Thursday Afternoon ASMS Workshops

June 3, 2020

On Thursday afternoon in the ASMS 2020 Reboot event, seven workshops will be held, on ambient ionization, DMPK aspects of new therapeutic modalities, machine learning for MS data analysis, standardizing the MS workflow, leveraging emotional intelligence during the pandemic, the multidimensional clinical space, and large-scale data analysis and management.

On Thursday afternoon in the ASMS 2020 Reboot event, seven workshops will be held, on ambient ionization, DMPK aspects of new therapeutic modalities, machine learning for MS data analysis, standardizing the MS workflow, leveraging emotional intelligence during the pandemic, the multidimensional clinical space, and large-scale data analysis and management. All sessions will be held from 12:00 to 1:30 pm CDT, and are as follows:

  • Ambient Ionization: How Can We Make It More Reproducible? Presided by G. Asher Newsome. This workshop on ambient ionization aims to encourage the participation and presentations of new investigators, postdoctoral rsearchers, and graduate students with a balanced perspective from academia, non-academic laboratories, and industry. One of the goals of the workshop will be to gather scientists interested in ambient ionization technology and discuss the formation of an ambient ionization interest group to address these new scientific challenges.

  • DMPK Aspects of New Therapeutic Modalities. Presiders will be Brian Rago and Aaron Teitelbaum. The purpose of this workshop is to gather the ASMS drug metabolism and pharmacokinetics (DMPK) community and learn from recent new therapeutic modalities (NTM) success stories, while discussing the utility of mass spectrometry within DMPK to support NTMs.

  • Machine Learning Analysis of Mass Spectrometry Data in the Life Sciences. Presiders are William Noble and Arzu Guler. This workshop has two goals: to spur workshop attendees to brainstorm potential applications of machine learning to problems that they want to solve, and to teach attendees how to recognize what makes a problem well-suited (or not) to a machine learning approach.

  • Standardizing the Imaging MS Workflow: Current Progress. Presided by Peggi Angel and Tiffany Porta. This workshop will entail short presentations by students, postdoctoral fellows, and investigators from industry, academia, and government laboratories on standardizing imaging mass spectrometry workflows. Each presentation will be followed by a 5–10 minutes discussion within the interest group. A goal is to further disseminate information on challenges and solutions for method transfer between laboratories.

  • Leveraging Emotional Intelligence Strategies during the Pandemic. Presiders will be Lucinda Hittle and Charles Veltri. This workshop will convene scientists across diverse sectors including academia, industry, government, and non-profit agencies to discuss coping strategies during the global pandemic. These strategies include leveraging the four elements of emotional intelligence: self-awareness, self-management, social awareness, and relationship management.

  • The Multidimensional Clinical Space-From Discovery to Practice in Screening and Diagnostics, Presiders will be Candice Ulmer and Don Chace. This workshop will highlight best practice quality control and quality assurance (QC/QA) standards for clinical laboratories that can be applied in targeted and multi-analyte assays across multiple applications and mass spectrometric platforms. Representatives from industry, regulatory bodies, and clinical hospital laboratories will deliver brief presentations on their considerations of the proposed QA/QC measures.

  • Large-Scale Data Analysis and Management: Challenges for Analytical Laboratories. Presided by Samuel Mackintosh and Ryan Leib. This analytical laboratories managers workshop will focus on techniques for processing and management of data from emerging methodologies in ways that meet the needs of non-specialist clients and collaborators. The workshop will feature three speakers discussing the analysis and management of different types of data.

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