As AI reshapes productivity and investing, its next frontier is medicine and building custom cures. The rise of “one-patient medicine” could change both healthcare and finance as we know them.
The End of the Old Model
For decades, we trusted big pharmaceutical companies to deliver the cures of the future—blockbuster drugs, cutting-edge therapies, vaccines that changed history, and lives saved. But that model is breaking down. As development costs now exceed $2.6 billion per drug and incentives skew toward common conditions, millions of patients with rare diseases are left behind.
Artificial intelligence is beginning to fill that gap. Just as AI transformed software—automating tedious work and collapsing complexity—it’s now reshaping medicine. Algorithms are finding patterns in genomic data, proposing molecular targets, and even managing the logistical grind of therapy development for rare diseases.
This transformation is as financial as it is scientific. More people have rare diseases than cancer, and hyperpersonalized treatment pathways, made possible for the first time ever by AI, mean that we may be witnessing the rise of the fastest-growing, and least understood, new subsector of the global pharmaceutical industry.
AI tools that rewrote the rules for software development are now taking aim at biotech’s most expensive problems: drugs that cost billions to develop, take over a decade to reach market, and still fail most of the time— targeting the bottlenecks that have made treatment pathways prohibitively slow and costly.
A new generation of founders are translating that convergence into real-world treatment options. A few of the startups at the epicenter of this shift include Nome, XtalPi, and Benchling—each tackling a different layer of the AI-in-medicine revolution.
I recently spoke with Stevie Ringel, founder of Nome, about the growing impact of AI, and how it’s transforming healthcare access and costs—especially for families and individuals who need more than a “one-size-fits-all” treatment.
The Founder Who Refused to Wait for a Cure
When Ringel began losing his sight to a rare genetic condition, the future went dark. There were no clinical trials, no treatments, and no pharmaceutical companies willing to invest in one.
“I have been waiting for 16 years for a magical phone call that somebody has a clinical trial for my condition,” Ringel says. “It hasn’t happened.”
So, instead of waiting for a miracle treatment, he built something new. Nome, the company he founded, uses AI to map treatment options for rare diseases that traditional medicine ignores. Acting like a scientific project manager, Nome analyzes genomic data, surfaces viable therapies, and connects families with researchers and manufacturing partners.
“Above all else, action creates hope,” Ringel explains. “Now that AI has made expert-level knowledge more accessible than ever, I knew it was time to take matters into my own hands.”
Recently, the company announced a new funding round and a partnership with Genome Medical, a clinical genetics network that will help families move from diagnosis to therapeutic planning. The partnership may not make headlines, but it’s an early proof point that patient-led AI innovation is moving from research to the mainstream.
The Financial Shift Behind “N = 1” Medicine
For generations, drug development was driven by scale. If a disease didn’t affect millions, it wasn’t commercially viable. But new foundation models, multimodal bio-tooling, and AI-assisted hypothesis generation are dismantling that constraint.
What once took years—and hundreds of millions of dollars—can now happen in weeks. AI can model protein interactions, simulate drug binding, and triage thousands of therapeutic possibilities before a single experiment begins. According to McKinsey, AI adoption across industries more than doubled between 2017 and 2022, with life sciences positioned among the sectors poised to see the biggest impact from the technology.
The global AI-in-drug-discovery market is projected to reach $20.3 billion by 2030, according to Grand View Research. And just last month, the National Institutes of Health approved the first-ever gene therapy designed for a single child—a quiet milestone marking the dawn of “N = 1″ medicine, where treatments are tailored not to a population or even a subgroup, but to one patient’s unique genetic profile.”
Nome is among the first to make this future real, turning AI breakthroughs into personalized therapies that patients can actually get. The company provides families with a score from 0-100 and a confidence interval indicating whether a personalized therapy approach is worth pursuing—all at no cost initially.
“Ultimately, families want to know if moving ahead with personalized therapy is worth their hope,” Ringel says. “We take that responsibility seriously.”
Meanwhile, peers like XtalPi, backed by Sequoia China and Google Ventures, are using quantum physics and AI to accelerate molecular design for major pharmaceutical partners. Benchling provides the connective tissue—cloud-based tools that modernize data sharing and collaboration across biotech teams. Together, they illustrate how intelligence, not infrastructure, is becoming medicine’s most valuable resource.
From Blockbusters to Bespoke
Traditional biotech economics are unforgiving: develop one drug, sell it to millions, and hope for billions. Anyone with a rare disease? Not profitable enough to pursue.
AI changes that equation. By cutting discovery costs and compressing timelines, it makes room for smaller, more agile players. Companies like Nome are unbundling the pipeline. Rather than relying on a single corporate entity to shepherd a therapy from concept to clinic, they orchestrate a network—genomics labs, contract manufacturers, and AI systems working in parallel.
This doesn’t replace Big Pharma. It complements it. Just as startups once unbundled the corporate software stack, micro-biotechs are now unbundling the R&D stack. Instead of one-size-fits-all therapeutics, we’re entering an era of personalized orchestration—matching each patient’s genetic profile with precise, actionable options.
When I ask Ringel how Nome differs from other AI-driven drug discovery companies, he’s clear about the company’s unique positioning: “The most pervasive gap we see is that no other organizations are great at determining how an individual patient should proceed.”
Yet the shift brings new questions. Who owns a therapy generated by AI? How should insurers price a drug designed for one person? And what happens when computation, not chemistry, becomes the bottleneck?
Ringel believes regulatory clarity is essential. “We need leadership from Washington—both from the FDA on regulatory pathway guidance and from CMS on how these therapies should be priced and paid for by the system.”
These questions are already shaping how investors assess valuation, intellectual property, and go-to-market models across biotech’s next wave.
How AI Is Changing Biotech Investment
AI platforms are redirecting venture capital in ways that will ultimately affect healthcare costs. Investors who spent the last decade backing consumer software are now funding AI systems that can run lab experiments and design treatments—a fundamentally different proposition.
The investment strategy is splitting. Some are betting on broad platforms that can discover drugs across multiple diseases. Others are funding specialized tools for complex, high-stakes fields like rare-disease research, where even small efficiency gains translate to lives saved.
What makes Nome’s approach particularly interesting is who’s investing. Beyond traditional venture capital, the company is attracting families affected by rare diseases, philanthropic foundations, and healthcare-focused funds—investors who see the bigger picture. If you can figure out how to cure one ultra-rare condition affordably, you’ve essentially created a repeatable process for hundreds of others.
It’s a different kind of bet. It’s driven less by market size and more by proof of concept. And it could reshape how medical innovation gets funded.
The Bottom Line
Nome’s story isn’t just about one founder confronting blindness. It’s about a broader movement to democratize cure-building, and turning roadblocks into action.
As AI takes on the heavy lifting once reserved for pharma giants, we’re watching both a technological and moral inflection point unfold. Medicine is becoming a service, personalized at the atomic level. Investors should be watching. Patients should be hopeful.
When I ask Ringel about the role of empathy in this AI-driven space, his answer is refreshingly simple: “Empathy is the business. Technology enables us to provide it at scale.” If AI can automate creativity in business, perhaps it can automate compassion in science. Because the real breakthrough isn’t just in the science; it’s in who gets to use it.