Applying tech frameworks to biotech: key differences

In tech, the company often uses a standard software stack and applies it in a novel way (a new product). The question is usually not ‘can this thing be built’, but ‘does anyone want this thing we made’?

In biotech, this is flipped. The market (a disease) is well established, but the ability to develop a product (a drug) that addresses this market is the core risk.

In tech, you want the ‘up and to the right’ chart, showing exponential increase of some core metric of the company. Adoption, revenue, and other metrics derisk the company and give early signs of PMF. Early signs can be highly predictive of the company’s eventual success.

In biotech, derisking the company is predominantly tied to specific biological milestones. These come in bursts, with long periods of waiting in-between. Additionally, early milestones (such as the drug working in mice) aren’t 1-to-1 predictive of eventual success (the drug working in people).

In tech, the product is constant iterates and improves from customer feedback to find the exact product that people want.

In biotech, due to the extensive regulation, the final product (the drug) is finalized years before it first goes into people. If the drug doesn’t work in people, there is no iterating. If you want to modify the product, you need to restart the entire process over again.

In tech, a prototypical founder often worked at the incumbent company or realized a market opportunity by being that market themself. The insight around the market opportunity itself is a core value of the company.

In biotech, the insight of the founder is around a new or better way to develop a drug for the disease, or a discovery that was made in the laboratory (and the relevant patents around it).

In tech, the 18-year-old drop-out is lauded and mystified. If anything, older founders may be subconsciously discriminated against in favor for younger founders.

In biotech, the prototypical founder is older, often a career CEO or exec coming out of a Big Pharma company. At minimum, the founders almost always have significant scientific training - a PhD can take 6-8 years, and post-docs 2-3 years each. It is less common to see founders in their 20s and you almost never see ‘youth wunderkinds’. This is in part due to the conservatism of the industry and in part because extensive scientific training is generally necessary to have enough biological insight to correctly identify an opportunity.

In tech, some of the most successful companies created or defined their market - a classic example being ride sharing. Once a new market is validated, other companies/copycats/fast-followers flow in.

In biotech, the market opportunities are diseases. New markets can somewhat be created (e.g., nootropics, elective medicines, Viagra) but generally speaking the markets are well known.

In tech, investors often bet on a specific horse with the hope that the horse will win the race (and all the earnings). Bifurcated markets can be especially dangerous as companies compete on pricing and ‘race to the bottom’.

In biotech, the markets are so large, and the unmet need so high, that there can and often are many winners in one market (disease). The classic example here are statins, which in 2020 had over $1 trillion in sales across seven market approved statins, with the best-selling Lipitor having peak sales of $12B in the mid-2000s.

Focus is crucial for any startup. However, in biotech the most successful and valuable companies often take a portfolio approach to product development - developing multiple products simultaneously. In tech, companies generally focus around one product or core offering, only differentiating once they have earned the right to do so by finding PMF with their first product.

A significant reason for this is to derisk the company against biological randomness. Instead, focus in a biotech company is usually around a core competency - e.g., a method of discovering drugs, or a way of delivering the drug - and then diversified within this core competency. For example, gene therapy company Spark Therapeutics had a core competency of AAV-based gene therapy (a virus loaded with DNA to treat a genetic disease) but leverages this competency simultaneously across multiple diseases.

In tech, not having someone technical on the founding team is a classic ‘no no’. You generally should have the ability to build (and therefore rapidly iterate on and improve) your core product within the team.

In biotech, it is common and often preferred to use contract research organizations (CROs) for much of your experimental work. Some experiments can only be done by specialized CROs, and they often have advantages from scale that a startup cannot hope to replicate. Building and staffing a laboratory, including the multiple six-figure machines necessary, is impracticable and unnecessary for most companies.

Virtual biotechs - companies with distributed leadership and all research outsourced to CROs - have been popular long before it became the tech zeitgeist.

In tech, being the first/best product to a new market is so important because once you validate a market’s need for a specific product, it is easy for others to copy and chip at your market share. This is especially common in traditional D2C brands, for example the many bed-in-a-box companies.

In biotech, patents are king. If you hold the key patent it is impossible for your drug to be copied. Once patents expire, however, there is a whole industry (generics) around copying drugs and selling them cheaper than the branded product. Because of the hundreds of millions it takes to develop a drug, it is almost impossible to commercialize a drug that is not able to be protected by patents, regardless of its efficacy.

Biotech companies’ biggest line item is undoubtedly R&D spend - funding to do research experiments necessary to find and develop their drug. This is despite the average salary in biotech also often being higher than tech’s.

In tech, you can often show proof-of-concept or even begin selling your product with a small team and pre-seed capital.

Biotech Seeds can often look like tech Series As in magnitude. On the East Coast, the first rounds in biotech companies are more than often in the $10s of millions. This is because of the millions needed to hit biological milestones to push the company forward (and therefore qualify for the next stage of financing).

Tech valuations usually optimize for selling 10% - 25% of the company in any one financing.

In biotech, valuations are historically significantly lower, with many East Coast deals selling 50%+ of the company in one financing. Such huge dilution is less common in West Coast biotech financings, but it is more common sell 33%+ of the company in one financing. Biotech founders also often have less negotiating power here because they have to raise large amounts to bring the company to the next stage.

While the company may be far from profitable, tech companies almost always have significant revenue at exit (IPO or acquisition).

In biotech, companies almost never have revenue at exit. Instead, the value of the company is driven by the increasing probability that their drug will work (and therefore decreasing biological risk). The company is often sold or partnered years before the drug is commercialized.

In tech, there is a self-selecting group that aspire to work in or on a startup, and are primed to take the high equity with lower salary in the hope that they pick the company that will become a unicorn and make them rich, too. They are often younger and therefore less likely to have a family depending on them.

In biotech, the core team is more experienced. They will likely have developed drugs in Big Pharma, have a family, and require a larger salary & some sense of security if they are to join a startup. Senior talent is necessary as many parts of drug development can’t be learned from a book - it is closer to an apprenticeship model.

In tech, there are millions of engineers and other talent pools primed on startups, and more resources on building tech companies than there are hours in the day to read them. Tens of thousands apply to Y Combinator alone.

In biotech, startup culture is less pervasive. Startup culture is the opposite of academic culture, which is where many potential biotech founders spend years of their lives. Academia is generally hierarchical, slow, conservative, and sequential - it does not encourage the traits that make a good founder, making the leap into company building even harder.

Biotech talent can be incredibly specialized and therefore sparse. Fields are narrow and somewhat isolated - if you, for example, need to hire a research associate with experience in mouse models of a specific mitochondrial disease, there may be only be a couple of labs in the US which produce students with this expertise. Pharma commonly trains people up within a company, but for a startup this can cost precious capital and time.

While it depends on the specific area the company is building in, generally speaking tech companies do not have to grapple with significant regulatory barriers before going to market.

In biotech, everything is done with regulation in mind. From designing experiments to first-in-human to commercializing, the entire process is overseen and largely dictated by the FDA. The FDA gives the final green light on whether your product will eventually be commercialized and how long that will take.

The regulatory requirements to bring a new drug to market are significant. You have to complete a large pre-clinical package of data delineating your drug’s safety, potential efficacy, manufacturing, and clinical plan before you can go into people (1-3 years). You then have to complete multiple clinical studies across three phases to demonstrate the safety and efficacy of your drug in people (5-8 years). Most likely, the company will exit years before this process is complete. While speed can shave months to years off of these timelines, it is not possible to simply start selling your product.

In tech, the value of the company is driven by the increasing rate of customer adoption and retention, revenue, and similar quantifiable, customer-centric metrics.

In biotech, the value of the company increases as the core biological risk around the drug is lowered. Again, it is highly unlikely that the company will have revenue before it exits, and therefore the increasing value of a biotech company is tied to the increasing likelihood that they have found a drug that works.