double majoring

i am my school's first dual-major in engineering and health sciences. specifically, i'm studying a combination of chemical engineering and biochemistry (for short I usually just tell people that i'm a biomedical engineer haha). however, as someone who works in software, specifically ai drug discovery, with no actual educational background in the subject matter, i'm often met with many questions.

how i got here

the software side of my life came from nowhere official. after learning to code in first year, i taught myself the fundamentals of machine learning, and worked my way into ai drug discovery through self-directed projects and an internship rather than through any credential. i started university in general engineering, without having decided on a discipline yet. it was only after that first year, once i'd already been doing ai work on the side, that i committed to chemical engineering, and added biochemistry as a second major on top of it. this is usually the first thing that confuses people: if i can already do the software part, why go build a chemical engineering and biochemistry background instead of just studying more software?

why not just formalize the software side

the gap in my knowledge was never really the software. a new library or a new architecture is something i can pick up on my own; i've been doing exactly that for a while now. what i can't pick up on my own is the actual science of how a molecule becomes a drug: the reaction engineering, the separations, the process constraints that determine whether something that works beautifully in a model or in a beaker can ever be manufactured at scale. that's chemical engineering's territory, not computer science's, and it's the part of drug discovery that a lot of 'ai for biology' work conveniently ignores. a model can predict a promising compound all day long; it means nothing if that compound can't actually be made and scaled economically. i wanted the domain expertise, not more of the tooling i already had.

why add biochemistry on top of it

chemical engineering alone gets you the manufacturing half of the story: whether a compound can actually be made and scaled once you have it. but it doesn't teach you much about why that compound does what it does at a molecular level in the first place, and that's exactly the half biochemistry covers. i wasn't willing to be the engineer who can scale a molecule but can't speak to the biology behind why it works. most people trained in one of these disciplines don't have real fluency in the other, which is exactly why a purely computational researcher predicting drug candidates and a process engineer trying to scale them up so often talk past each other. i wanted to be able to reason about a candidate compound end to end, not just the manufacturing half.

that's really the whole point of the combination. generation is the software and ml side: proposing what the candidate compound should even be. understanding is biochemistry: figuring out why that molecule behaves the way it does. scale is chemical engineering: whether it can actually be made and manufactured once you have it. with all three of these layers, i get a full understanding of everything, from a compound's conception to it becoming an actual drug, instead of being fluent in one piece and dependent on someone else for the rest.

where this is actually going

i don't have the next ten years mapped out, and i'm not in a hurry to force that. there's real value in being someone who can sit at the intersection of 'this can be discovered' and 'this can be made,' whether that ends up being in industry, in research, or somewhere i haven't considered yet. the dual major isn't a bet on one specific outcome. it's me making sure i'm not locked out of any of them.