Cerno Bioscience CEO Discuss Business Trends and Analytical Challenges in Calibration

At the 2025 American Society for Mass Spectrometry (ASMS) Conference in Baltimore, Maryland, we sat down with YongDong Wang, co-founder and CEO of Cerno Bioscience, to discuss evolving trends in calibration, and the future of the field.

In the first part of this interview, Wang shares background on Cerno Bioscience, which develops vendor-neutral software designed to streamline spectral analysis across mass spectrometry (MS) platforms. Cerno currently partners with several major instrument manufacturers, including Agilent and Thermo Fisher Scientific, and is actively expanding into new markets such as Central and Eastern Europe, Southeast Asia, and beyond.

Tell me about what you’re showcasing at ASMS this year. Is there anything you’d like to highlight?

Wang: We have made a name for ourselves with our vendor neutral mass spec software’s ability to calibrate nominal mass data into accurate mass information. We are the only software company who can do this because of our patented technology. We can perform the calibration, whether you have gas chromatography (GC), mass spectrometry (MS), or liquid chromatography (LC)–mass spectrometry (LC–MS), single quad or triple quad, we can turn that an existing instrument into an accurate mass machine capable of deeper more accurate insights.

This year we have two posters that showcase our software’s broad capability to enhance performance across both high- and low-resolution mass spec instruments.

Our first poster is focused on applying ion chromatography (IC) to MS and showcases how our software unlocks new market potential by enabling precise identification and quantitation of small organic molecules and metals in complex samples—making high-value material inspection and environmental analysis possible on widely available instruments. We demonstrated that, using our software’s calibration technology, we can improve mass accuracy to differentiate very similar compounds and perform spectral deconvolution to make quantitation more accurate. The second poster demonstrates how our software enhances even the most advanced mass spectrometers, like the Orbitrap, by enabling confident identification of completely unknown compounds—unlocking new discovery potential in high-value fields like metabolomics, proteomics, and environmental analysis.

We applied our software to the Orbitrap Lab, which is a very popular high-res instrument—known for being much more expensive and demonstrating much higher performance than other mass spec instruments.

Even on high-resolution instruments, unfortunately, you still encounter unknown compounds, and you have no idea what they are. You don't know what elements might be involved—whether you're doing metabolomics, proteomics, natural products, flavor, or environmental.

Our software’s calibration technology is able to uniquely identify compounds that are totally unknown, and provide a highly confident, single-compound identification.

What unique analytical challenges are you hearing from customers as they dive deeper into emerging areas like proteomics or metabolomics that make analysis more difficult?

That’s where it gets the most demanding, because you don’t even know where to start the search, right? People use all sorts of technologies—computational, hardware, software. They use the highest-end instrumentation systems, which can cost as much as a million dollars each. And you also see a lot of people using artificial intelligence (AI) to do better mining. They build a tremendous number of databases that encompass all sorts of compounds, all sorts of spectra, and all sorts of instrument conditions. That approach might work, if you have enough data to feed into the system.

We took a more traditional, analytical, fundamental approach—to look at where the data comes from and how we can get the best part, the highest quality data, by operating the instruments at their best possible analytical performance. We evaluate them and then combine all the available information using our calibration technology to tease out answers—without requiring a tremendous amount of data, a huge number of experiments, or a massive AI engine to make predictions. Instead, we compute it analytically from the outset—even without a library.

We tested on 26 small molecule compounds, and out of the 26, all of them—100%—could be uniquely identified with high confidence. No library, no training sets. Simply by operating the instruments according to good old analytical chemistry—understanding how it works, how it should work, and evaluating them to achieve the best possible performance.

Other than metabolomics, what would you say is the next most commonly requested application that's challenging for folks?

Wang: Other challenging applications that we provide superior accuracy for include product quantity, QA/QC applications, material inspection, incoming material inspection for potential contaminants. Also process control, environmental studies, and medical and biomarker research.