When results don't match: navigating scientific integrity in industry-academia partnerships

Picture taken at Alithea Biotechnology GmbH in BerlinBioCube

Teeradon Phlairaharn, a Senior Scientist specialising in immunopeptidomics at Alithea Biotechnology in Berlin, is developing a method that could make advanced mass spectrometry techniques accessible without requiring expensive new equipment. His commitment to open science and collaboration has shaped his approach to navigating the complex relationship between academic discovery and industry influence. Throughout his career, which began with a chance kitchen conversation at the Max Planck Institute, he’s learned that scientific progress often requires uncomfortable conversations, especially when your results contradict established findings. It’s this commitment to publishing findings “in line with scientific integrity” that defines his approach to bridging academic research and industry partnerships.

From mystery box to defining passion

When Teeradon first walked into the Department of Proteomics and Signal Transduction at the Max Planck Institute of Biochemistry in Martinsried as an intern, mass spectrometry was little more than a mysterious ‘big box’.

“I knew almost nothing about mass spectrometry or its capabilities,” recalls Teeradon. “I had only heard that these instruments were both incredibly sophisticated and expensive, and I was eager to learn more, seeing it as a rare and valuable opportunity.”

His very first experiment, measuring plasma samples on a Q Exactive, sparked what would become a defining passion. “I was so impressed that I immediately wrote to my supervisor and advisor to share my excitement,” he remembers. “I was fascinated by how much information could be extracted from this ‘big box,’ and that first experience sparked a deep and lasting interest in mass spectrometry.”

The kitchen conversation that changed everything

A chance encounter in the institute’s kitchen would set the trajectory for his research focus. He had already been introduced to the BoxCar method developed by Florian Meier, a postdoctoral researcher in their group, though he admits he “couldn’t fully grasp the complexity of his work” at the time. This challenge motivated Teeradon to understand projects like this.

“One day, by chance, I met our group leader in the kitchen, and he casually asked if I would be interested in working in a similar direction. I immediately said yes.” That “yes” launched a research journey that would eventually lead him to work under renowned scientists Brian Searle, Erwin Schoof, Hamish I. Stewart, and Denis Chernyshev, whose mentorship helped shape his understanding of mass spectrometry and inspired him to explore its vast potential.

Challenging assumptions: when less is more

A pivotal moment that shaped Teeradon’s philosophy came during his bachelor’s thesis, where he worked on using linear ion traps to analyse low-input samples. This project fundamentally changed how he viewed the relationship between cutting-edge technology and impactful science.

“It sparked a deeper interest in making mass spectrometry more accessible and cost-effective, as linear ion traps are not only more affordable than other high-resolution mass analysers but also provide high sensitivity,” he explains. “It also changed my perspective, showing me that impactful research doesn’t always require the newest, most cutting-edge instruments. Instead, it’s often about selecting the most suitable setup for the question at hand.”

This philosophy of thoughtful tool selection extends to his current work, where he’s found that high-quality analytical columns from companies like IonOpticks can significantly enhance workflows in challenging applications where data quality is critical. “Our results show that these columns can significantly enhance workflows in low-input proteomics, including both immunopeptidomics and single-cell proteomics,” he notes. “The peaks are exceptionally sharp.”

MAP-MS: standing on the shoulders of giants

Today, Teeradon’s work centres on MAP-MS, a project that represents the fulfillment of his “longtime goal of contributing to a project inspired by MSX and BoxCar.”

To understand the significance of MAP-MS, it helps to grasp its inspirations. “BoxCar is a method that improves how we detect precursor ions by splitting the scan into smaller ranges, which helps capture low-abundance signals more clearly. MSX, on the other hand, speeds up and improves fragmentation by analysing multiple precursor ions at the same time. In short, BoxCar makes the MS1 signal more sensitive, while MSX makes MS2 analysis more efficient.”

MAP-MS draws from both approaches, offering what Teeradon hopes will be “an alternative way to acquire data” that researchers can explore and apply to their own biological questions. Importantly, the method doesn’t require new hardware purchases, aligning with his commitment to making advanced techniques more accessible.

Learn more about MAP-MS and read Teeradon’s full preprint.

Navigating scientific integrity in an industry-influenced field

Working at the intersection of academic research and industry allows Teeradon to pursue his own scientific curiosities and choose research topics that inspire him. At the same time, he must navigate the complex relationship between academic integrity and industry partnerships. For one, the need to align his efforts with broader project goals has taught Teeradon to balance his personal curiosity with practical impact.

Moreover, his research sometimes produces results that contradict published work, creating delicate situations that require careful handling.

“Sometimes our findings differ from previously published results in the community, which has put us in a difficult position especially when deciding whether to publish results that might contradict the work of peers or our industry partners,” he admits. “We have always chosen to publish and present our findings in line with scientific integrity, even though it can be challenging to keep everyone happy.”

To Teeradon, it’s about finding the right balance while staying true to the role of a scientist, “particularly in a field where industry partners can influence publications and where much of the literature resembles industry-produced white papers.”

His approach to these situations shows an appreciation of the multidisciplinary nature of MS-based omics. “When results appear contradictory, we usually take a step back and carefully review the experimental setup, first considering the technical aspects and possible sources of variation to avoid bias,” he explains.

Picture taken at Alithea Biotechnology GmbH in BerlinBioCube

Because researchers may approach problems and interpret results from different perspectives, Teeradon’s group always make sure to examine instrument performance, data quality, and data processing methods in detail. “It’s rarely about someone making a mistake; rather, as a scientific community, we value sharing results and open discussion.”

This philosophy has led to some interesting findings in his recent work investigating how ion numbers influence peptide fragmentation spectra across different mass analysers for low-input applications. “Using our acquisition method, our results show that orbitrap mass analysers don’t produce atypical fragmentation patterns and are suitable for low-input proteomics analysis” – a finding that challenges some prevailing assumptions in the field. Teeradon and his group look forward to sharing these results with the broader scientific community soon.

Waiting for technology to catch up

Balancing his scientific work with a Master’s in Management at the Technical University of Munich’s School of Management, where he focuses on marketing analytics with particular interest in early-stage biotech startups, Teeradon has developed a unique perspective on the pace of scientific progress.

“I would tell myself not to rush into research, but to take things slowly,” he reflects when asked what advice he’d give his younger self. “Technologies, including instrumentation, separation devices like analytical columns and liquid chromatography, or software for data analysis, are constantly evolving. If I don’t achieve the desired results the first time, it’s often worth waiting for technological advancements and then revisiting the idea to try again.”

He points to single-cell proteomics as a perfect example: “Advances in next-generation instruments, improved sample preparation techniques, and developments in analytical columns and liquid chromatography systems have made single-cell proteomics not only possible but also increasingly accessible to more researchers in the field.”

This example highlights, to Teeradon, how collaborative science can enable us to achieve goals more effectively than working individually. “And synergies from vendors play an essential role in advancing the field,” he adds.

Looking forward: AI and the future of proteomics

At the intersection of academic research and industry, Teeradon has a front-row seat to observe emerging trends in proteomics. He’s particularly excited about the integration of artificial intelligence and machine learning into data analysis and interpretation.

“Advances such as deep learning-based spectrum prediction, improved peptide identification algorithms, and AI-driven protein structure prediction are accelerating workflows and enabling us to extract more information from complex datasets,” he explains. “In the future, I believe AI will help bridge the gap between raw mass spectrometry data and actionable biological insights, making proteomics more accessible and impactful across both research and clinical applications.”

The collaborative spirit

Throughout his career, Teeradon has maintained a commitment to open science and collaboration that reflects his broader philosophy about scientific progress. His work on MAP-MS embodies this approach: it’s designed to be accessible, doesn’t require expensive new equipment, and actively encourages co-development and collaboration.

“We’re happy to contribute even if industry partners adapt our work for commercial use, as this demonstrates our commitment to supporting the broader scientific community,” he says. It’s a perspective that reflects his understanding that the best science happens when knowledge flows freely, even when that means navigating the occasional uncomfortable conversation about contradictory results or challenging established thinking.

“Especially when our findings differ from published data, our first step is to reach out to collaborators and industry partners to exchange insights and gather opinions. We believe in making results public and fostering collaboration, rather than competing.”

In a field where sophisticated instruments and cutting-edge methods often dominate the conversation, Teeradon’s journey offers a reminder that the most important scientific instrument might just be curiosity – and the wisdom to know when to wait for the right tools to catch up to big ideas.

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