August 1 is the deadline to register if you wish to receive printed course material on-site (if it is provided by the instructor(s)).
The Short Courses for MSACL 2025 will be held only In-Person.
Short courses will be from 8-16 hrs.
Continuing Medical Education (CME) is anticipated to be offered.
You MUST be registered for the conference in order to attend a Short Course. Short Courses have an additional fee.
Short Course Pricing (per HOUR):
EarlyBird by Jun 18, 2025
Regular after Jun 18, 2025
Late after Jul 23, 2025
über-Late after Sep 07, 2025
Industry
USD$45/h
USD$50/h
USD$60/h
CLOSED
Academic
USD$35/h
USD$38/h
USD$41/h
CLOSED
Student
USD$13/h
USD$16/h
USD$20/h
CLOSED
All courses are IN-PERSON only.
All short courses are anticipated to include Continuing Medical Education (CME) AMA PRA Category 1 Credit™. The amount of credit assigned to each course may be slightly less than the contact hours stated
due to hourly breaks.
*Note : You can take more than one course if they don't overlap. Use segment times listed under the course to coordinate.
Course Offering
Admin Alert: Two or more courses have the same place-order. This needs to be corrected to achieve a proper flow of the course profiles below.
Financial Disclosures (past 24 months as of Jan 29, 2025) Other Conflicts: Labcorp / Employee
Labcorp / Stock
The presenter will not mention or discuss Specific Products or Services of the company(ies) or technology listed above, or of ANY other ineligible entity, except in general, generic terms ensuring balance and impartiality.
Matthew Campbell, PhD Labcorp
Financial Disclosures (past 24 months as of Jan 29, 2025) Other Conflicts: Labcorp / Employee
The presenter will not mention or discuss Specific Products or Services of the company(ies) or technology listed above, or of ANY other ineligible entity, except in general, generic terms ensuring balance and impartiality.
General knowledge of laboratory operations and assay development.
Overview
This course is designed to enhance participants' understanding of how automation technologies can streamline laboratory workflows, improve efficiency, and ultimately lead to better patient outcomes. It addresses the common challenge of knowing where to begin with automation and which tools to use. Through practical examples, participants will identify key areas for automation, focusing on processes such as sample handling, analysis, and reporting, all aimed at increasing accuracy and reducing errors.
The course also explores the integration of electronic data within clinical laboratories, teaching participants common methods to connect data from analytical instruments to data management systems. This will support better decision-making and improve the accuracy of test results. Participants will learn how automation can help minimize pre-analytical errors, directly contributing to more reliable outcomes.
By the end of the course, participants will be equipped to apply automation technologies effectively in their own labs, optimizing workflows, and improving overall laboratory performance. Key topics include automated liquid handling systems, data flow, integrating equipment, and human-centered design to ensure reproducibility and reduce common errors. This course empowers participants to make informed decisions on automation, driving greater precision and efficiency in clinical settings.
Topics Covered
The typical clinical laboratory – manual & automated workflows.
Principles of automated liquid handling – advantages & best practices.
Programming basics – electronic data flow & positive identification.
Integrating equipment – joining together distinct systems.
Human-centered design – reducing common errors & ensuring reproducibility.
Tying it all together – reports & dashboards.
Objectives:
At the conclusion of this short course, the participant will be able to:
Define the key components of clinical laboratory workflows and automation.
Identify capabilities of automated liquid handling systems and troubleshooting strategies.
Discuss the flow of electronic data and integration of data management systems.
Develop an automation toolbox to optimize laboratory workflows.
Understand procedures and tools available to automate processes.
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.
Financial Disclosures (past 24 months)
: Not reported
Cory Bystrom, PhD Ultragenyx
Financial Disclosures (past 24 months)
: Not reported
Salary: Ultragenyx
Christopher Shuford, PhD Labcorp
Chris Shuford, Ph.D., is Associate Vice President and Technical Director for research and development at Laboratory Corporation of America in Burlington, North Carolina. Chris received his B.S. in Chemistry & Physics at Longwood University and obtained his Ph.D. in Bioanalytical Chemistry from North Carolina State University under the tutelage of Professor David Muddiman, where his research focused on applications of nano-flow chromatography for multiplexed peptide quantification using protein cleavage coupled with isotope dilution mass spectrometry (PC-IDMS). In 2012, Chris joined LabCorp’s research and development team where his efforts have focused on development of high-flow chromatographic methods (>1 mL/min) for multiplexed and single protein assays for clinical diagnostics.
Financial Disclosures (past 24 months as of Feb 05, 2025) Other Conflicts: Laboratory Corporation of America / Employee / Stock
The presenter will not mention or discuss Specific Products or Services of the company(ies) or technology listed above, or of ANY other ineligible entity, except in general, generic terms ensuring balance and impartiality.
The main goal of this course is to provide an interactive forum in which attendees will be introduced to critical aspects of clinical protein measurements.
The topics of this course will be templated on the framework of CLIS guidance document, C64: Quantitative Measurement of Proteins and Peptides by Mass Spectrometry.
The motivation for using mass spectrometry to quantify proteins in clinical research and in clinical care will be discussed as part of this interactive workshop. Technical topics uniquely affecting quantitative protein and peptides measurements by mass spectrometry will be a point of emphasis. Case studies from assay inception through validation will be presented and participants will work interactively to critique various aspects of clinical proteomic measurements.
Topics Covered
Protein vs Peptide Measurands
Workflows
Sample Preparation (Digestion & Enrichment)
Internal standards
Calibration
Validation
Quality control
Objectives
At the conclusion of this short course, the participant will be able to:
Describe the holistic process of delivering a clinically relevant mass spectrometry based protein/peptide assay from inception to validation.
Recognize the factors in assay development that are unique to proteins and peptides in comparison to traditional small molecule assays.
Use guidance documents in conjunction with rigorous experimental design to support fit-for-purpose method development strategies.
Data literacy, or the ability to read, understand, create, and communicate data in context, has become a foundational skill set across a wide number of fields. Computational thinking is focused on solving problems in a way that a computer would. Its core concepts are decomposition, pattern recognition, abstraction, and algorithmic design. While a variety of roles throughout research and clinical laboratory practice frequently interact with data and increasingly have access to data science tools with a need to evaluate such technologies and use them to create solutions, courses that cover the fundamental concepts of data literacy and computational thinking are not commonly required in undergraduate, graduate, or postgraduate training programs. Though now incorporated into K-12 education, the current clinical laboratory workforce and trainees have largely missed this instruction. These skills are critical for understanding and using digital technologies and advanced computational approaches to develop automated solutions and validate their performance or effectiveness. Broader access to data and informatic technologies, including no-code and low-code data science tools, AI-based chat technologies, and self-service analytics, has elevated the need for education in these areas. In this short course we will focus on fundamental concepts and best practices for working with and understanding data in a variety of contexts, including cleaning and managing data, visualizing data to communicate meaning, analyzing data with statistical methods to draw sound conclusions, and applying computational thinking concepts to work with and solve problems using programmatic and artificial intelligence-based solutions. Acquisition of key concepts will be supported with frequent case-based exercises and discussions and at least one representative data set per lesson will be used to support these interactive activities. Knowledge of a programming language will not be required for these activities; though block-based coding resources may be used and a basic working knowledge of spreadsheet software such as Microsoft Excel will be needed. This short course is intended as an introductory course to the data science track (i.e. before Data Science 101); however, as many of the concepts are not explicitly covered in other Data Science courses at MSACL, attendees who have previously taken other courses are welcome to join this course for formal coverage of these fundamentals.
Syllabus and Format
The course format will be interactive, with frequent case studies, exercises, and/or discussion to demonstrate how to apply the concepts as they are being learned. For each lesson at least one representative data set will be examined and/or analyzed. However, only a basic working knowledge of Microsoft Excel or similar spreadsheet software will be required. While basic concepts related to computer programming to analyze data may be discussed, writing code will not be required to demonstrate proficiency.
Basic concepts in data management and literacy
Patrick Mathias, 2 hours
Lesson Objectives
Describe the different types of analytics (i.e., descriptive, predictive, prescriptive)
Demonstrate how data science can augment expertise to draw robust conclusions and make better decisions
Illustrate best practices for organizing data in spreadsheet-based (rectangular) formats for use in data analytics
Compare and contrast different data types (e.g., numerical, categorical, timestamp, logical) used in data analytics
Identify common problems associated with real world laboratory data (e.g., censoring, keystroke errors, missing values, varied formats) and methods to mitigate them
Perform basic data cleaning and preparation steps to facilitate analysis
Principles of data visualization
Shannon Haymond, 2 hours
Lesson Objectives
Describe at least 2 scenarios in which a plot is more effective than a table in demonstrating relationships between variables in a data set
For each possible combination of data types, identify a type of plot that will effectively illustrate the relationship between two variables
List 2 types of plots that can illustrate statistical uncertainty when comparing numeric values between groups.
Key statistical concepts for laboratory data
Patrick Mathias, 2 hours
Lesson Objectives
Understand the fundamental statistical concepts used in laboratory medicine, including measures of central tendency, variability, and probability distributions
Critically evaluate the validity and limitations of basic statistical inference methods (e.g., regression models, hypothesis testing, confidence intervals) in various laboratory scenarios
Apply statistical principles to real-world laboratory scenarios to improve laboratory quality, interpret results accurately, and make evidence-based decisions.
Identify the key components of a complex problem and break it down into smaller, more manageable parts.
Use patterns to predict future outcomes or generalize solutions.
Create simplified models to represent complex systems.
Design step-by-step instructions or algorithms to solve a problem.
Describe basic coding concepts to better apply computational solutions.
Objectives
At the conclusion of this short course, the participant will be able to:
Apply best practices to managing data to support re-use and reproducibility
Perform basic data validation, cleaning, and preparation for analysis
Identify types of common data visualizations that are most appropriate given the types of data available and the goal of the analysis
Evaluate the validity and limitations of basic statistical inference methods across common scenarios
Develop computational thinking skills to more effectively utilize emerging digital technologies
2498
Data Science 101 : Breaking Up with Excel @ Outremont 4
2469
Data Science 203 : Machine Learning : A Gentle Introduction @ Outremont 3
Stephen Master, MD, PhD, FADLM Children's Hospital of Philadelphia
Stephen Master received his undergraduate degree in Molecular Biology from Princeton University, and subsequently obtained his MD and PhD from the University of Pennsylvania School of Medicine. After residency in Clinical Pathology at Penn, he stayed on as a faculty member with a research focus in mass spectrometry-based proteomics as well as extensive course development experience in bioinformatics. After time as an Associate Professor of Pathology and Laboratory Medicine at Weill Cornell Medicine in New York City, where he served as Director of the Central Lab and Chief of Clinical Chemistry Laboratory Services, he took a position at the Children's Hospital of Philadelphia at Chief of Lab Medicine. One of his current interests is in the applications of bioinformatics and machine learning for the development of clinical laboratory assays. He would play with R for fun even if he weren't getting paid, but he would appreciate it if you didn't tell that to his department chair.
Financial Disclosures (past 24 months as of Feb 21, 2025) Other Conflicts: Roche Diagnostics / Advisory Board / Ended
Indigo BioAutomation / Medical Advisory Board / Ongoing
The presenter will not mention or discuss Specific Products or Services of the company(ies) or technology listed above, or of ANY other ineligible entity, except in general, generic terms ensuring balance and impartiality.
Randall Julian, PhD Indigo BioAutomation
Randy Julian is the Founder and CEO of Indigo BioAutomation. Randy earned a Ph.D. in Chemistry from Purdue University. Dr. Julian worked for 14 years at Eli Lilly using mass spectrometry in natural product drug discovery, high throughput screening for RNA anti-viral compounds, and proteomics and metabolomics in animal models. Randy founded Indigo as a spin-out of Lilly. Indigo develops software that uses machine learning techniques to automatically analyze data from laboratories world-wide. Indigo's technology also drives new stand-alone medical devices, bringing advanced data analysis to every level of the clinical lab. Dr. Julian is also is an Adjunct Professor of Chemistry at Purdue.
Financial Disclosures (past 24 months as of Feb 05, 2025) Other Conflicts: Indigo BioAutomation, Inc. / Employee
Indigo BioAutomation, Inc. / Stock
The presenter will not mention or discuss Specific Products or Services of the company(ies) or technology listed above, or of ANY other ineligible entity, except in general, generic terms ensuring balance and impartiality.
Data Science 101 or 201 (or equivalent experience)
Overview
Machine learning techniques have been highly successful in driving the growth of companies like Amazon, Google, Netflix, and other companies that rely on identifying patterns in big data. More importantly, these algorithms are beginning to revolutionize clinical diagnosis and mass spectrometry, from FDA-approved retinal image analysis to robust detection of mass spec chromatographic peaks.
But ... what exactly is machine learning? How does it work? How can you apply it to your own data?
In this course, we will help you sort through the hype and provide an introduction to machine learning, including an overview of common approaches, known pitfalls, and other important concepts.
We will include practical instruction on applying machine learning algorithms using the R statistical language, so familiarity with R at the level of the material taught in Data Science 101 and/or 201 is desirable.
Topics Covered
What is machine learning?
Basic practices
Exploring your data
Preparing your data for ML algorithms
Features: Selection and Engineering
Decision trees
Model evaluation
Solutions to overfitting: Ensembles
Random Forests
Explaining complex models
Gradient Boosting with XGBoost
Objectives
At the conclusion of this short course, the participant will be able to:
Explain principles of machine learning
Describe machine learning processes
Perform classification using multiple machine learning models
Evaluate and test the performance of machine learning models
2475
Glyco(proteo)mics 101 : Clinical Glyco(proteo)mics by Mass Spectrometry @ Westmount 5
Guinevere Lageveen-Kammeijer, PhD University of Groningen
Dr. Guinevere Lageveen-Kammeijer is an Assistant Professor in the Analytical Biochemistry group at the University of Groningen, within the Groningen Research Institute of Pharmacy. She holds a BSc in Biotechnology - Forensic Sciences from the University of Applied Sciences van Hall Larenstein, Leeuwarden, and an MSc in Analytical Chemistry from VU University, Amsterdam. Her research interests were ignited during her MSc internship, where she focused on separation techniques coupled with mass spectrometry.
Guinevere earned her PhD in Clinical Glycomics from the Leiden University Medical Center in 2019 under the supervision of Prof. Manfred Wuhrer. Her thesis developed small-scale sample preparation workflows using capillary electrophoresis (CE) and mass spectrometry (MS/MS) to analyze glycans, glycopeptides, and glycoproteins, with applications in biomarker discovery and biopharmaceutical characterization. She continued her research as a post-doctoral researcher at the same institution before expanding her expertise with a visit to Northeastern University, Boston, in 2017, where she focused on protein charge and proteoform heterogeneity.
In 2022, Guinevere began her tenure-track assistant professorship at the University of Groningen, where she works on advancing glyco(proteo)mic techniques, particularly in single-cell glycomic analysis. Her research includes expanding the mass spectrometry-based glycosylation assay for prostate-specific antigen (PSA), a key biomarker for prostate cancer, and exploring the in-depth analysis of glycans and glycoproteins for biomarker discovery in other diseases and biopharmaceutical characterization.
Guinevere’s contributions have been recognized through funding such as the Investigator Sponsored Research grant from Astellas (2019) and the prestigious NWO VENI grant (2023). She is actively involved in the scientific community, serving on the Scientific Omics Committee for MSACL. Guinevere is passionate about promoting the importance of glycosylation in biomarker research, aiming to bridge the gap between researchers and clinical professionals to improve biomarker translation to the clinic.
Financial Disclosures (past 24 months as of Jan 22, 2025)
: none
Tamás Pongrácz, PhD Karolinska Institutet;
Leiden University Medical Center
Tamas Pongracz is an analytical chemist who, during his PhD and postdoctoral training at Leiden University Medical Center in the Netherlands, specialized in developing and refining advanced analytical methods and bioinformatics tools for high-throughput mass spectrometry-based protein glycosylation analysis.
His research focuses on exploring the glycomic dimensions of human diseases, establishing links between antibody structure and function, and contextualizing these findings within clinical disease proxies across various conditions. Currently he works as a postdoctoral researcher in the group of Charlotte Thalin at Karolinska Institute, Sweden, where his research focuses on the role of secretory IgA glycosylation in mucosal immunity.
Tamas' primary ambition is to introduce a next-generation, noninvasive liver fibrosis marker to the clinical lab by bridging the gap between his basic research findings and practical application.
Financial Disclosures (past 24 months as of Jan 28, 2025)
: none
Knowledge on basic mass spectrometry and spectral interpretation.
Overview
Did you ever encounter glycans, but you -kind of- neglected them as they seemed too complicated to characterize? Or did you just perform a glycan release to make the analysis of your protein a lot easier? You have no idea how to interpret your data when a glycan is present? Fear no more! We are here to provide you with the basics in the field of mass spectrometric glycomics and glycoproteomics.
The course will start with a historical overview on glycan research (i.e. how did glycans work their way up to being acknowledged as important study objects) and we will guide you through the maze of different nomenclatures. Moreover, although glycans are well known for their complexity, we will reveal to you the “rules of glycan structures” based on known biosynthetic pathways. This will be followed by an in-depth discussion on glyco(proteo)mic mass spectrometric technologies and workflows. In addition, different sample preparation steps and data analysis approaches will be covered. We will close-up with a session about glycomic biomarker discovery.
The course will run over two days and time will be split between lectures and workshops (e.g. how do you recognize a glycan in a mass spectrum and how do you assign it). While not everything can be covered within these two days we will ensure that you will know your “glyco-basics” in the end. Moreover, participants are encouraged to submit any specific glyco-questions they have prior to the course and we will try to discuss them during the course.
Objectives:
At the conclusion of this short course, the participant will be able to:
Understand the importance of glycosylation in human physiology through landmark discoveries
Understand glycan nomenclature and biosynthesis to aid mass spectrometry data interpretation.
Know what analytical method to choose for you specific glycomics experiment.
Learn how to interpret MS1 and MS2 data of glycans and glycopeptides.
Know what software to use to aid glyco(proteo)mics MS data processing.
FROM 2024
Discuss glycan nomenclature and biosynthesis
Select an appropriate analytical method for a specific glycomics research question.
Interpret mass spectrometry data using the biological background of a sample and the biosynthetic restrictions of the system.
Define the identity of released glycan and glycopeptide molecules using MS1 and MS2 data.
Select the appropriate software tools to aid glyco(proteo)mics MS data processing knowing the used analytical platforms.
2483
Isotopes 101 : Modern Isotope Ratio Analysis for Biomedical Research and Clinical Diagnostics @ Outremont 6
Cajetan Neubauer University of Colorado, Boulder
The frontiers of metabolomics & proteomics are finally merging with isotope ratio mass spectrometry, opening exciting new opportunities in our understanding of biological systems.
My lab at the University of Colorado Boulder helps pioneer related novel molecular measurements based on soft-ionization isotope ratio mass spectrometry. These advances can be used to study natural stable isotope fingerprints in metabolites, drugs, or small inorganic ions for a fascinating range of cross-disciplinary applications in life and earth sciences.
To achieve our longterm goal of making natural isotope patterns universally useful, we combine expertise in metabolomics and proteomics with advanced concepts of high precision stable isotope analysis from geochemistry.
Financial Disclosures (past 24 months as of Jan 20, 2025) Other Conflicts: Thermo Fisher Scientific / Consultant / Ended
The presenter will not mention or discuss Specific Products or Services of the company(ies) or technology listed above, or of ANY other ineligible entity, except in general, generic terms ensuring balance and impartiality.
Dwight Matthews, Ph.D. University of Vermont
Prof. Matthews received his PhD degree in 1977 in Analytical Chemistry from Indiana University with a focus in mass spectrometry. For his Ph.D. thesis he developed the first gas chromatograph-combustion-isotope ratio mass spectrometer (GC-C-IRMS). He then began his career at Washington University School of Medicine in St. Louis in the Department of Medicine where he developed stable isotope tracer methods to study in vivo amino acid metabolism in humans centered around gas chromatography-mass spectrometry (GC-MS). Several of these methods are commonly used by investigators today. In 1986 he moved to Cornell University Medical College in New York City as a tenured Associate Professor of Biochemistry in Medicine and Surgery to continue studies of metabolism. Here his focus broadened to include studies of metabolism in conditions found commonly in surgical metabolism and energy metabolism using doubly labeled water measured by IRMS. He also directed the Core Laboratories of the General Clinical Research Center. In 1996 he moved to the University of Vermont (UVM) as a Professor of Medicine in the College of Medicine and as a Professor of Chemistry in the College of Arts and Sciences. At UVM he directed core laboratories related to mass spectrometry for the Clinical Research Center, the Vermont Genetics Network Proteomics Core Laboratory, and the Mass Spectrometry Core Laboratory in Immunobiology. During this period, he developed new proteomics methods using liquid chromatography-mass spectrometry (LC-MS) with a focus on precise measurement of stable isotopic enrichments in proteins and peptides. From 2002-2014, he was Chair of the Department of Chemistry at UVM and named the Pomeroy Professor of Chemistry. In 2019, Matthews became a Professor Emeritus of Chemistry and Medicine at UVM, but continues his research activities. Professor Matthews is a world-renown expert in the development of stable isotope tracer techniques to study metabolism in humans. He has published over 175 papers in a range of peer-reviewed journals and over 75 contributions to symposia and chapters in books, and has an H-index of 85.
Financial Disclosures (past 24 months as of Jan 22, 2025)
: none
Patrick Day, MPH, MLS (ASCP) Mayo Clinic
My background, training, and educational degrees are in Laboratory Medicine & Pathology and Public Health. I received my bachelor’s and master’s degrees both from the University of Minnesota. My MPH thesis was on how geospatial supercomputing and clinical laboratory data can be combined to study how socioeconomic determinants of health and geography within the United States are associated with elevated levels of arsenic and mercury in humans. I am currently a principal developer in the Division of Computational Pathology and Artificial Intelligence at the Mayo Clinic in Rochester, MN. Prior to this role, I was a senior developer with the Metals Laboratory at Mayo Clinic. This clinical laboratory is staffed by thirty highly specialized employees that conduct metal analysis of biologic samples as well as analyze thousands of kidney stones a year by Fourier Transform Infrared Spectroscopy (FTIR). In the Metals Laboratory, I developed numerous laboratory developed tests (LDTs) as well as managed various multidisciplinary research projects. I currently hold the academic rank of Instructor in the Mayo Clinic College of Medicine and Science. I have co-authored numerous conference abstracts and peer-reviewed articles related to metals toxicology and artificial intelligence in the clinical laboratory and was honored to receive an American Society for Clinical Pathology 40 under Forty award.
Financial Disclosures (past 24 months as of Jan 21, 2025)
: none
This course will introduce clinical mass spectrometrists to the fundamental concepts of stable isotope ratio analysis and their applications in biomedical research and the practice of medicine. The course will cover isotope tracer techniques and natural abundance variations, providing examples to illustrate these distinct approaches in isotope research. Additionally, the course will explore emerging trends in isotope ratio mass spectrometry, including high-precision isotope analysis of biomolecules using soft-ionization mass spectrometry and the clinical applications of natural abundance variations of metal isotopes.
Recent technological advances have made precision isotope analysis more accessible to clinical laboratories. These advances include applications that use MS instrumentation that is already widely utilized in clinical MS laboratories. By connecting clinical researchers with experts in isotope ratio mass spectrometry, this course seeks to foster innovation and collaboration in clinical isotope analytics.
Topics Covered
Introduction to stable isotope analysis (instructor: CN, DM, PD)
Isotope tracers in biomedical and clinical research (DM)
Natural isotopic fractionation in human health and disease (CN)
Practical applications and case studies (DM, CN, PD)
Challenges to the translation of new isotope technologies into the clinical laboratory (PD)
Current applications from isotope experts that relate to MSACL community (CN, PD)
Objectives
At the conclusion of this short course, the participant will be able to:
Provide an overview of the current applications of isotopes in clinical diagnostics, including their role in isotope dilution as internal standards and in total metal analysis. (This objective sets the baseline understanding of stable isotopes in medicine.)
Describe the fundamental principles of isotope tracer studies and explain their application in investigating human metabolic pathways in health and disease states.
Explain the concept of natural isotopic fractionation and how these variations offer unique insights into nutritional status, metabolic processes, and potential disease markers.
Evaluate the capabilities of new advances in isotope ratio mass spectrometry and discuss their potential applications in advancing biomedical research and developing novel diagnostic tools for clinical applications.
Describe the technical, clinical, regulatory and financial challenges of translating new advances in isotope ratio mass spectrometry into the clinical production laboratory.
2485
LC-MSMS 101 : Getting Started with Quantitative LC-MSMS in the Diagnostic Laboratory @ Montreal 1-2
Grace van der Gugten, B.Sc. Chemistry Alberta Precision Laboratories
Grace discovered her love for clinical mass spectrometry when she began working at St Paul's Hospital in Vancouver in the special chemistry mass spec group with Dr. Dan Holmes in late 2010. Grace was challenged in this role but gained a wealth of knowledge and experience over her 10+ years in the SPH laboratory. She puts this experience and knowledge into use in her current role as Lab Scientist in the Newborn Screening and Biochemical Genetics lab at Alberta Precision Laboratories in Edmonton. Grace loves developing streamlined, easy to use (if possible!) clinical mass spectrometry assays; teaching others and helping others succeed; and troubleshooting (especially when the problem is solved!).
Financial Disclosures (past 24 months as of Jan 27, 2025)
: none
Deborah French, PhD, DABCC (CC, TC), FADLM UCSF
Deborah French Ph.D., DABCC (CC, TC), FADLM is a Director of Chemistry and the Director of Mass Spectrometry at the University of California San Francisco Health Clinical Laboratories. Her work currently focuses on the development and validation of LC-MS/MS assays for small molecules, specifically therapeutic drug monitoring, steroid hormones and toxicology. Deborah received her Ph.D. in biochemistry from the University of Strathclyde in Glasgow, Scotland and then completed a postdoctoral fellowship at St. Jude Children’s Research Hospital in Memphis, TN. She subsequently completed a ComACC Clinical Chemistry postdoctoral fellowship under the direction of Dr Alan Wu at the University of California San Francisco and is now board certified in Clinical Chemistry and Toxicological Chemistry by the American Board of Clinical Chemistry.
Financial Disclosures (past 24 months as of Jan 27, 2025) Other Conflicts: ARK Diagnostics / Consultant
Roche Diagnostics / Consultant / Ended
The presenter will not mention or discuss Specific Products or Services of the company(ies) or technology listed above, or of ANY other ineligible entity, except in general, generic terms ensuring balance and impartiality.
Jacqueline Hubbard, PhD, DABCC Beth Israel Deaconess Medical Center, Harvard Medical School
Jacqueline Hubbard received her BS degree in Biochemistry from the University of Vermont. She then earned her MS and PhD in Biochemistry and Molecular Biology from the University of California, Riverside (UCR). Following a one year postdoc at UCR, Dr. Hubbard completed a Fellowship in Clinical Chemistry at the University of California, San Diego Health. She is board certified in Clinical Chemistry by the American Board of Clinical Chemistry. After fellowship, she took a position as an Assistant Professor in the Department of Pathology and Laboratory Medicine at the Geisel School of Medicine at Dartmouth and as the Assistant Director of Clinical Chemistry at Dartmouth-Hitchcock Medical Center. There, she focused on developing and validating drugs of abuse assays and SARS-CoV-2 serology testing. Next, she briefly served as a Lab Director for a small reference laboratory in PIttsburgh, PA. She then joined Beth Israel Deaconess Medical Center as the Co-Director of Clinical Chemistry and Director of Toxicology in 2024. She is also an Assistant Professor of Pathology for Harvard Medical School. Her research focus still includes mass spectrometry method development and toxicology test interpretation.
Financial Disclosures (past 24 months as of Jan 28, 2025)
: none
Grace Williams VCU Health
Financial Disclosures (past 24 months as of Jan 29, 2025)
: none
Interested in a detailed, practical introduction to clinical quantitative LCMS
Overview
Is your laboratory under pressure to purchase an LC-tandem MS or is the ROI you wrote last year haunting you now? This short course is designed for attendees implementing quantitative LC-tandem MS for patient testing who have laboratory medicine experience but no mass spectrometry training - CLS bench analysts, supervisors, R&D scientists, and laboratory directors. Theoretical concepts necessary for a robust implementation of clinical mass spectrometry will be presented – but the emphasis is on practical recommendations for:
LC-MS/MS system purchasing, site preparation and installation
Choosing internal standards, solvents, and water, making reagents and calibrators
Selecting and optimizing LC parameters
Selecting and optimizing MS/MS parameters
Selecting and optimizing sample preparation
Adjusting sample preparation, LC and MSMS parameters to achieve the desired assay performance
Establishing data analysis & review criteria
Pre-validation stress testing and method validation
Maintaining quality in production
Preventative maintenance and troubleshooting
Objectives
At the conclusion of this short course, the participant will be able to:
Describe the components of a triple quadrupole mass spectrometer and describe how they work.
Evaluate sample preparation options for LC-MS/MS and explore matrix effect validation experiments.
Explain the importance of developing an LC gradient method that is compatible with their analyte(s) of interest.
Outline MS parameters that need optimization, including source and compound specific parameters.
List quantitation and review criteria options for LC-MS/MS data.
Formulate a validation plan and describe how to execute those experiments for an LC-MS/MS assay.
Appraise equipment options and justify the purchase cost.
2471
LC-MSMS 203 : Validation of Quantitative LC-MS/MS Assays for Clinical and Academic Use @ Montreal 3
2479
LC-MSMS 302 : Advanced LC-MSMS Method Development, Troubleshooting and Operation for Clinical Analysis @ Outremont 5
Robert Voyksner, PhD LCMS Limited
Dr. Robert D. Voyksner received his B.S. in Chemistry at Canisius College in 1978 and his Ph.D. at the University of North Carolina at Chapel Hill in 1982. He was employed at Research Triangle Institute (RTI) from 1983-2001 as the director of the mass spectrometry facility and has been responsible for developing
extraction, separation and mass spectrometric methods for biologically and environmentally significant compounds. His work earned him the Presidents Award, the highest award within RTI. In 2001 he co-founded LCMS Limited in Durham, NC and has been the CEO of the company to date. Under his direction LCMS Limited is working on technological advancements in LC-MS/MS, offering services to pharmaceutical, clinical and agrochemical industry for solving unique problems by LC/MS/MS and offering training in LC/MS/MS and MS/MS interpretation and on LC/MS/MS instrumentation. Dr Voyksner is also an Adjunct professor at the North Carolina a School of Veterinary Medicine and at The University of North Carolina
School of Pharmacy.
Dr. Voyksner's research in mass spectrometry has resulted in over 230 publications and presentations, primarily in the area of LC-MS/MS. He has served on the Board of Directors for The American Society For Mass Spectrometry (ASMS), is on the organization committee for The Montreux LC/MS Symposium and was the organizer for the 1995, 1999, 2003 and 2007 Montreux LC/MS Symposia. Dr. Voyksner has taught over 100 courses on LC-MSMS, CE/MS and CID interpretation during the past 10 years for MSACL, ASMS, pharmaceutical companies; ISSX, PBA, HPCE and HPLC focused meetings.
Financial Disclosures (past 24 months as of Jan 18, 2025)
: none
Working knowledge analytical chemistry, including experience with LC separations and/or mass spectrometry. Attending level 100 or 200 LC/MS courses at MSACL would be beneficial. This is a course for those who want to increase their understanding of LC-MS/MS, who want to learn how to develop a successful quantitative and qualitative LC-MS/MS assay and a deeper understanding the technique to achieve better sensitivity, specificity or throughput in their laboratory.
Overview
This course focuses on method development method trouble shooting and application for the analysis of both small and large molecules that are clinically relevant. All examples are taken from real world analyses, performed by Dr. Voyksner at LCMS Limited. The concepts presented in the course are reinforced through numerous problem sets the attendees will work on throughout the 16 hour course. These concepts will be valuable for the course attendees in developing and troubleshooting their own methods and enable a better understanding on how to improve their LC/MS/MS method. The last part of the course is an open forum where each attendee is invited to share a current LC-MS/MS issue they face. As a class we work through potential solutions and experiments to be performed to find a solution to the student problem, applying the concepts taught in the class and Dr. Voyksner’s 40 plus years of experience in LC-MS/MS. From past classes this has been the attendee’s favorite part of the class.
This course is designed for the scientist that uses LC-MS/MS in the clinical lab, who wants a deeper understanding in steps towards developing successful methods, optimizing methods, trouble shoot methods and solving problems employing LC-MS/MS.
The course covers important aspects in understanding and optimization ionization with electrospray on multiple instrument platforms including triple quadrupole, time-of-flight, quadrupole time of flight and orbit trap mass analyzers.
The course will discuss sample preparation, modes of chromatography and MS/MS considerations with respect to method development and optimization for the analysis of “real-world” samples by LC-MS/MS, to achieve the best sensitivity, specificity, and sample throughput.
The course will cover all aspects of quantitative LC/MS/MS assays development and troubleshooting for small clinical molecules, peptides and proteins.
The course will introduce concepts needed for the interpretation of MS/MS mass spectra.
Topics Covered
Understanding API ionization processes for electrospray, APCI and APPI, what affects the ionization process and how to maximize the ionization for compounds of interest.
Understanding the effects of LC columns (dimensions and particles size), flow rate, and mobile phases have upon the separation and LC/MS analysis.
Determining the type of ions that can form by electrospray and APCI, how to interpret the MS and MS/MS spectra and approaches on how to perform qualitative analysis in LC-MS/MS and high-resolution MS/MS.
Understanding important issues that affect quantitative analytical results and how to optimize the method to achieve the best performance, reduce matrix suppression, reduce background and generate the best accuracy and precision.
Exploring what new techniques are available (e.g. direct analysis MS, chip method and MS instrumentation) that can improve the results one can obtain.
Discuss aspects of method development and method trouble shooting from example problems of real world problem in quantitative LC-MS/MS.
Open forum discussing attendees’ specific problems they face in method development or analysis using LC-MS/MS.
Objectives
At the conclusion of this short course, the participant will be able to:
Improve sensitivity and specificity for LC-MSMS analysis.
Develop methods to analyze the target compounds.
Select correct electrospray or APCI conditions to analyze the target compound.
Reduce matrix suppression.
Troubleshoot a method to improve accuracy, precision, sensitivity and specificity.
Reduce background in LC-MSMS analysis.
2489
Lipidomics 101 : Mass Spectrometry-based Lipidomics and Clinical Applications @ Outremont 7
Anne K. Bendt, PhD Singapore Lipidomics Incubator (SLING), National University of Singapore
Anne K Bendt studied Biology focusing on marine biotechnology (Greifswald University, Germany), followed by a PhD in Biochemistry (Cologne University, Germany) employing proteomics and transcriptomics. Driven by her fascination for infectious diseases, she joined the National University of Singapore (NUS) in 2004 to develop lipidomics tools for tuberculosis studies. She is now a Principal Investigator at the Life Sciences Institute, NUS, focussing on translation of mass spec technologies into clinical applications, and serving as the Deputy Director of the Singapore Lipidomics Incubator (SLING) taking care of operations and commercialization.
Financial Disclosures (past 24 months as of Jan 19, 2025)
: none
Amaury Cazenave Gassiot, PhD Singapore Lipidomics Incubator (SLING) and Department of Biochemistry, National University of Singapore
Research Assistant Prof. Cazenave-Gassiot is an early-career researcher and an expert in mass spectrometry-based lipidomics. He graduated with a PhD in analytical chemistry at the University of Southampton (UK), under the supervision of Dr John Langley, specialising in supercritical fluid chromatography and mass spectrometry. His interest in lipids started while a postdoc in the team of Professor Anthony Postle, still in Southampton. A member of SLING since 2009, his research centres on separation sciences, mass spectrometry, and their applications to life sciences, especially lipid biochemistry. He has developed chromatographic and mass spectrometric methods for the identification and quantification of lipids in diverse biological systems. This has included successful local and international collaborations.
Financial Disclosures (past 24 months as of Jan 20, 2025)
: none
Michael Chen, MD MSc The University of British Columbia
Dr. Michael Chen is a clinical pathologist, specializing in clinical chemistry and translational mass spectrometry. He is the Division Head of Medical Biochemistry at Island Health and Provincial Discipline Lead at Provincial Health Services Authority. As a researcher, Dr Chen is the scientific director of UBC Translational Omics Lab in the Victoria General Hospital. He is also the director of Vancouver Island Biobank, and he co-chairs the BC Biobank Network. Dr. Chen’s research focuses on clinical mass spectrometry, biobanking, biomarker validation and clinical implementation.
Financial Disclosures (past 24 months)
: Not reported
LC-MS/MS, clinical translation, lipidomic applications, method harmonization AND an interest in lab medicine and clinical lipidology.
Overview
This one-day course is meant to (1) create awareness for the importance and therefore potential value of lipid testing beyond cholesterol and triglycerides for future clinical applications. We will (2) then outline currently available technologies and their respective opportunities and challenges, and (3) discuss candidate molecules in the context of current case studies.
Topics Covered
Looking beyond cholesterol and TAG:
- Potential of blood-based lipid testing
- Gain an understanding of the universe of lipids, how they are intricately linked to biology and their implications in health and diseases (e.g., inherited genetic disorders, cardiovascular disease, clinical nutrition, etc.)
- Identify physiologically relevant candidate lipids for adoption by the clinical community, for future studies towards establishing clinical utility
Current lipidomics R&D workflows:
- Path of translation from R&D laboratory-style methods towards robust and quantitative assays with appropriate turnaround times
- Pre-analytics (sampling requirements, plasma vs serum, storage, etc.)
- Analytics (i.e., batches, internal standards, lipid extractions, direct infusion vs LC-MS and LC-MS/MS, quality assurance)
- Post-analytics (raw data processing, lipid annotations, quality control, quantification)
- Ongoing harmonization efforts
Case studies of markers that have advanced to clinical settings
Outreach and Engagement between the analytical scientist specialized in mass spectrometry of lipids, the clinician researcher and laboratory medicine as the end user are key to the development of impactful/ useful lipidomics in clinical applications
Objectives
At the conclusion of this short course, the participant will be able to:
Discuss the lipid universe beyond cholesterol and triglycerides,
Explain what lipid molecular species are.
Describe the process of biomarker validation and implementation in clinical labs and how the analysis of lipid metabolites will contribute to precision diagnostics.
Describe how to measure lipid metabolites using multiple-reaction-monitoring mass spectrometry.
Evaluate the performance and quality of lipid metabolite-based tests.
Review molecular MS data and provide answers for laboratory specialists.
