Rethinking How We Build Biotech Companies

Borrowing From Tech To Build Product-Platform Biotech’s

Introduction

In the world of technology, there’s a well-known principle from Intel’s Andy Grove: every product should be ten times better than the one before it (a concept well outlined in his book High Output Management). That kind of exponential leap has powered decades of innovation in Silicon Valley. But what happens when we try to bring that mindset into biotech?

In theory, it sounds impossible. Biotech has never had the luxury of agile iteration. You can’t release a “version 1.0” of a therapy, gather feedback, and improve the code. Between regulatory hurdles, manufacturing complexity, and the time and cost of generating clinical data, biotech has traditionally been slow, expensive, and rigid.

But in today’s environment, we have to rethink the model. There are many pressures on the system. The obvious Financial Considerations but also the the knowledge Explosion Medicine all support the need for an iterative product centric model in biotech drug development.

Financial Pressures in Biotech

Biotech founders today are building under immense financial pressure—arguably more than at any time in the past decade. Consider just a few of the forces at play:

1. Higher interest rates have dampened risk appetite.
2. Crossover investors have pulled back, focusing on late-stage derisked assets.
3. IPO markets remain sluggish, with few viable exits.
4. M&A has slowed, especially for early-stage companies without human data.
5. Big pharma is more disciplined, demanding value-based data before partnering.
6. VCs are triaging their portfolios, allocating capital only to perceived winners.
7. Time to value is compressed—founders have fewer cycles to show traction.
8. Cost of capital is rising, forcing leaner and faster execution.
9. Dilution is painful, especially in down rounds or bridge financings.
10. The “platform” premium has collapsed, shifting focus to clinical products with clear differentiation.

Against this backdrop, the old biotech playbook—raise big, build broad, and hope for a premium—is broken. What works now is clear: demonstrate product potential early, cheaply, and repeatedly.

The Knowledge Explosion in Medicine

Medical knowledge is expanding at an unprecedented rate. In 1950, it was estimated that medical knowledge doubled every 50 years. By 1980, this had accelerated to every 7 years, and by 2010, every 3.5 years. Astonishingly, by 2020, the doubling time was projected to be just 73 days .

This rapid expansion means that during the traditional 10–15-year drug development cycle, medical knowledge could double multiple times. Consequently, therapies developed over such extended periods risk becoming outdated before they even reach the market.

Embracing a Product-Led, Iterative Model

That’s the model being tested at Myeloid Therapeutics.

The company’s MT-302 program marked the first-ever in vivo CAR technology using first-generation mRNA to enter human trials—providing critical proof-of-concept. Building on that, MT-303, which targets GPC3 in liver cancer, introduced a second-generation RNA capable of expressing for up to 12 days—an unprecedented duration for linear RNA. That same RNA was later retrofitted into MT-302 to create an enhanced version. Their latest candidate, MT-304, is designed to engage multiple cell types. None of these are standalone bets; each is a deliberate iteration that builds upon prior insight and data.

And the pace has been remarkable. MT-302 took 18–24 months to reach the clinic. MT-303 took just 8. The enhanced MT-302 was built on the original IND, and MT-304 is on track to continue this acceleration.

This progress reflects a technology-driven mindset—borrowing principles from software: rapid prototyping, focused experiments, and feedback loops—applied to the complexities of drug development. Critically, Myeloid has achieved this while adhering to the rigorous standards of global regulatory oversight, GMP manufacturing, and human safety.

Richard Farleigh describes this challenge as reducing the cost of discovery. In biotech this is the cost proving an idea in humans– not the cost of the preclinical validation, opening an IND, dosing the first patient, the cost of a platform, or a brand. In a world where capital is scarce and expectations are sky-high, this metric is more important than ever.

In biotech, investor sentiment often swings between favoring platforms and favoring products. Today, products clearly lead the way—but I would argue they always should. Platforms are valuable, but only to the extent that they generate real therapies: products that address unmet needs, deliver compelling human data, and earn their place in the next financing cycle. A platform earns its worth by proving it can produce meaningful outcomes—not by existing in theory.

The experiment at Myeloid is still running. But if they are right, this model—fast, iterative, product-focused biotech—could represent the next chapter in company building. Not by mimicking tech’s pace without acknowledging biotech’s complexity, but by taking its best lessons and applying them with discipline.

Because in this environment, the companies that survive won’t be the ones with the most potential—they’ll be the ones with the clearest path to proving it.

Conclusion

Biotech has long been viewed as slow, expensive, and resistant to iteration—but in today’s high-pressure financial and scientific landscape, that model is breaking. This post explores how Myeloid Therapeutics is applying a product-first, tech-inspired approach to biotech: moving fast, learning from each iteration, and proving value in human trials early and often. With capital tight and medical knowledge doubling faster than ever, the companies that thrive won’t be the ones with the biggest platforms—but the ones that can prove their ideas in people, quickly and clearly.