Summary

I spent October 6 to 9 in Montréal with the clinical mass spec community. Five themes emerged over the course of the conference:

  • Optimizing clinical lab operations. Automated LC/MS at scale, older methods redeveloped to save time, chromatography-free methods for speed, and a steady focus on quality and standards.
  • Moving from the population to the individual. Proteomics, metabolomics and spatial mass spec, and a talk that reexamined what “normal” means for an individual patient.
  • The role of AI in clinical testing. Labs are exploring the use of AI for processing and analyzing results, and the final plenary was about how a lab can trust what AI produces.
  • Testing is moving closer to the patient. Remote sampling, dried blood spots, breath analysis and mass spec in the operating room.
  • Toxicology and therapeutic drug monitoring (TDM), from cannabis detection windows to monoclonal antibody therapeutics.

Optimizing clinical lab operations

A healthy share of the MSACL 2026 program discussed lab operations and how to automate and streamline them. Posters and talks evaluated the Roche cobas i 601, including in a multi-site study. One large reference lab described running it at scale and gave it a solid stamp of approval. Another lab described its cobas system adapting to high backpressure on one column by rerouting samples to other columns without stopping the run. There was also a push for speed. Methods that skip chromatography and put the sample straight into the mass spectrometer in seconds came up in workshops, tracks and posters.

One lab discussed optimizing its operations by redeveloping legacy tests: fixing problem tests, combining tests into panels and harmonizing methods so assays share common processes, which freed up staff for other work. Magnetic-bead sample prep came up in talks and workshops, including immunoaffinity purification on the cobas system, fully automated prep with no manual pipetting and high-throughput workflows, along with kit-based methods.

Quality and standards were heavily discussed: guidance for labs developing their own mass spec tests, updates from the new third edition of CLSI C62, Liquid Chromatography–Mass Spectrometry Methods, process quality requirements for diagnostic mass spec, external quality assessment and traceability, and reference methods that help results agree from lab to lab. One session described lab software moving from processing one batch at a time to managing the whole lab, with review, records and quality trends in one place.

Precision, from the population to the individual

One talk reexamined the definition of “normal” when it comes to reference ranges for patient results. Population reference intervals rest on fairly small studies, and tracking changes in one patient’s results over time can bring us closer to the range that matters for that individual.

Drugs act on proteins, and in cancers protein levels often don’t track with mRNA, so proteomics can answer questions genomics can’t, from early detection to whether a drug is hitting its intended pathway. Multiple myeloma and cardiovascular disease had proteomics tracks of their own, cancer had a public special session on future diagnostics, and one award lecture was on ovarian cancer biomarkers.

In metabolomics, large cohorts tracked over years are revealing new markers for things like aging and mortality, and one lab traced how diet connects to tumor growth. The harder part now is processing the data, since the vast majority of signals in untargeted runs are contaminants, artifacts or duplicates rather than unique signals from the subject’s biology. At a SCIEX lunch talk, the ZenoTOF 8600 system’s sliding MS/MS windows were presented as a way to untangle the chimeric spectra common in untargeted profiling.

Spatial mass spec came up across several sessions, including a discussion on fitting imaging into a pathologist’s daily work.

The role of AI in clinical testing

Data science and AI was a recurring theme throughout the week, from short courses on data literacy and machine learning to a coding workshop and a discussion on AI and JMSACL, the conference’s journal. One lab described exploring and evaluating an in-house agent for routine data work that cut a long analysis to a short one, with the caveat that it does worse with an ambiguous prompt.

The final plenary of the week was about verification. AI speeds up the easy work and leaves the more challenging (and time-consuming) work, the judgment about evidence and validity, for us humans to resolve. Expertise can’t be fully written into an SOP, but the speaker pointed out that this community already knows how to get reliable results from imperfect tools, and that the same discipline applies to AI. The quote I wrote down: “The machine proposes. The expert holds the residual.”

Testing is moving closer to the patient

Sample collection outside the lab came up in several places. A discussion covered the regulatory picture for remote sampling, a full track was given to dried blood spots, and posters and talks used capillary and microsampled blood for everything from lead screening to cardiac risk. Breath analysis had its own scientific session and a booth in the exhibit hall.

Mass spec has also reached the operating room, with a talk on assessing surgical margins during cancer surgery.

Toxicology and therapeutic drug monitoring

One plenary discussed studies of chronic daily cannabis users, who take in more THC than they excrete, so it builds up in fat and brain tissue. THC was still detectable in half of chronic daily users after more than 30 days. The speaker also explained that results can swing between positive and negative as exercise releases THC from fat stores. In one study, alcohol and THC together were shown to have a summative impact on impairment. Another study covered kratom, mitragynine, and a more potent metabolite of mitragynine (7-OH mitragynine) that can be synthesized for illicit use, and posters covered fentanyl exposure in newborns, novel psychoactive substances and cannabinoid screening. Finally, monoclonal antibody therapies give labs plenty of reasons to consider TDM: they’re expensive, patient responses vary widely and anti-drug antibodies can develop. The challenge is that the real evidence for monitoring can only be built once the assays exist.

The MSACL community

The best thing about the MSACL community is that its members share reference materials, methods and experience with a common goal: improving patient care. The conference serves that goal with a strong scientific program, a troubleshooting forum and fantastic plenary speakers. It also leaves room for impromptu discussions and networking, with a closing dinner and trivia night and daily networking events late into the evening hours. Next year it’s returning to Montréal, September 26 to October 1, 2027. I hope to see you there.

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