(PC: IStock)

The Builder Era of Biology

Life science degrees are like CS degrees in the '70s

Michael Trịnh


One of the most common existential crises of incoming life sciences students can be summed up in one big question:

Is this degree useless if I don’t get into medical school?

Now if you have a genuine passion for working with patients and practicing medicine- go for it! COVID-19 has shown that the people we glorify in our time won’t just be our war heroes, but also should be the heroes who work in our medical front lines. Your GPA and application need to be competitive: keep yourself healthy, crush it.

If you want to pursue your curiosity for research in life sciences and go into academia- go for it! We will always need people like you who are uncovering the key insights that act as the bedrock for building anything new. Without the initial research, there’s nothing really to build off of in this field. But even if you plan to pursue academia, this article is for you.

For the large group of us who aren’t really passionate about working with patients or practicing medicine, and are unsure of graduate school: there lies the existential question. Are your tuition and all those hours spent learning about molecular cloning worthless if you don’t pursue a PhD or MD?

The short answer: no it’s not useless, the future is in biology.

A paradigm with vintage CS degrees

If you asked around a university campus in 1970 whether computer science was a “useful degree”, it’s really unlikely you would get an answer that reflects reality today.

Computer science and software engineering programs are now among the most competitive programs for incoming undergraduates. Working at Google and Facebook is now applauded like landing an investment banker job at Goldman Sachs would have been back in the 70s.

This is all because computational power was, and still is, growing exponentially as transistors got smaller in size. This allowed for more powerful hardware. Faster hardware allowed people to build and test more complex software. Fast forward since 1970 and now here we are.

Moore’s Law: The number of transistors we can fit in an integrated circuit has been doubling every ~2 years

The stigma of life science education being useful only for prospect academics or doctors is like the stigma computer science had back in the 70s when its potential wasn’t understood well. Before PCs and smartphones, relatively primitive computers were brought on trucks to big institutions.

We’ve come a long way from those days because the exponential increase in computational power defined the rise of tech as we know it. It turns out that we’re beginning to see the biological cousin of Moore’s law.

The cost of DNA Sequencing (reading DNA nucleotides) and synthesis (assembling DNA) is falling quickly. Just like how it’s hard to build a new app without code, it’s hard to perform research or do build much with biology without reading and assembling life’s DNA code.

The cost of sequencing and synthesizing DNA are falling drastically (PC: Rob Carlson)

Faster computational speeds allowed eager developers to build more ambitious software. More ease and accessibility for research involving DNA is the biological version of boosting our computational power.

Just like with computers, there are a ton of problems Biology can help solve.

Life Sci = information leverage in an era of Biotech

The future is in biology sounds like a bold claim for me to make. Despite the stigma, I’ll let the actions of multibillion-dollar VC firms (ex. a16z, Lux) who started out in software now speak for themselves. We also have awesome companies working on really unique problems like Gingko Bioworks, Bolt Threads, Tango Therapeutics, Octant, Cyclica, and tons more.

Venture capital, startups, pitching, tinkering, and design teams are the new normal for biotech.

3D printing DNA sequences and entire cell lines, and we’re just beginning. (PC: Liou, 2016)

More engineering and CS people are getting into biology

Despite the existential question of my fellow life sci majors, curious friends of mine in computer science and engineering programs keep asking me:

What is an interesting problem in biology that I could help solve using (insert their skill here)?

That’s a real different tone from asking whether your degree useless without an MD or PhD.

The reason my CS/Eng/Business friends gave for being curious, albeit anecdotal, was that they’re vaguely aware that there are unsolved questions in biology. Whether we’re talking about discovering new insights in a specific tumor, aggregating tons of chemical data to learn how to better design or repurpose drugs, or genetically engineering e.coli to produce insulin…

Biology is a maze with tons of unanswered questions and challenges. Solving these hard problems will lead to incredible human impact in terms of new therapies, products, procedures, etc. It then shouldn’t be a surprise that we’re seeing an influx of engineers and business people joining forces with seasoned researchers and academics to help tackle said problems.

Is all this influx of people and ideas overwhelming? Yes.

Is this a unique opportunity for the life sciences? Absolutely!

Understanding Biology = opportunity to work at an intersection

Whether you start in a “builder” culture (ie. Engineering, CS) or in a more traditional science program (ie. Life Sciences), you need to understand the science at hand before jumping into solutions. Many researchers that I’ve spoken with have talked about their pet peeves with bioengineering projects where the people involved don’t understand the science well. They all-too-often ended up imposing their solutions on a complicated biological problem that they didn’t fully understand.

The right breadth of understanding in biology/chemistry should allow you to think critically on new ideas and propose your own ideas that obey the fundamental rules which biological or chemical systems play by. We need teams of biological problem solvers to understand biological problems.

For a student coming from a life science background, this biology or chemistry understanding is your area of unique knowledge. When you stack this up with an additional skill like computer programming or design, you (or your team) have an opportunity to build or invest in something new. One of my favorite examples is an upcoming startup Biorender that got started by a life science graduate who had a passion for design.

Curious? Learn, collaborate, work on cool problems

So if you want to get involved in helping build this future, then where do you start?

There are lots of organizations (ex. IGEM, CSBERG) that enable people from different backgrounds to explore bioengineering/synthetic biology more in-depth and hands-on. Applying to labs that work on an area you’re interested in, and starting your own projects is one of the best next steps you can take.

An overview of topics covered by CSBERG in their YouTube synbio course

Coming from a life science background and want to build? Learn a “building” skill that you find interesting: coding, visual art/design, Arduino, 3D printing, etc. You can also team up with someone who already has expertise in some of these skills. Having some sort of unique building skills helps make you a more valuable asset to any labs you’re trying to join.

Coming from a comp-sci/engineering/business background and want to build? Learn the basics of biology: what is: a gene, the central dogma, basic cell biology. This will let you team with someone who has a life science background while being comfortable with the fundamentals and their jargon.

I recommend finding people to look up to who you can see parts of your future self in. As cliche as it sounds, most people who push the envelope in some way have their heroes. Some of mine include George Chruch, Wendel Lim, Richard Feynman, and David Liu.

Some big biotech questions we have yet to answer

Here is my non-exhaustive list of huge questions to tackle in biotech for my CS, Engineering, business, and hopefully after this article, Life Science friends to check out:

  • How do we further reduce the cost of DNA Synthesis?
  • How do we consistently stay steps ahead of anti-drug resistance? Can computational methods like evolutionary algorithms help us here?
  • How do we wrap our heads around protein structures and engineer our own protein designs that work?
  • How do we create incentive structures for big and small pharma companies to sell drugs to at-risk, lower-income patient populations?
  • How do we design new biological circuits and incorporate more complicated decision-making logic into these systems?
  • How do we design immunotherapies to better tackle the various tumor microenvironments we see across different tumor types?
  • How do we make cellular agriculture and manufacturing even more economically scalable and feasible?
  • How do we standardize cloud (automated) wet lab protocols in a way that’s industry standard?

These questions won’t answer themselves, other people will.

If you find biology or chemistry interesting but don’t plan on pursuing medical school or if you are completely unsure of whether or not you want to commit to graduate school…

It may be you developing this future in biology, so what will you build?

Melba Roy Mouton, an early NASA computer scientist (1960)

Side note: I fully understand that comparing engineering and science disciplines can get messy as one is building focused while the other is usually focused on revealing insight through empirical data or reviewing the literature. This article is intended to guide more cross-disciplinary action in biotechnology, and hopefully, spark new builds from younger students!



Michael Trịnh

Undergraduate builder & researcher @UofT in the crossroads of bioinformatics, immunology, and genome engineering.