The Great Brain Bet: How Human-derived mini-brains and AI could upend big pharma

Choosing powers in early stage TechBio

Picture by Jonathan Cooper
Breaking through the old model.

Intro

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This week, we continue to explore how to build moats and what this means for early stage TechBio companies.

In his 2016 book, “7 Powers: The Foundations of Business Strategy”, Hamilton Helmer looked at companies like Netflix and Pixar and developed a toolkit to create Power and build moats.

Last week, I talked about founder-market misfit. This week, I’ll answer the question of how to choose your powers.

Let’s get it on.

The 7 Powers in Short

1. Scale Economies — Unit costs decline as production volume increases due to fixed cost spreading and operational efficiencies. Barriers rise when competitors can’t match your volume economics.

2. Network Economies — Today, we call this ‘network effects’. Product value increases as more users join the network. Each additional user makes the product more valuable for all. See The Network Effects Bible for a detailed treatment of the different kinds of network effects.

3. Counter-Positioning — A newcomer adopts a superior business model that established players can’t copy without damaging their existing business. Incumbents face a “damned if you do, damned if you don’t” dilemma.

4. Switching Costs — Customers face high financial, time, or risk costs when changing suppliers, keeping them loyal even when alternatives exist.

5. Branding — Customers attribute higher value based on reputation and trust, not just product features.

6. Cornered Resource — Exclusive access to a critical asset (data, talent, IP, relationships, raw materials) that others can’t easily obtain.

7. Process Power —Organizational capabilities and methods that enable superior operations and are difficult for competitors to replicate, often built through years of learning and refinement.

Choosing the Right Power

Helmer breaks company-building into three stages: Origination, Takeoff, and Stability.

So when’s the right time to build a moat — and which kind should you choose?

The answer depends on where you are in your company’s life cycle.

Most founders instinctively point to the Origination stage, and they’re right. That’s when the window is open — before your habits harden, before the market defines you.

At this early stage, a tech startup really has only two viable paths to defensibility:

• Cornered Resources — something uniquely yours that others can’t easily access: IP, team, molecule, or mathematical model.

• Counter-Positioning — a business model incumbents can’t copy without hurting themselves.

It’s far too soon for Scale Economies or Network Effects — you don’t yet have the users or volume. And Branding or Process Power take years (and a lot of capital) to build.

In the beginning, your moat has to come from what only you can do — or what your competitors can’t afford to.

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Another way to think about this comes from the Theory of Constraints (TOC). TOC argues that every complex system has only one constraint — two at most — that determines its performance. Optimizing anything else is a waste of effort.

Before Eli Goldratt introduced TOC, production planners relied on critical path analysis. The problem with that approach is that it assumes perfection: if anything goes wrong along the path, the entire system stalls. TOC, by contrast, says: find the one bottleneck that limits throughput, and optimize around it. Mathematically, you can’t do better.

That same logic applies to building Power. In the early days, you can’t optimize for everything — you have to identify the single constraint that defines your leverage, and build around it.

Building the right moat at the right time can make or break your TechBio company. If you’re wrestling with these strategic decisions, I’d love to help. I work with early-stage founders to identify their unique constraints and build defensible positions before the window closes.

👉 Book a strategy session or reply to this email to share your current challenge.

Intel

I worked at Intel in the 1980s and 1990s. Intel was founded in 1968, and by 1985 it had already achieved Scale Economies in chip design and manufacturing. The company lived by Intel Culture — common values for an aggressive pursuit of operational excellence that was Intel standard.

More importantly, under Andy Grove’s leadership, Intel pivoted the entire company toward microprocessors. With IBM’s design win for the 8088, Intel secured a pole position in computing that lasted nearly 30 years — from the 1980s through the early 2010s.

So what was Intel’s secret?

Intel had its own early Cornered Resource — the unique combination of Bob Noyce, Gordon Moore, and Andy Grove. As investor Arthur Rock said, Intel needed all three, in that order. Each brought something the others didn’t: Noyce’s vision and willingness to bet on the microprocessor; Moore’s scientific depth that solved early chip-production challenges; and Grove’s relentless focus on flawless execution. It’s hard to imagine Intel’s rise without that trio — a rare blend of complementary genius that’s almost impossible to assemble in a young company.

You see this pattern elsewhere too. In pharma, breakthrough drug patents often serve as Cornered Resources — the foundation for massive value creation across the industry.

But often, people are the Cornered Resource.

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Itay and Beyond

One of my early podcast guests, Itay and Beyond, is a Jerusalem-based TechBio company building brains on a chip — a platform that models neural networks in living tissue.

Their unique platform integrates functional measurements from brain organoids with advanced AI analysis to estimate the efficacy of drugs for neurological and psychiatric disorders.

Itay and Beyond began with a Counter-Positioning bet — replacing animal models altogether.

In the realm of neurological and psychiatric disorders, traditional drug development methods fail. Animal models, particularly mice, often do not predict human outcomes accurately. 95% of drugs developed on mice fail in human clinical trials. Only 5 new drugs were approved by FDA for neurological and psychiatric disorders in the last 20 years. And this is not that people have not tried - there is < 1% success rate in translating preclinical studies to clinical trials.

If Intel’s early Cornered Resource was a trio of founders, Itay and Beyond’s is a pair: Nisim Peretz, co-founder and CEO, and Nir Waiskopf, VP R&D.

Nisim comes from the world of applied science and entrepreneurship. He’s pragmatic, grounded, and deeply attuned to where the next breakthrough will meet an actual market. Nir is the archetypal deep scientist — the kind of R&D leader who doesn’t chase trends but invents the underlying methods others later follow.

Together, they represent a rare combination: vision and precision, ambition and discipline. Their Cornered Resource isn’t a single patent, assay, or chip design — it’s the fusion of leadership and technical depth that drives the company’s entire trajectory.

In the same way that Noyce, Moore, and Grove gave Intel a 30-year leadership position in microprocessors, Nisim and Nir give Itay and Beyond something equally defensible: a living, thinking system that learns faster than its competitors because its leadership does too.

Outro

At the beginning, Power often looks like people.

Before it becomes a process, a product, or a brand, it’s embodied in the founders — their judgment, chemistry, and capacity to see around corners. Over time, those qualities harden into systems and culture that others can imitate but never fully replicate. That’s why the earliest constraint in any company is almost always human — and why the rare alignment of vision and execution, like Intel’s or Itay and Beyond’s, is the most durable moat of all.

This Week on Life Sciences Today

I hosted Tim O’Connell, Founder and CEO of Emtelligent this week.

Speaking of Power in practice — this week’s Life Sciences Today guest, Tim O’Connell, shows what it looks like when a company turns years of domain depth into a scalable moat.

Emtelligent stands out in the healthcare AI space by delivering production-ready solutions that are purpose-built exclusively for medical data, achieving an impressive 99% benchmark accuracy across over 5 billion processed clinical notes. Unlike generic NLP tools that struggle with medical terminology, their platform is deeply rooted in medical ontologies and leverages cutting-edge deep learning to extract nuanced clinical insights from patient experiences, family histories, medication relationships, and genetic information. With proven scale across 10+ therapeutic areas and an extensible architecture that adapts to diverse use cases, Emtelligent transforms unstructured clinical text into structured, actionable data that delivers unmatched operational efficiency for payers, pharmaceutical companies, health systems, and health tech platforms.

🎧 Listen: Clean and structured data from medical records

About Me

I’m a 5X founder who learned hard lessons the hard way.
Today, I help early-stage TechBio companies stay focused, hit ship dates, and sustain solid teams.

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