Translating Pre-Clinical Research to Clinical Patient Care™

Educational Grants supported in part by:
& Brian Kelly

Agenda (Preliminary) - View Program

Friday, April 8



Monterey Challenge Run/Walk

Location: De Anza Foyer

Meet-up in front of Registration in De Anza Foyer. Advice: Once on path, go left towards Cannery Row.

Registration Desk Opens

Location: De Anza Foyer

Addressing Hurdles in Clinical Translation of Targeted Proteomics

Location: De Anza

Jeffrey Whiteaker, PhD

Fred Hutchinson Cancer Research Center

Quantifying proteins and post-translational modifications will improve precision medicine, but several hurdles remain to adopting proteomics to the clinical laboratory. Dr. Whiteaker will discuss successes and remaining challenges for incorporating targeted proteomic measurements in clinical trials and other clinical applications.

Newborn Screening by Mass Spec Meets Newborn Screening by DNA Sequencing

Location: De Anza

Michael Gelb, PhD

University of Washington

Our laboratory has been developing tandem mass spectrometry (MS/MS) for worldwide expansion of newborn screening (NBS) panels to include an ever-increasing collection of treatable genetic diseases. There is widespread discussion on the use of whole genome and whole exome DNA sequencing in population-wide NBS. The intersection of biochemical- and DNA-based NBS is an interesting topic now under heavy discussion.

We will highlight the development of liquid chromatography-MS/MS (LC-MS/MS) for multiplex NBS of a large panel of treatable genetic diseases in newborns. Next generation sequencing (NGS) is also employed currently as a second-tier analysis after LC-MS/MS assays. We will also illustrate how it is possible to carry out first-tier NGS followed by second-tier LC-MS/MS NBS.

LC-MS/MS is used together with enzyme substrates and biomarkers to monitor the activity of a large collection of enzymes and to measure the abundance of biomarkers in dried blood spots on NBS cards. We will focus on multiplex methods and then zoom in one a more detailed analysis of one disease called metachromatic leukodystrophy (MLD). We carried out a pilot MLD NBS study and determined that the rate of false positives out of 28,000 newborns screened is essentially zero showing the power of LC-MS/MS for NBS of this lysosomal storage disorder. In the second arm of the study, we have been measuring the activity of the enzyme relevant to MLD on a large collection of gene variants that are found in allele databases and for which no pathogenic information is reported. We show how we can integrate these efforts to provide for a highly efficient NBS program for MLD.

We screened ~28,000 newborns for elevated sulfatide lipid, the biomarker that is relevant to MLD and found 180 high sulfatide newborns. These were submitted to an assay of the activity of the relevant enzyme, arylsulfatase A, and all but two showed normal levels of activity. DNA sequencing was carried out on 2 newborns, one with 0% and one with 8% of normal ARSA activity. The newborn with 0% activity was confirmed to have MLD, the other was shown to not have MLD. On the DNA front, we created a phenotype matrix that allows one to input the ARSA enzymatic activity of each variant to provide a composite genotype, and to make a prediction of the phenotype associated with this genotype. We show that this method is 83% accurate at predicting the true set of phenotypes observed in MLD patients.

Massively multiplexed NBS of genetic diseases in newborns is possible using LC-MS/MS, and when used with second-tier NGS leads to a successful NBS platform. We show that it is also possible to carry out NGS as a first-tier NBS step and to clarify the results with second-tier biochemical assays based on LC-MS/MS. Thus LC-MS/MS meets DNA and DNA meets LC-MS/MS, and this provides a framework for the future employment of both LC-MS/MS and NGS in expansion of population based NBS.

Coffee Break

Location: De Anza Foyer

Utilization of Mass Spectrometry to Discover and Develop Novel Biomarkers to Support Drug Development

Location: De Anza

Veronica Anania, PhD


Biomarkers play an important role in the drug development process including providing necessary insights into target engagement, dose selection and mechanism of action of candidate therapeutics. LC-MS is uniquely positioned to enable accurate quantitation of both small and large molecule biomarker candidates, however, the process of going from biomarker discovery to a multiplexed targeted MRM panel in clinical samples is long and resource intensive. Moreover, biomarker candidates often fail to replicate when tested in large clinical cohorts. Recent advances in data-independent MS (DIA-MS) have made this technology more accessible and certain benefits of DIA-MS including reproducible label-free analysis of hundreds of samples, ability to capture low abundance ions over a high dynamic range, and deep proteome coverage makes this technology well suited to streamline translational proteomics. One major hurdle for using DIA-MS to support drug development is that the quantitative range for most DIA-MS methods has not been well characterized and thus, quantitative conclusions drawn by prior studies that have employed this approach have been controversial. Here, we describe challenges associated with applying DIA-MS methods to address questions associated with clinical development and introduce best practices for establishing quantitative criteria for DIA-MS approaches in clinical trial samples. Results and lessons learned from both discovery and targeted clinical biomarker studies will be discussed and a model for a more streamlined biomarker development workflow that conserves resources and provides more comprehensive proteomic information from clinical trial samples will be discussed.

Panel Discussion

Location: De Anza

Closing Statements

Location: De Anza

Boxed Lunch Pick-Up and Mixer

Location: Jacks

Pickup a boxed lunch and enjoy a little down time or check out the workshop starting in Bonsai at 1215.

Workshop: Rethinking the Traditional Workflow for Urine Toxicology Testing

Location: Bonsai

Melissa Budelier, PhD

TriCore Reference Laboratories

Benjamin Beppler

TriCore Reference Laboratories


- Identify common challenges with reflexive urine drug screening
- Discuss the utility of 'hybrid' testing and direct to definitive testing using mass spectrometry
- Address the importance of drug panel test selection, and the potential issues with specific drug classes
- Describe the value of providing interpretive reports for urine drug testing, particularly for pain management clients

Workshop Summary

Many clinical laboratories continue to utilize a traditional urine drug testing algorithm involving an initial screen, typically via an automated immunoassay, followed by confirmation of positive and/or unexpected results using mass spectrometry. This algorithm emerged in the 1970s and 1980s from the desire to test for the use of illicit substances in the military and other workplaces. It was designed to answer the question: Are employees upholding a drug-free workplace? This algorithm presents significant limitations in many clinical situations, particularly in the areas of pain management and substance use disorder treatments, where the primary question changes to: Is my patient taking their medication as prescribed? This workshop will discuss several alternatives for urine drug testing, such as direct to mass spectrometry testing and 'hybrid' panels. It will also discuss considerations for selecting the appropriate analytes for urine drug testing panels and potential pitfalls associated with certain classes of drugs. Finally, it will introduce our recent efforts to implement the use of interpretive reporting for pain management clients.

Workshop: Pre-analytical considerations as prerequisite for successful clinical application of lipidomics

Location: De Anza 1

Robert Gurke, PhD

Fraunhofer Institute for Translational Medicine and Pharmacology ITMP

Bo Burla, PhD

Sling @ National University of Singapore

Margret Thorsteinsdottir, PhD

University of Iceland

Anne K. Bendt, PhD

Singapore Lipidomics Incubator (SLING), National University of Singapore


It is the objective of the workshop to provide an introduction into pre-analytical considerations for clinical application of MS-based analytics, with a special focus on lipids. However, these considerations are in many cases independent of specific analytes of interest and can hence be applied for polar metabolites as well as proteins. The workshop is focused on main hurdles to be considered when performing clinical research using LC-MS based determination of lipids namely: (I) pre-analytical sample handling, (II) frequent generation of patient samples as well as (III) overall cohort and study design.


Lipids are involved in a broad spectrum of functionalities in the organism and implicated in a variety of physiological and pathological processes. Changes in lipid levels are promising biomarkers for early diagnosis, prognosis of disease progression, or guidance for selecting promising therapeutic approaches. However, biomarker discovery in the field of lipidomics is a very challenging process since lipids require specific procedures regarding sampling (including selection of sample type and collection procedures, storage conditions and number of freeze-thaw cycles), sample preparation and analysis for reliable determination. As especially pre-analytical sample handling is a critical step for the reliable analysis of the lipidome, a close cooperation with the clinicians is necessary. This ensures following a highly standardized protocol for venous blood sampling to avoid several pre-analytical pitfalls potentially changing the lipid profile ex vivo. As collecting venous blood samples is very laborious for patients as well as clinicians, other ways for a more frequent sample collection are necessary. Therefore, capillary blood sampling using microsampling devices is an auspicious way to complement the strategy of analyzing venous blood-based samples taken in the clinics. Besides considering the right sampling strategy, the structured recording of sampling details and subject metadata, the overall planning of the study and also the cohorts to be included is of high relevance. All mentioned points have to be considered before starting a clinical research project applying lipidomics to generate high quality data making biomarker discovery possible.

- Pre-Analytical factors influencing lipid concentrations
- Capillary vs. venous blood sampling - the potential of microsampling
- Cohort & Study design for lipidomics in clinical research

Short Course: LC-MSMS 201 : Understanding and Optimization of LC-MS/MS to Develop Successful Methods for Identification and Quantitation in Complex Matrices

Location: De Anza 2

Robert Voyksner, PhD

LCMS Limited

Workshop: CLSI C64 - Supporting development of quantitative protein and peptide assays for clinical use

Location: De Anza 3

Cory Bystrom, PhD


Russell Grant, PhD


* with Special Guest Stars *

Workshop attendees will gain an understanding of the clinical assay development framework for proteins and peptides established in CLSI C64. Using C64 as a framework for development will help the laboratorian approach protein and peptide assay development confident that analytical performance will meet clinical requirements.

The development and validation of quantitative assays for proteins and peptides for clinical use is a significant undertaking and presents challenges that are distinct from small molecules. The heterogeneous nature of proteins and the frequent requirement to use proteolysis aided workflows add complexity that require careful attention to definition The workshop will be an interactive discussion covering each chapter in C64, guided by authors that contributed extensively to the development of the document.

Objective 1: Understand the holistic process of delivering a clinically relevant LC-MS/MS protein/peptide assay from inception to validation.

Objective 2: Recognize the factors in assay development that are unique to proteins and peptides in comparison to traditional small molecule assays.

Objective 3: Understand key experimental requirements for successful development and validation.

1. Introduction to C64, philosophy and scope
2. Interactive discussion of each chapter

Short Course: Sample Prep 201 : Sample Preparation and Alternative Matrices for LC-MS Assays

Location: Bonsai

William Clarke, PhD, MBA, DABCC

Johns Hopkins University School of Medicine

Mark Marzinke, PhD, DABCC, FAACC

Johns Hopkins University School of Medicine

** Part In-Person and Part Online **

This in-person activity is Segment 2 (4 hr) of a 3 segment (12 hour total), part in-person and part online, short course.

Segments 1 and 3 will take place ONLINE on March 4 & April 22, 2022. The first segment is before the conference, the third segment is after the conference.

While attending this IN-PERSON segment is FREE, the ONLINE attendance is fee-based. You can REGISTER HERE.


This course highlights not only the importance of sample processing in the clinical laboratory environment, but also illustrates the "fit for purpose" application of processing techniques in clinical mass spectrometry. This course discusses the theory behind different specimen preparation methods, strengths and weaknesses of each approach, as well as opportunities for automation.

The first 4 hour online segment will cover workshop ground rules, introduction, pain points of LC-MS, specimen processing (tube types, management, etc.), and matrix effects.

The second 4 hour in-person segment will cover dilution and protein precipitation, solid phase extraction, supported liquid extraction, liquid-liquid extraction, and affinity-based sample preparation

The third 4 hour online segment (online) will elaborate on the foundations established in the first two segments, and expand into newer technologies and automated alternatives for sample processing.

Specific topics to be covered include:

  1. Pain points in clinical LC-MS
  2. Overview of specimen processing in laboratory medicine
  3. Off-line sample processing
  4. On-line sample processing
  5. Analysis of blood and urine
  6. LC-MS of tissue specimens
  7. Alternate body fluid specimens (e.g. CSF, breast milk, etc.)
  8. Dried specimens as matrices
  9. Automation of sample processing

Topics will be covered through lecture, Q&A, Case Studies, and small group exercises.

Short Course: Data Science 201 : Going Further With R: Tackling Clinical Laboratory Data Manipulation and Modeling

Location: Colton

Patrick Mathias, MD, PhD

University of Washington

Shannon Haymond, PhD

Northwestern University Feinberg School of Medicine

** Part In-Person and Part Online **

This is the first segment (4 hr) of a 16 hour, part in-person and part online, short course.

Segments 2, 3 and 4 will take place ONLINE on April 28,29 and 30, 2022

While attending this IN-PERSON segment is FREE, the ONLINE attendance is fee-based. You can REGISTER HERE.


Having completed your first steps into the wonderful world of data analysis with R (Data Science 101 with Daniel Holmes), would you like to go further? You’ve learned the basics of R, so now it’s time to put that knowledge to work and tackle some interesting clinical applications. Along the way you will also be introduced to even more of capabilities of R and the tools developed by the amazing R community.

The course will be run over two days and time will be split between lecture sessions, individual problem solving, and a highly interactive group-level data mining of real data sets (there may even be prizes). Like the introductory course, this class will maintain the “no student left behind policy”. Students will be given time to solve problems taken from real life laboratory work and to do some more advanced analysis on large scale data sets. All attendees will need to bring a laptop with the R language installed and R Studio interface installed. Students may use Windows, Mac OSX or Linux environments. Both R and R studio are free (as in “Free Beer”) and open-source.

Students should be prepared continue to expand their skill in programming – which, as you learned in the introductory course can be a little frustrating, but not as frustrating as not being able to get the computer to do what you want at all!

Obtaining the Software


!!! POWER : Make sure your computer is charged to hold power for 4 hrs, as power outlets may not be available.

Instructions for installing the R language are here:
Instructions for installing R Studio are here:

Course Description

The course will cover:

  1. Core concepts in reproducible data analysis
  2. Introduction to version control
  3. Using R Markdown for reproducible reports
  4. Advanced file reading capabilities
  5. Scaling up your data transformation skills
  6. Cleaning dirty data and managing timestamps
  7. Joining data sets together
  8. Connecting R to databases
  9. Prediction with linear regression and classification with logistic regression
Closing Dinner Reception

Location: Jacks

Jacks Club Room

After Hours Activity Suggestions

Location: Off-site

*These are non-MSACL-sponsored activities.

Alvarado Brewery.

Club Cibo - $5 drinks all night.