FEBRUARY 2025
Revolutionizing Metabolomics: AI Meets Mass Spectrometry
Download an editorial summary about our webinar hosted by The Analytical Scientist featuring Matterworks CSO Jennifer Campbell and Dr. Naama Kanarek.
JANUARY 2025
Bringing Scalability to Metabolic Flux Analysis Using Machine Learning to Accelerate LC-MS Interpretation
A recap of our Dedicated Dialogue podcast featuring Pyxis™ user Dr. Sam Yenne from Metalytics, Inc., a company that specializes in the science of metabolic flux. Listen to the full podcast here.
NOVEMBER 2024
High Throughput Metabolite Quantification in Biological Samples with Pyxis, a Matrix-Agnostic AI/ML Tool
A poster authored by Sofia Costa, PhD, Principal Scientist at Matterworks. Presented at Metabolomics Association of North America (MANA) 2024.
OCTOBER 2024
Rapid Absolute Quantitation of Metabolites Using Machine Learning
Dr. Jennifer Campbell, CSO at Matterworks, discusses work completed by Sofia Costa, PhD in collaboration with Sartorius Stedim Biotech GmbH in which the performance of Pyxis is compared against traditional isotopologue analysis.
JULY 2024
Scalable Absolute Quantitation for Untargeted Metabolomics
Dr. Luke Ferro, PhD, Senior Scientist at Matterworks, discusses work performed with the Kanarek Lab at Boston Children's Hospital regarding the use of Pyxis to analyze animal models of disease. This poster was originally presented at the 2024 American Society for Mass Spectrometry Conference.
JUNE 2024
ASMS 2024 Posters
See a list of posters presented by Matterworks and collaborators at the 2024 American Society for Mass Spectrometry (ASMS) Conference.
JUNE 2024
Pyxis Product Brochure
A product brochure that details Pyxis application areas, function, and technology along with a list of recent publications.
JUNE 2023
Absolute Quantification of Key Cellular Metabolites in Bioprocessing Samples Using Machine Learning
Luke Ferro, PhD, gives a short poster overview of a collaboration between Matterworks and Eli Lilly for the quantification of metabolites from bioreactors.
SEPTEMBER 2024
Absolute Quantitation for Metabolic Flux Analyses using Machine Learning
Dr. Luke Ferro, PhD, Senior Scientist at Matterworks, discusses the use of Pyxis is metabolomic flux analysis. This poster was originally presented at the 2024 American Society for Mass Spectrometry Conference.
JULY 2024
Infographic: Navigate Your Way to Precise and Scalable Untargeted Metabolomics
An infographic that highlights the advantages of absolute quantitation over relative quantitation and explains how Pyxis enables absolute quantitation.
JUNE 2024
Preprint: LSM1-MS2: A Foundation Model for MS/MS, Encompassing Chemical Property Predictions and de novo Generation
Read our preprint about Matterworks' LSM1-MS2, a pre-trained self-supervised foundation model for tandem mass spectrometry (MS/MS).
AUGUST 2023
Unlocking Scalable Quantitative Metabolomics with AI
Jennifer M. Campbell, PhD, Chief Scientific Officer, discusses how Matterworks is unlocking scalable quantitative metabolomics with AI. This talk was originally given at a breakfast workshop hosted by Thermo Fisher Scientific at ASMS 2023.
SEPTEMBER 2024
Preprint: A scalable approach to absolute quantitation in metabolomics
Read our preprint authored in conjunction with collaborators from Boston Children's Hospital and Harvard Medical School.
JUNE 2024
Simple, Scalable Absolute Concentrations in Untargeted Metabolomics
An application note that explores the challenges of quantitative metabolomics and how Pyxis can be used to generate simple, scalable absolute concentrations.
MAY 2024
Using Pyxis for the Characterization of Microbiome Function
An application brief explaining how Pyxis can be used for absolute quantitation of untargeted small-molecule messenger analytes to elucidate microbiome function.
JULY 2023
Absolute Quantitation of Metabolites Using Machine Learning and StandardCandles as Universal Calibrators - the second-generation model
Jennifer Campbell, PhD, Chief Scientific Officer, gives a brief overview of how Matterworks is using machine learning and universal calibrators to enable whole metabolome reading