Why I built this

A named founder, not a faceless app.

You're being asked to hand over the most personal file you own. You should know who's asking.

"I didn't build MarkerView because of my résumé. I built it because of what I found in my own results."

I hold two graduate degrees — a Master of Biomedical Science from Rutgers University, where I concentrated in stem cell biology, and an MBA from Villanova University specializing in artificial intelligence and machine learning. Before either of those, I studied Biology at Drexel and spent years in academic and pharmaceutical research.

For years I watched the pieces of a person's health sit in separate silos: DNA in one company's vault, bloodwork in a patient portal, medications at the pharmacy, supplements on the kitchen counter. No single service used today's AI to look at them together and produce something a physician could actually review. So I built one.

Then I ran my own file through it. I learned I carry DNA variants I can pass on to my sons — they're five and eight. Variants I never would have known to ask about.

And I learned something that stopped me cold: one of my daily prescription medications has two direct contraindications with two supplements I was already taking. Both are common. One is so ordinary you can buy it at any retail pharmacy — so ordinary it never occurred to me to even mention it to my primary care provider. There's no black-box warning. There's nothing on either bottle. The risk only became visible when my medications and my supplements were reviewed side by side.

MarkerView exists so you can find these things the way I did — before they matter, not after.

💌 I believe in this enough to share my own results. Email [email protected] and I'll send you my personal, real MarkerView report as a free sample. No signup required, and nothing to cancel.

— Greg Conner, Founder

That report is my actual data, not a marketing sample — which also means it isn't typical. Results vary; most reports contain entirely different findings. Always discuss your own results with your physician before changing any medication, supplement, or care.

Connect on LinkedIn →

What that means for the product

Two habits that came straight out of the science training.

Claims name their source — and admit when they have none. Marker mappings come from curated clinical databases and industry-standard, open-source annotation tools, not from a model's memory. Drug–gene findings carry the CPIC or PharmGKB guideline and its PubMed ID; a finding with no guideline behind it is labelled as such. AI writes the explanation. It doesn't invent the science.

Rare, alarming calls don't get headlined. Consumer DNA arrays are screening-grade, and a rare "pathogenic" hit on array data is frequently a false positive. Building the product meant deciding, on purpose, not to lead with those — and to tell you how well your file actually covered a region instead of pretending coverage was perfect. More on that →

Read my report first, if you'd rather.

Email me and I'll send it. Or start yours — it's one upload away.