Twenty years ago, determining a single genomic sequence in the lab was a significant achievement. Today, we're whole genome sequencing millions of people, analyzing proteomes at unprecedented resolution, and generating more healthcare data in a day than we did in a year just a decade ago. So much data is being generated that we're at risk of losing the signal for all the noise. And importantly, this evolution in data generation isn't just about the volume of information - it's fundamentally changing how we approach human health. What follows is the story of how I found myself embedded in this evolution, and how it led me to found a company focused on turning this flood of data into actionable insights.
When I was in graduate school, we thought our high-resolution confocal microscopy and Seahorse XF assays were generating significant amounts of data. File sizes bloomed into the megabytes (ha), and we carried around data on thumb drives (haha!). Looking back, those datasets were tiny ripples compared to the deluge of biological data being generated today. Yet even then, there were signs of the coming revolution in data analytics.
At the time, my work on cellular metabolism was pushing the boundaries of real-time cellular analysis, generating types of data that simply hadn't existed before. But I didn't truly grasp the scale of change happening in life sciences until poking my head out of my academia bubble and joining Seahorse Bio. Within my first week, my perspective shifted dramatically. We weren't just serving individual research labs - thousands of scientists worldwide were using our technology in disease areas I had barely considered in my prior academic life. Each of those labs were generating massive datasets. I realized that the challenge was no longer in creating these data; it was in making sense of them.
The industry is drowning in data while thirsting for knowledge.
This challenge wasn't unique to us - it was becoming the defining problem of modern life sciences. Companies were investing millions in data generation capabilities, but the ability to derive meaningful insights wasn't keeping pace. The industry was drowning in data while thirsting for knowledge. In the years since then, the data revolution has only accelerated. Next-generation sequencing became routine, proteomics technologies advanced rapidly, and widely deployed clinical screening became widely available.
I felt this reality acutely. At one point my research team was running 1500 experiments each year, yet we couldn't answer seemingly basic questions about patterns in our data. Which cell lines produced the most variable results? Did that experimental variance correlate with specific operators? The data existed, but the insights remained locked away.
This realization marked a turning point in my career. I began to see that the future of life sciences wouldn't belong to those who could generate the most data, but to those who could extract the most meaningful insights from it. The skills I'd developed - hypothesis generation, scientific method, strategic thinking - were perfectly suited to this challenge.
The industry itself was evolving rapidly. Artificial intelligence and machine learning were being applied to biological data in ways previously unimaginable. Healthcare providers were digitizing millions of patient records. Diagnostic companies were generating complex molecular profiles. And across the industry, a fundamental challenge remained: how do we translate this wealth of data into meaningful improvements in human health?
This burning question led directly to the founding of Terrain. My cofounders and I are building a novel approach to spatial proteomics, but our real mission is larger: we're creating solutions that bridge the gap between data generation and insight for the benefit of patients. Our approach reflects 3 key lessons from witnessing this transformation firsthand.
The life sciences industry continues to evolve at an unprecedented pace. Data generation capabilities grow exponentially, and new AI-enabled approaches for analysis emerge almost daily. Many of these advances are just noise, but there are bright spots and real advances too. For scientists navigating this transformation, the key is developing a broader awareness of how data flows through the entire healthcare ecosystem. The laser focus that serves us well in research must expand to encompass how data becomes knowledge, and knowledge becomes action.
At Terrain, we're tackling this challenge head-on in the spatial proteomics field. Our standardized, clinical-grade assays are designed not just to generate high-quality data, but to produce insights that can directly impact patient care. In twenty years, we could be looking at a healthcare landscape where truly personalized medicine is reality, powered by our mapping system combined with innovative drug delivery technologies. I'm elated to be locked in for that journey - finding signal in all the noise.