope ratio mass spectrometry, and quantitative mass spectrometry. The MacCoss laboratory has been actively applying these tools to important areas of biology including but not limited to, the basic biology of aging, neurodegenerative disease, protein-protein interactions, insulin signaling, cancer, measurement of protein half-life, transcriptional regulation, characterization of post-translational modifications, proteogenomics, and clinical diagnostics. The MacCoss laboratory is widely known for its expertise in the development and support of proteomics software tools. This expertise in mass spectrometry and the support of open-source software tools will be critical to the success of this project. Dr. MacCoss has been actively involved in the scientific direction and management of NIH centers, program projects, consortia, and large quantitative proteomics data production efforts since he arrived at UW in 2004. The MacCoss lab has worked on proteomics application of the biology of aging for the last 20 years and has been working in the analysis of samples of relevance to Alzheimer’s disease for the last decade. The MacCoss lab has trained 15 Ph.D. students and 15 postdoctoral fellows. There have been 1000s of individuals who have attended the Quantitative Proteomics Courses co-taught by MacCoss lab personnel. Relevant Financial Disclosures (within past 24 months, reported on Feb 27, 2026) Consultant Fees ThermoFisher Scientific, Alnylam Grant/Research Support Agilent, Bruker, Sciex, Shimadzu, ThermoFisher, Waters Committee/Board/Advisory Board Talus Biosciences, Profound Therapeutics Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

Summary

Diabetes represents a collection of endocrine disorders with severe systemic complications, including type 1 diabetes, an autoimmune condition characterized by insulin deficiency. The disease pathogenesis, trajectory, and end-organ damage are variable from patient to patient. As a result, the precise and accurate quantification of proteins and peptides involved in diabetes will help facilitate research into disease pathogenesis and ultimately improve the diagnosis, prognosis, and therapeutic management of patients with diabetes. Unfortunately, most of the studies to date have relied on immunoassays, with little effort put into demonstrating the specificity of the reagents or the robustness of the assays. Furthermore, recent publications have highlighted the limitations of many commercial assays, including a failure to detect the intended target. Rigor and reproducibility could be substantially improved by applying mass spectrometry to the quantification of these biomarkers. Major improvements in sample preparation and instrumentation have made mass spectrometry–based targeted proteomics a highly reproducible methodology for detecting and quantifying proteins and peptides. In addition, the ability to quantify specific proteoforms provides insight into prohormone processing and post-translational modifications and creates an opportunity to identify and validate new biomarkers that can be used for disease stratification.

The NIDDK continues to fund several projects that aim to use targeted mass spectrometry to quantify human plasma/serum proteins and peptides of interest to the diabetes clinical research community. During this workshop, the presenters will provide an update on their recent progress toward this goal that have been made by the Targeted Mass spectrometry Assays for Diabetes and Obesity Research (TaMADOR) consortium, with a special focus on biomarkers important in type 1 diabetes.

Syllabus

• Detecting proteins and peptides in human serum and plasma
• Preparing samples for targeted proteomic analysis
• The role of antibodies and immunoprecipitation in LC-MS quantification of protein and peptide biomarkers
• Examples of assays that can be translated to clinical research or clinical care

Objectives

1. Outline the potential utility of biomarkers in clinical research and clinical care in diabetes
2. Provide the rationale for the use of LC-MS/MS methods in the quantification of peptide and protein biomarkers, including proteoform-specific biomarkers
3. List the advances in sample preparation and instrumentation that enable the development of assays to peptide and protein biomarkers in human serum/plasma
4. Identify the hurdles that exist for the development of novel protein and peptide biomarker assays
5. Demonstrate the reproducibility and robustness of LC-MS assays through inter-lab assessments.