During my journey in graduate school and my involvement in translational biomedical research, I've had numerous discussions with my younger brother, a Stanford Computer Science graduate of 2019, who delved into the realm of tech startups with his first job at a series-A Sequoia backed ridesharing platform startup. These conversations sparked intriguing observations regarding the stark differences between the tech and biotech industries when it comes to startup frameworks and strategies.
Many of the common startup frameworks for tech companies do not apply as well to biotech. I’ve gone through the most common frameworks below, and how they differ for biotech companies.
I’m defining a tech startup here as a company whose product is largely based off of code. I am not including in my arbitrary categorization ‘deep tech’ (e.g., autonomous trucks, satellite startups, etc), which often face similar challenges as biotech companies.
Biotech here is a startup developing a drug.
These are generalizations, and many exceptions exist.
RISKS AND PRODUCT MARKET FIT (PMF)
TECH: Significant market and execution risks
BIOTECH: Minimal market risk, a lot of technical risk
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.
TECH: Rolling derisking, early signs of product-market fit
BIOTECH: Derisking comes in bursts over years (biological milestones), early signals less reliable
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).
TECH: Iterate to product-market-fit
BIOTECH: Product (drug) finalized years before on market
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.
FOUNDER MARKET FIT (FMF)
TECH: Founders often bring insight around a market
BIOTECH: Founders often bring insight around key biology
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).
TECH: Founders often younger, ‘youth wunderkinds’ widely accepted
BIOTECH: Founders often older due to scientific training or are a professional CEO, rarer to have very young founders
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.
INTELLECTUAL PROPERTY AND PATENTS
TECH: Fast-followers and copycats a significant risk
BIOTECH: Strong patent protection
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.
ON SCALING
TECH: Often little to no regulation
BIOTECH: Significant regulation
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.
TECH: Time-to-market usually determined by speed of team
BIOTECH: Time-to-market restricted and dictated by regulatory requirements
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.
TECH: Milestones center around selling the product, revenue, and other customer-centric metrics
BIOTECH: Milestones center around biological de-risking
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.
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