LESSONS FROM 560 BIOMARKERS
Stanislav Skakun
Stanislav Skakun runs a personal biohacking experiment since 2014, measuring 560 biomarkers on monthly basis and managing dozens of personalized interventions simultaneously. With thousands of datapoints to date, this is probably one of the most well documented biohacking longitude case-study available worldwide.
Stanislav Skakun, a finance expert and data scientist, shares his unique two
We should know our biomarkers like we know our electricity bills. This is going to be very important in the nearest future because we are coming up with more and more interventions which will work for healthy aging.
Summary
- Applying financial performance measurement and data science to human biology enables the creation of a detailed, longitudinal health model through hundreds of monthly biomarkers. - Successful biohacking requires a rigorous documentation process and testing one intervention at a time to verify causality through follow-up testing and biomarker restoration. - Comprehensive biomarker panels can identify dozens of latent health risks in asymptomatic individuals, allowing for targeted interventions with over 90% specificity and precision. - Organizing biological data into categories like homeostasis, inflammation, and the microbiome simplifies the interpretation of complex metabolic pathways and gene-regulating aging processes. - Biological data is evolving into a commodity that powers aging research, making regular monitoring of biomarkers as necessary as tracking basic expenses like electricity bills.
Article
Lessons From 560 Biomarkers
A Data-Driven Approach To Health Risks And Longevity
At the Biohacker Summit 2017 Helsinki, held in Helsinki, Finland, on 13 and 14 October 2017, Stanislav Skakun stepped onto the stage with a proposition that sounded at once coldly analytical and deeply personal: what if the body could be managed with the same rigor as a balance sheet?
Skakun, a finance expert and data scientist rather than a physician, described a self-tracking experiment that began in 2014 and had grown into one of the most exhaustively documented personal biohacking case studies in the world. Month by month, quarter by quarter, he had measured hundreds of biomarkers, building a longitudinal map of his own biology in an attempt to identify hidden risks before they became illness.
“I look at my business through a set of indicators and I put the same approach to human biology,” Skakun said during his presentation, *Lessons From 560 Biomarkers*. “I choose an informative set of biomarkers to track every system, organ, and health risk I might have in the future.”
Turning Biology Into A System Of Indicators
The power of Skakun’s talk lay not in futurist spectacle, but in method. He argued that health, often treated reactively until symptoms appear, could instead be observed as a stream of measurable signals. In his model, those signals included roughly 560 biomarkers in total, with 200 to 300 tested each month, most of them through blood work.
Over time, that approach produced thousands of data points. Some markers were measured monthly, some quarterly, others biannually. Together they formed what he described as a longitudinal model of the human organism, one capable of detecting deviations while they were still subtle, perhaps even silent.
This was not a vision of wellness built on intuition. It was a case for disciplined measurement. Skakun said the same logic used in financial performance analysis could be applied to organs, metabolic pathways, inflammatory status, hormones, diet, microbiome composition, and physical performance.
The result, he suggested, was a more coherent picture of future health risk, and with it the possibility of acting early.
The Unromantic Truth About Biohacking
There was, however, nothing glamorous in the way Skakun described the work itself. He dismantled the fantasy of biohacking as a life of dramatic breakthroughs and clever shortcuts. In reality, he said, it was mostly reading, record-keeping, and repetition.
“Ninety percent of this experiment is reading and ninety percent of what is left is grinding the organism with analysis,” he said. “Only one percent of this exciting life is actually about scientific discoveries and experiments on yourself.”
That line landed because it exposed something larger about the self-optimization era. Behind the rhetoric of disruption and personal reinvention lies a quieter, more difficult labor: absorbing the literature, organizing the evidence, and resisting the urge to mistake novelty for knowledge.
Skakun said he had spent years trying to close his own knowledge gap in biology, often reading 30 to 40 scientific articles a day. The challenge was not only learning, but structuring what had been learned into a system that could be revisited and tested.
The Discipline Of Documentation
If there was a single principle running through Skakun’s account, it was documentation. Every article, every hypothesis, every biomarker trend, every diagnosis, every intervention, every follow-up had to be captured and organized. Without that record, he argued, personal experimentation collapses into anecdote.
“Each step should be documented because otherwise you won't be able to go back and understand what has happened,” he said.
His method relied on building a personal knowledge base, using digital tools to store research and sort it into categories that made sense to him. He recommended keeping the system simple enough that it would remain usable over time.
“When you are collecting data and trying to understand it, keeping it simple is the best way to keep it up,” he said.
That simplicity mattered because the volume of information was immense. Data, in this framework, was not liberating on its own. It had to be made legible.
One Intervention At A Time
Skakun also warned against the familiar temptation of modern self-experimentation: changing everything at once. A stack of supplements, a new diet, altered sleep, added exercise, medication, fasting. The more variables introduced simultaneously, the less one knows about what actually worked.
“You don't change everything overnight,” he said. “You pick up one thing at a time and put it to a test.”
His standard for confidence was what he called the “cancellation effect”. If a supplement or medication appeared to improve a biomarker, it should then be withdrawn. If the biomarker returned to its previous state, the causal link became far more credible.
“Only if you have a cancellation effect and the biomarkers restore to normality can you be sure you have arrived at the right decision,” he said.
It was a strikingly conservative principle in a field often accused of overreach. For Skakun, self-experimentation was not about maximal intervention. It was about isolating signal from noise.
Hidden Risks In Apparently Healthy Lives
One of the most arresting claims in the presentation was that extensive testing could reveal latent problems in people who felt entirely well. Skakun said that before he began, he had no health complaints. Yet through his panel he identified around 40 potential health risks, many of which he then tried to address through supplements, lifestyle changes, and, in some cases, pharmaceuticals such as Metformin and Aspirin.
He reported that most of those risks had been managed, though several remained unresolved. He also said that false alarms were relatively few, arguing that his system had shown more than 90% specificity in practice.
This mattered because it challenged a common criticism of broad biomarker testing: that it produces anxiety, overdiagnosis, and noise without practical value. Skakun’s answer was that large panels need not be meaningless if they are interpreted within a structured model and tied to follow-up action.
He extended the point beyond himself, describing a focus-group style effort in which other people underwent smaller but still extensive panels of around 300 biomarkers and received reports he deemed actionable.
Inflammation, Aging, And The Search For A Common Language
To make the complexity manageable, Skakun grouped biomarkers into categories such as homeostasis, inflammation and immunity, diet, physical fitness, hormones, and microbiome. The largest conceptual weight, perhaps, fell on inflammation, which he framed as one of the central pathways of aging.
He linked this to the broader scientific framework known as the Hallmarks of Aging, a key reference point in longevity research. In Skakun’s telling, biomarkers were not merely isolated readings. They could be translated into the language of metabolic pathways and genetic regulation.
Aspirin, for example, was not just a pill but a modulator of inflammatory signaling. Metformin was not merely a diabetes drug but part of a larger conversation about metabolism and aging. The body, in this view, became interpretable through interacting systems rather than disconnected test results.
That attempt to create a “universal language” of biology was one of the most ambitious parts of the talk. Aging, Skakun suggested, could be understood as dysregulation in how genes and pathways function. Biomarkers, interventions, and visible outcomes could all be described within that same framework.
Why The Microbiome Mattered More Than Genetics
Among the many claims Skakun advanced, none was more provocative than his insistence on the centrality of the microbiome.
“Knowing your microbiome is about ten times as important as knowing your genetics,” he said.
His reasoning was functional rather than rhetorical. The human body, he noted, produces around 20,000 proteins, while the microbes living within it generate roughly 200,000, many of which interact directly with human physiology. Those microbes, he said, act like biological machines inside the body, influencing health in ways that genomic testing alone cannot fully capture.
In an age obsessed with DNA kits and ancestry reports, the remark served as a corrective. If genetics offers a script, the microbiome may be one of the actors constantly rewriting the performance.
Biological Data As The Next Commodity
Toward the end of his presentation at Biohacker Summit 2017 Helsinki, Skakun widened the frame beyond personal experimentation. Biological data, he argued, was becoming a commodity, increasingly valuable to insurers, healthcare providers, pharmaceutical companies, and longevity researchers.
He pointed to emerging platforms such as Young.AI and Gero, which allowed individuals to upload health data, estimate biological age, or participate in broader data ecosystems that might eventually connect monitoring with healthcare incentives.
There was something quietly radical in that forecast. To know one’s biomarkers, Skakun suggested, might soon become as normal as knowing one’s utility bills. The quantified self, once niche and eccentric, could harden into infrastructure.
That possibility carries its own unease. Data can empower, but it can also be priced, traded, and governed. Still, Skakun’s message was less cautionary than pragmatic. The systems were coming, he implied. Better to understand them, and perhaps shape them, than to remain passive inside them.
The Body As Evidence
What lingered after Skakun’s talk was not simply the number 560, impressive though it was. It was the underlying ethic: that health could be approached as an evidence problem, one requiring patience, humility, and a willingness to confront the body not as mystery alone, but as record.
This was not medicine in the institutional sense, nor was it mere self-help. It was a hybrid form of personal science, awkward at times, ambitious throughout, and rooted in the belief that hidden risks could be surfaced before they become fate.
At Biohacker Summit 2017 Helsinki, Stanislav Skakun did not offer the audience immortality, nor even certainty. What he offered was something more grounded and perhaps more unsettling: a future in which longevity begins not with miracle cures, but with spreadsheets, blood panels, disciplined skepticism, and the slow accumulation of proof.
Part of Biohacker Summit 2017 Helsinki