It is important to have a fundamental understanding of biology and chemistry, and ability to critically evaluate data, but once you have that, its more important to be able to find people with the right domain expertise and have productive interviews with them about data. If you are a neuroscience PhD you should not be evaluating a cancer assay or a GLP tox study on your own, you should read enough to have a productive interview with someone with more expertise, then go have that interview
You need a rigorous science background to start a company but that is not sufficient. Many projects are just not fundable. For non scientists, id recommend learning how the industry works and how value is created, because that complements the expertise of scientists who know the science but dont know the right clinical applications
Is that the need, though? Few SaaS CEOs truly understand all the background of computer science. They do understand the problem space, but they leave it to the experts in the organization to get into the details of applying computer science to the problem.
Is biology different, where the level of expertise needs to be at a more detailed level in order to lead an organization?
To found a company? How do you know where to start? If you are hiring PhDs to come up with the idea for you, how do you if their ideas are novel or worthwhile?
Not to disparage SaaS founders, but I think it's somewhat easier to look about and say "there is no app for sending texts via REST API" and do that, than it is to look at say "no one has found a way to selectively target cancer cells for CRISPR" and then go do that.
We are still at a point in Biotech where companies have to do fundamentally new things with their tech to succeed. If you were starting a company that applies CRISPR to X genetic disease, you might not need a Ph D. to start the company, because you can apply existing technology to solve that problem. But that begs the question: Why has no one else done it yet?
At the end of the day, you need a unique insight to start a large company. That means experience with either the problem space or the technology space is helpful. Not discouraging OP either, if you have a vision for what the future should look like, and can acquire talent/capital... anyone can start a massive company. So OP should try to acquire that vision.
But there's no doubting that some sort of counter-intuitive or hidden insight is necessary. Even if that insight is: "people think this is obvious and not worth doing, but it actually IS worth doing." RE: Zero to One.
I think we need to stop this useless debate as clearly one side has often no clue about the other. This behavior has led to massive failure in my career to successfully launch IVD devices or have a successfully bioinfo software for physicians - talking from experience here.
Success in biological research is driven by the scientist's ability to sort wheat from all this chaff, and it's acquired by gathering the data themselves hands-on in wet labs. A master biologist has learned how to navigate that space experimentally and analytically using techniques they've mastered just well enough to see over the noise.
As someone with degrees in both bio and CS and 15 years of work that crosses the boundary between them, I'm decidedly more in awe of those who have mastered biology.
I think that you and a lot of people in this thread don't understand the impossibility of understanding millions of lines of code. Do you really think "computer geeks" just hold them all in their heads, and then assume that since they can do that, it must not be difficult?
No, but I think a group of geeks could. However a group of biologists cannot explain a biological system in full. When I say a computer system can be understood in full, I mean that human knowledge encompasses the working and programming of the machine, not that one person could know every detail. This is not the case for biology, as there's plenty we don't know.
> Otherwise, you could just as well say that a biological system can be understood from the atoms on up, since quantum theory provides a complete understanding.
It really doesn't provide a complete understanding for biology anymore than it does for sociology. It's not possible for humans to reductively explain such fields in terms of physics. No one can even prove this is possible. But it's not a complete understanding for physics either, since there's Relativity and questions about quantum gravity and dark energy.
Not only is documentation pretty scarce these days, but good information on the interactions between pieces of software is much scarcer, due to the exponential number of ways that it can interact.
How do you find info on bio topics right now?
The trick is interpreting it and putting it into context. A paper will report the results of one specific experiment, and it’s very rarely exactly what you want. Understanding how a result will generalize to other conditions is tricky, even for experts: there are tons of weird feedback loops, unusual dynamics, and other traps for the unwary (plus badly designed experiments and the occasional legit Type I error). For example, doubling the amount of a substance almost never doubles its effect, and in some cases, the effects aren’t even monotonic: ~75% alcohol, for example, is a much better disinfectant than 50 or 100%.
With time—-and lots of paper-reading, you do eventually develop a sense for what factors might matter and how you could check.
But its rubbish.
Speed + onus behind learning > everything.
Also note the self-serving bias where Phd's swear:
"You need a phd"
If you want to have a decent shot at getting funding from biotech VCs, the team overall needs experience in biotech AND startups, and the less experience the founder has in biotech the more the team will require to compensate for the deficiency. And vice versa for business experience, a freshly minted PhD is going to need team members with significant biotech BD experience.
A PhD or MD counts towards experience in biotech. MS + years of industry experience also counts, as would BS + many years of industry experience.
A PhD is nice because because it demonstrates deep experience in a narrow field plus an understanding of context. The context part is key. Autodidacts tend to miss out on the context, and their learned knowledge tends to be more fragile as a result, so there is a slight bias towards advanced degrees.
Insufficient experience is a hard no for biotech. Nobody wants to see another Theranos, and notably biotech VCs didn’t put any money into Theranos. We’d like to keep it that way.
> "A PhD is nice because because it demonstrates ..."
An employees willingness + investment to singularly do just one thing for the rest of their life.
It works as really good signaling for a CEO / hiring manager to assess someone as a really consistent employee.
Theranos had an excellent market fit—-people hate having blood drawn—-but the technology did not work and fundamentally could not work. The whole point of being a subject matter expert is to learn about things like that.
It’s true that there are other routes to becoming an expert in something (and proving it). A masters and a stint at a well-known company certainly works for many people; bootstrapping your own company might be an option too, but you’d need to be very successful to establish your bonafides. The advantage of a PhD is that it’s a fairly well-known quantity.
I studied Genetics and CS. What you can do instead is reach out to the PhDs and gather information from them to start getting a general sense of the direction.
This is easy some schools allow you to sit in on lectures / come to events. Most PhDs are usually off working independently though. Make friends with the competent PhDs gather info. Hack the system you don’t need a PhD you can hire one later.
This is all assuming you have the raw talent of product and can lead well, and can convince people exceptionally well, otherwise disregard.
God knows they'll work for 3rd-world labor rates.
The question is if the methods are complex. AFAIK computational biology involves statistics, statistics and statistics. The systems themselves are incredibly complex and interconnected , but the abstraction levels of the math involved are not incredibly high.
In all seriousness, you are going to need a PhD if you want to truly understand all of the background of the field. Human biology/biochemistry is just about the most complex thing humans have ever studied. It would surely be easier to just find people with the requisite skill sets.
Even if you just want to start a company, I feel that it would be really hard to pick out a scientific direction/what your company is going to do, without a rigorous scientific background