Where Are the Greatest Opportunities for Innovation in Mass Spectrometry?

At the 74th ASMS Conference on Mass Spectrometry and Allied Topics, experts in mass spectrometry gathered to discuss the latest innovations in research, method development, hardware, and software.

Throughout the presentation of scientific breakthroughs and new techniques, conference attendees also spoke about their visions for the future of the field, including more sustainable instrumentation, smarter software, and emerging technologies that could revolutionize analytical science.

To learn more about the future of mass spectrometry, Technology Networks asked a range of experts present at the conference: "Where do you see the greatest opportunities for innovation in mass spectrometry?"

Frederick Strathmann, PhD. Senior vice president of global business at MOBILion Systems

"It's a really interesting question because it depends on who you talk to; innovation is going to look different for everybody. But I think what we are seeing right now with mass spectrometry is that it is getting easier, smaller, and greener. For some people, that is fantastic because it lowers a lot of the barriers that they would have had issues with in the past. But other people are still looking for peak performance—they want to get more out of their systems.

"Improving data quality is perhaps one of the most exciting opportunities. One of the reasons why people buy high-res instruments is because they want to figure out what an unknown is, but this always comes with the "price tag" of eventually needing to get a standard made, because if you don't have a standard, then you are going to have a hard time determining anything. Ion mobility—and particularly high-res ion mobility—has the chance to upend that. Maybe you won't need a standard; maybe the 99.99% confidence you'll have is enough. If you have these kinds of measurements, that will revolutionize the way that drugs are discovered, the way we identify unknowns in the environment, and the way that regulation can happen. That will accelerate discoveries significantly beyond the capabilities we have now."

Melissa Sherman, PhD. Chief executive officer at MOBILion Systems

"At the high end, I think one of the largest barriers in mass spec is the expanding complexity of it. The users have to be really high-skilled and highly-trained people. I think anything that lowers this complexity barrier from an ease-of-use perspective is going to change the game.

"Just think about affinity techniques; there are a lot of other techniques that have come in where new segments are being created and billion-dollar businesses are being started in other areas largely because these are easier to use, not because they are necessarily the best analytical answer. This is a really important trade-off—most people would likely agree that mass spec gives the purest, most accurate analytical answer, but if it's too difficult to use, then it simply won't be used. Lowering the barrier of complexity through automated systems, LLM-based user interfaces, and other technologies can really help to lower that barrier of adoption from a complexity perspective."

Matthew Lewis, PhD. Vice president, metabolomics and lipidomics at Bruker Daltonics

"I believe, based on how technologies have developed to address other omics areas in the past, significant opportunities for breakthroughs could emerge in areas such as parallelization.

"I started out running sequencing gels by hand, then that became capillary arrays, then next-generation sequencing, and then came more and more multiplexing. Sequencing could do that because you can effectively barcode a sample. There’s no direct equivalent in metabolome measurement—metabolites are the same molecules in every sample. But parallelization is a different problem to multiplexing, and one that’s more tractable. Today, sample analyses are still fundamentally serial—one sample through one analyser at a time. In principle, parallelization could help move the field toward measuring whole populations. Currently, the only solution we really have for that is for people to deploy more individual systems or use higher-throughput methods. But a more efficient, more parallelized array approach is conceptually exciting to me. What that would look like in implementation, I don’t yet know.

"From a future applications standpoint, I firmly believe that the exposome is where we should be focused. There are industries out there whose business depends on creating new chemicals, with hundreds of thousands of chemicals and mixtures already registered for production and use globally. The world around us is always changing because of this influx of new chemistry, and whether we like it or not, we're interacting with that. To me, this is the "forever frontier"—looking at how we deal with our exposures and the environment around us."

Gary Harland. Senior director and portfolio owner for discovery, characterisation, and imaging HRMS at Waters Corporation

"To bring liquid chromatography–mass spectrometry to everywhere where it has the potential to be used, we need to make those systems completely accessible to people who don't know much about mass spectrometry. Also, AI is very much part of the way that we are thinking now, even just in terms of how our engineers work, how our scientists work, and how we can build that into the instruments' software.

"It is going to be a very different space, I think, in 5–10 years' time. And that pace of change is accelerating." — Gary Harland.

"I think the ability to make devices that give the right results without an expert or a person needing to know how to tune and set up these instruments, a person who maybe doesn't understand what resolution is, that is a key part of the task as well. We are technologists; we love to drive forward innovation in technology, but that [accessibility] is a key theme in how we are thinking about development work."

Geoff Winket. General Manager and Vice President, Spectroscopy and Vacuum Division at Agilent Technologies

"I would say automation. From our history as a company, looking at these instruments, things are changing rapidly—especially around workflows and how instruments can automate that workflow.

"We had a customer around a month ago say that they wanted a dark QA/QC lab and they wanted us to help them get there. At the moment, people are running all of these instruments with some level of automation, but we're just scratching the surface. It’s about more than an autosampler or an autodilutor. It's about hardware, software, and taking humans out of the process completely.

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"To me, that is the next revelation in not just mass spectrometry, but across most analytical equipment."

Shane Tichy, PhD. Associate vice president, LC-MS R&D at Agilent Technologies

"If we were to go back 15 years ago, a single instrument would barely fit in this room. If you were to go even further back to the late 90s or early 2000s, when it was all about Fourier-transform ion cyclotron resonance (FT-ICR) and using a huge 21 Tesla magnet, bigger was better.

"That's not the future. The future is looking at how we get 10 instruments in a room, while not affecting the HVAC (heating, ventilation, and air conditioning) power consumption by having those 10 instruments running. Those instruments also need to have this same level of performance as the 21 Tesla magnet and the FT-ICR.

"The biggest challenge is, how do we continue to make these instruments to a sustainable level that our customers can accept, while also not sacrificing performance." — Shane Tichy, PhD.

"Analytical challenges are always continuing to grow, and so that's on us to figure out how to make these autonomous instruments smaller, more sustainable, and capable of delivering results."

Ansgar Korf, PhD. Chief executive officer at mzio

"To me, the greatest opportunity is easily software. All of the instruments are getting faster, more accurate, and producing more data. For us, as a scientific community, it is necessary to extract the most out of that data. This was already a challenging task 20 years ago, but it gets more and more challenging every day.

"With advances in software, plus what AI can now bring to the table, we have so many new tools and possibilities. I think software will be game-changing here."