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Techniques & Tools Data Analysis, Liquid Chromatography, Mass Spectrometry, Sample Preparation, Technology, Chemical, Environmental, Metabolomics & Lipidomics, Pharma & Biopharma, Proteomics

Looking Back, Moving Forward: With Koen Sandra

What would you say has been the field’s biggest accomplishment over the past five to ten years?
 

I think the evolution we’ve seen in mass spectrometry over the past decade has been incredible. It’s unbelievable how many analytical questions we are able to tackle with current technologies across various domains – in chemical, pharmaceutical, biomedical, food, and environmental sciences. The progress is really remarkable!

To give an example, today with high-end mass spectrometry we can study thousands of proteins within a single cell in just half an hour. To put that into perspective, 20 years ago, when I worked at a biomarker company, it took us half a day to identify 1,000 proteins from a sample of 1 million cells. So we’ve gone from 1 million cells to a single cell, and from half a day to half an hour – that’s quite an accomplishment.

Ron Heeren spoke about the "resolution revolution." Although resolution is indeed an important aspect of mass spectrometry, I’ve been particularly impressed by the advancements in speed, sensitivity, robustness, and data-handling capabilities of mass spectrometry. Regarding robustness, today’s mass spectrometers can keep running with minimal intervention, which is a huge improvement compared to a decade or two ago. As for data-handling capabilities, I always advise people to look closely at their data. These sophisticated instruments generate brilliant results, but they also produce a lot of irrelevant or "junk" data, and relying solely on software algorithms to make sense of it all isn’t ideal. That human touch – critically evaluating the data ourselves – is still essential. I often tell my team this, and though they laugh at me sometimes, they often come back later to admit that I was right!

One area particularly close to my heart is the biopharma domain, where we’ve seen tremendous advancements in protein analysis over the past decade, largely driven by the rapidly evolving antibody market. Antibodies are now among the top-selling medicines and are dramatically improving patients’ lives. With the rapid development of these products comes, of course, the need for advanced analytical methods.

In this field, we’ve seen the introduction of new reagents, advanced columns, and inert instrumentation (such as HPLC columns) which have proven very beneficial. Multi-dimensional liquid chromatography has also made significant strides, progressing from two dimensions to three and even four dimensions, often incorporating chemical or enzymatic reactors.

Over the last decade we’ve also seen previously incompatible chromatographic methods, like ion exchange, size exclusion, and affinity chromatography, being directly coupled with mass spectrometry. The coupling of affinity chromatography to mass spectrometry is particularly exciting as it enables us to study the structure-function relationship of antibodies in ways that weren’t previously possible. Native mass spectrometry has also seen widespread adoption, which has been a game-changer. It allows us to measure proteins that were previously unmeasurable, opening up new possibilities. Beyond primary structural analysis, we’re now using mass spectrometry to study higher-order structures and protein interactions, which is relatively new.

When we consider all of these advancements, we’re now able to study the structure and function of antibodies in incredible detail. This ultimately benefits patients by enabling the development of well-characterized products in a more timely and efficient manner.

Looking back over the last year, considering conference themes and key papers, what innovations or major trends stood out in 2024?
 

I attended quite a few conferences in 2024, and three major topics regularly came up: artificial intelligence (AI), nucleic acids, and "forever chemicals." 

I recall sitting down with your colleague Rich Whitworth a couple of years ago at the HPLC meeting in Düsseldorf around 2 years ago. At that time I was surprised by the limited number of AI-related lectures, but that's already changed dramatically. We witnessed an overload of AI topics this year, addressing areas such as method development, data analysis, and automation. That being said, the term AI is currently used quite loosely, even for topics that aren’t actually relevant – but I suppose that’s typical of how trends evolve.

Another emerging trend is nucleic acid analysis. It’s an interesting evolution because, for a long time, conferences and literature have been dominated by proteins and antibodies. While that’s likely to remain the case for a while, new modalities based on nucleic acids – like oligonucleotides, messenger RNA, and transgenes – are clearly on the rise. These bring their own analytical challenges and are an exciting field to watch.

In addition, there’s been a lot of focus on PFAS (forever chemicals). Our mailboxes have been flooded with information on PFAS measurement. These chemicals are being measured at extreme sensitivities in a wide range of matrices nowadays, including blood, soil, and water. Most methods today are targeted, using LC-MS with triple quadrupoles and sample preparation techniques like solid-phase extraction to concentrate and clean up samples. However, a growing trend is non-targeted screening using high-resolution mass spectrometry and ion mobility. This approach allows us to look beyond the usual suspects, which is important since there are thousands of PFAS chemicals and current methods typically only target a few dozen. Rapid detection, high-throughput analysis, and portable field-testing technologies are also emerging as important development areas in this domain.

Another area worth mentioning is omics, which was omnipresent at conferences again in 2024. Buzzwords like single-cell omics, spatial omics, and multi-omics were everywhere! I saw some great advancements, particularly in automation. One lecture showcased a fully automated single-cell proteomics workflow, covering everything from cell isolation and protein extraction to digestion, LC-MS analysis, and database searching. The presenter even showed a video of robots moving samples from the prep station to the LC-MS system – a fascinating demonstration. Omics continue to hold great potential for deepening our understanding of disease mechanisms, which should eventually lead to new treatments and advancements in personalized and precision medicine.

What would you say are some of the biggest challenges facing the field at the moment?
 

There are quite a few challenges, but for me, one of the most obvious ones is how to inspire and educate the next generation of analytical scientists. I see the field struggling with this – it’s becoming increasingly difficult to find skilled scientists with a critical mindset. It’s relatively straightforward to find people who can use the equipment, but finding those with in-depth knowledge and a deeper understanding of the technology is much more difficult. And to be honest, I don’t blame them entirely. Instrument vendors are developing more and more "black box" systems, meaning users no longer need to think about what’s happening behind the scenes.

Another major challenge is handling big data. Our instruments generate massive amounts of information every day, and interpreting it all is a daunting task. AI has the potential to play an important role here, but it also pushes us out of our comfort zones. As scientists, we now need to learn the "language" of informatics and engage with computational tools in ways that are currently unfamiliar to many of us.

Sustainability represents another key issue. While maintaining the highest analytical standards, we also need to reduce our ecological footprint. Miniaturization is one area we can focus on – not just in separation techniques but also in sample preparation. Many current methods still require liters of solvents to prepare a single sample, which is hardly acceptable in 2024.

Lastly, we’re facing challenges with new study objects, like sustainable food products (e.g. lab-grown meat, plant-based dairy) and novel therapeutic products based on proteins or nucleic acids. These innovations require us to rethink and expand our analytical toolbox to analyze them effectively. That being said, these challenges are also what makes the field exciting. Reinventing our tools and techniques is what we, as analytical scientists, thrive on. So while there are significant hurdles, the future is also bright for analytical scientists.

Are there any society-wide trends that you see impacting the field at the moment?
 

Yes, quite a few of these trends have already been addressed to some extent. Our field is increasingly moving in response to societal needs and pressures. For example, today we’re studying the aroma of lab-grown meat because our current food system is neither sustainable nor animal-friendly. Reinventing our food supply is essential, especially considering that we need to feed the 8 billion people on this planet equitably.

Similarly, the fact that analytical scientists are measuring pollutants like microplastics in blood, food, and environmental samples reflects growing awareness of environmental issues and their impact on health. This heightened consciousness drives our work in these areas.

In our lab, for instance, we’re conducting many measurements on GLP-1 agonists, which are the active compounds in medications like Ozempic. This focus stems from the increasing prevalence of diabetes and obesity as significant health concerns.

Our field is adapting to address these critical issues where the needs are greatest, and I believe we’re doing a good job in that regard. Along the way, we’re also embracing trends like AI, applying it in methodologies and data analysis, and adopting green analytical chemistry principles to minimize environmental impact.

Thinking about the future, what do you think needs to happen to make progress in the areas discussed? Are we missing anything from the toolbox, or are there other big milestones we need to achieve?
 

The toolbox will never be truly complete, which is part of what keeps our field exciting and full of opportunities. For example, in the biopharmaceutical field, there’s a clear need for technologies that can provide deeper insights into large molecular assemblies like lipid nanoparticles and viral vectors.

One specific need is for a mass spectrometer capable of measuring in the mega-Dalton range – having such a tool could reveal whether mRNA is encapsulated within lipid nanoparticles or if a transgene is present in a viral vector. In an ideal scenario, this same mass spectrometer would also work in the kilo-Dalton and Dalton ranges, enabling it to handle antibody measurements and lipidomics. That might be asking for a lot, but it would be a game-changer – especially if the instrument could be made affordable. Cost is a significant factor, as these advanced systems are becoming increasingly expensive.

Sticking with the biopharma domain, we often use dozens of different methods to gather complementary information about these molecules. Combining these methods into a single technology capable of assessing multiple structural and functional attributes would be a major step forward. There’s already work being done in this area, and the concept has even been given a name: MAM, or Multiple Attribute Method. This approach has the potential to streamline analysis and reduce costs significantly.

There’s also an opportunity for advancements in multidimensional liquid chromatography, which ties into a broader trend: automation and integration. These seem to be the "Holy Grail" of analytical science right now. With automation and integration often comes miniaturization, which in turn promotes sustainability. If we succeed in achieving these goals, it would be a win-win for everyone involved.

How positive are you about the current state of analytical science?
 

I’m quite positive. It’s truly amazing what we’ve achieved over the past decades, building on the incredible work of the early pioneers in the field. 

Looking ahead, I see a bright future for analytical science. There’s so much exciting potential in the advancements coming our way. I’m optimistic about the contributions we can make – to health, the environment, and beyond. I’m definitely looking forward to what lies ahead.

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