Episode 18 now available!

Ep 18 - Justin Byers, Founder and CEO, Axio BioPharma

​Fixing the Data Problem Slowing Down Life-Saving Drugs​

Justin Byers had to tell a founder, after 18 months and nearly $2 million, that their drug couldn't be manufactured at scale. The information was there the whole time. It was just trapped in the wrong systems in the wrong formats. That moment became Axio BioPharma.

Justin is a scientist by training who spent years at Illumina and Fujifilm watching drug programs get delayed by fragmented data, not bad science. Physical lab notebooks, electronic lab notebooks, separate computer systems for each piece of equipment. Nobody knew what data they had or where it lived.

Axio is building the data pipelines that get manufacturing information from early research into the hands of contract manufacturers in a clean, AI-ready state. He set up his lab at Forward BIOLABS in two weeks and had his first client two weeks after that.

We cover why AI tools are only as good as the data feeding them, how he found his co-founder through Y Combinator's founder matching program, Madison's deep biotech talent pool and its early-stage capital gap, and why he's now building Midwest BioCapital, a fund 100% focused on pre-seed and seed stage biotech startups in the Midwest.

All that and more inside this episode

→ Listen to the Interview​

Topics discussed

• The data pipeline problem slowing down drug development and how Axio is solving it
• Why AI in pharma needs structured data before it needs more models
• The pivot away from building a large contract manufacturing org and their own AI models
• How Justin found his co-founder through Y Combinator's founder matching program
• Madison's deep life science talent pool and why early-stage capital is the missing piece
• Midwest BioCapital: a fund 100% focused on pre-seed and seed stage Midwest biotech
• Building an advisory team before you need it, and why good advisors push back
• The federated biopharma network vision connecting pharma sponsors to contract manufacturers
• Forward BIOLABS and the infrastructure that let Justin go from zero to first client in four weeks

→ Listen to the Interview​

Key learnings

The data problem is bigger than the science problem.

This was the core of the conversation. Justin spent years watching drug programs get delayed, not because of bad science, but because critical information was trapped in silos. Physical lab notebooks, electronic lab notebooks, separate computer systems for each piece of equipment. Nobody knew what data they had or where it lived.

The breaking point was telling a founder, after 18 months and nearly $2 million, that their drug could not be manufactured at scale. When they looked back to figure out why it took so long to discover the problem, the answer was straightforward: the information was there the whole time. It was just stuck in the wrong systems in the wrong formats. That moment pushed Justin to build Axio.

For anyone outside pharma, the takeaway is universal. Data fragmentation kills speed in every industry. When your critical information lives in five different places and nobody knows the full picture, you're making high-stakes decisions with incomplete context. Justin saw that pattern at the highest stakes possible, where the cost is measured in patient lives and years of delay.

AI is only as good as the data flowing into it.

Everyone wants to use AI in drug development right now. Justin's team considered building their own AI models before realizing the industry doesn't need more models. There are plenty, and more being built every day. What's missing is structured, high-quality data to make the models that already exist actually useful.

That's where Axio is focused. Building the data pipelines that get manufacturing information from early research into the hands of contract manufacturers in a clean, AI-ready state. Without that foundation, the AI tools don't work. With it, they become genuinely powerful.

This is a lesson that extends well beyond pharma. The companies that will get the most out of AI aren't necessarily the ones building models. They're the ones that have their data in order. If your information is scattered across notebooks, spreadsheets, and disconnected systems, no model is going to save you.

Speed comes from staying focused.

Axio originally planned to build a large contract manufacturing organization on par with companies like Lonza and Samsung Biologics. They also considered building their own AI models. They walked back both. The clinical manufacturing space already has strong players investing heavily. The AI model space is already crowded. What's missing is the early preclinical manufacturing infrastructure and the data pipelines connecting it all.

Staying focused on that specific gap is what allowed Justin to move fast. Lab set up at Forward BIOLABS in two weeks. First client two weeks after that. That kind of speed doesn't come from doing more. It comes from doing less, but doing the right thing.

For founders in any space: if you're trying to do everything at once, you're probably not doing any of it well. The pivot that narrows your focus is often the one that unlocks your speed.

Build your advisory team before you need it.

One of the first things Justin did after bringing on his co-founder was build an advisory team. Not after the first roadblock. Not after the first raise. Before any of that. His advisors, including Greg Black who helped start Gala Designs (which became Catalent Biologics) and Graham Burley who headed up several Catalent sites, helped him avoid spending years trying to raise hundreds of millions for a clinical manufacturing site the industry didn't need from him.

Justin was direct about what makes a good advisor: they can't be an echo chamber. If your advisors are telling you yes on everything and never challenging your ideas, you're going to find yourself in trouble. You need people who know your specific industry and who are willing to tell you when your idea isn't the best one. That pushback is what saved Justin from spinning his wheels and let him move to revenue in weeks instead of years.

His advice for finding the right advisors: look for people with deep domain expertise in your space, not just general business experience. And make sure they have the courage to push back. The advisors who tell you what you want to hear are the most dangerous ones.

Finding a co-founder is like a marriage. Don't rush it.

Justin met his co-founder Brian Staats through Y Combinator's founder matching program. They didn't rush into it. They spent months going back and forth virtually, then Brian flew from Seattle to Madison so they could meet in person. After about six months total, they both decided it was a good fit.

The complementary skill sets matter. Justin handles process development and commercial sales. Brian handles software engineering and bioinformatics. Brian was one of the early software engineers at CrowdStrike when they were still pre-revenue, which gave him firsthand experience building federated network effects from zero. That's directly applicable to what Axio is building in biopharma.

Justin recommends every founder approach the co-founder search the same way you'd approach a marriage. You're going to be working closely with this person for years. The relationship matters as much as the resume.

Madison has the talent but needs the capital.

Madison has one of the deepest life science talent pools in the country. Exact Sciences, Catalent, Arrowhead, PPD. Companies that either started here or grew substantially here. The universities produce strong scientific talent and established companies produce experienced operators. Justin said it usually surprises outsiders just how much biotech depth exists in the area.

What's missing is early-stage capital. There are established VCs in Madison, Chicago, and St. Louis, but very few focused on pre-seed and seed stage biotech. Justin saw this gap firsthand at Forward BIOLABS, where companies were spinning out of UW Madison with solid business cases and strong founding teams but nowhere to turn for early funding.

This is a theme I keep hearing across the podcast, not just in biotech. Wisconsin has the talent, the ideas, and increasingly the infrastructure. The capital gap at the earliest stages is what's holding back velocity. Justin isn't just talking about it. He's doing something about it.

Midwest BioCapital is filling a structural gap.

Justin is building a fund that is 100% focused on pre-seed and seed stage biotech startups in the Midwest. No off-thesis allocations. No coastal deals. Just early bets on Midwest founders who have strong science and strong teams but no access to the kind of early capital that gives them a real runway.

He's still bringing on general partners and building out the team, but the problem it's solving is clear and urgent. The fund came directly from what he observed at Forward BIOLABS: too many strong companies with nowhere to turn for that first check.

What's interesting is the parallel to his Axio work. Both are about filling gaps in infrastructure. Axio fills the data pipeline gap. Midwest BioCapital fills the capital gap. Justin sees them as complementary forces in the same ecosystem.

Network is the multiplier.

Justin came from the commercial sales side of the industry, which meant he arrived at the founding stage with a larger network than most technical founders. He credits that network with much of his early momentum, including finding advisors, landing clients, and raising capital.

His advice for founders starting with a smaller network is simple and actionable: ask every person you meet, even if they're not the right fit for you, to introduce you to two people who might be a better fit. Do that consistently and the compounding effect is significant. It's not a new concept, but Justin's emphasis on consistency is what makes it work. One introduction leads to two, which leads to four. Over months, that snowball builds a network that would have taken years through traditional channels.

The federated network is where this all leads.

The long-term vision for Axio goes beyond individual data pipelines. Justin wants to build an interconnected, federated network connecting pharma sponsors to their contract manufacturer of choice so information flows seamlessly from development to clinical manufacturing. Think of it like CrowdStrike's model applied to biopharma: when one participant in the network flags a bad raw material, that information gets pushed to every other participant so they can flag it too.

The near-term focus is on early proof of concept programs. But if the network scales, the implications are massive. Drug development timelines could be cut in half. Risk goes down. Costs go down. And the drugs that patients need reach them faster.

Upcoming episodes 👀

• Jon Eckhardt (UW Madison School of Business)
• Jessica Martin Eckerly (Forward BIOLABS)
• Nadiyah Johnson (Milky Way Tech Hub)
• Joey Friedli (SpecterSight / Formerly Trashpoint)

What is the Startup Wisconsin Podcast?

It's a new show where you can learn about Wisconsin's growing tech scene. Hear the stories of startups, founders, investors, and the incredibly generous people making it happen every single day.

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