This week marks my one-year anniversary at SwiftPharma! We’re a Belgian startup, which I joined right after coming back from the US. My experience in the US opened my eyes to entrepreneurship, and basically convinced me to make the jump from academia to industry. But I didn’t want a job at just any other big company, I wanted to join a small company with an ambitious mission. There are quite a few of those in Belgium (and I would say more and more these days!), but I also wanted to stay in the fields of computational biology and AI, which is where I think a lot of innovation and positive impact is yet to be made. Turns out that SwiftPharma just started hiring and I was lucky enough to get on board from the beginning.
So what does SwiftPharma do? As the title alludes to, the core of what SwiftPharma does is “building the machine that builds the machines”. Vague enough? Let’s have a closer look.
Some context on biopharma
If you think about medicine, you can roughly classify them into two big categories: small molecules and biologics. You can classify them in many other categories too, but this keeps it simple. Small molecules are, I would say, the traditional drugs that are chemically synthesized and contain well-defined structures, and are literally small molecules (they have a low molecular weight). Typical examples include painkillers like aspirin and ibuprofen, or antibiotics such as penicillin. On the other hand, biologics or biopharmaceuticals are more complex molecules that are derived from or inspired by living organisms or components of living organisms. This second category is gaining significantly in importance in recent years.
The market demand for biopharmaceutical products has been constantly increasing year by year. And in parallel, there is an increasing pressure to lower the prices of expensive medicines, to increase global access to such biological drugs. That’s where SwiftPharma comes in.
These biological drugs are often proteins. Proteins are tiny machines that naturally reside inside organisms and perform all kinds of important tasks. Just think about your own human body. Proteins are the small machines that keep you alive. They transport oxygen throughout your body, break down food into basic building blocks your body can use, they protect you against pathogens, and much more. And our body produces all of these machines itself. In this way, we can actually see our body as ‘a machine that builds the machines’. We’re talking about biological machines here.
SwiftPharma grows biological machines
That concept is key to what SwiftPharma is doing, except we don’t use human bodies as machines 🤷♂️. Instead, we use plants. Plants are biological machines themselves, and they produce proteins to keep them alive, just like humans. But using one of nature’s own tricks (which involves a human-friendly bacterium), we can use plants to make a wide variety of proteins that are of interest to humans.
SwiftPharma is growing the machines (plants) that build the machines (proteins) to support a sustainable and scalable production of the worlds proteins.
Why is this a great mission to pursue? Because humans need proteins for many different things, and we want to be able to produce them in a sustainable way, in a scalable way and in an affordable way.
Plants don’t need a lot to grow, and can use side streams and capture CO2, making it a sustainable alternative versus standard industry solutions. Plant production is also easily scalable because each plant is a unit that does the same thing. If we want more protein, we just grow more plants! And that scale ultimately also translates to a lower production cost, which is further increased by automation and process optimization. No costly bioreactors needed.
Computational biology and AI
So what am I doing at SwiftPharma? I am the computational biologist of the team.
Recent years have seen a lot of advances in terms of data availability, computing resources and innovation in computational biology and AI. The result is that today, we can increasingly do useful research & development on the computer, before moving on to the lab. So that’s what I’m doing. I’m modeling and optimizing proteins on the computer, developing tools to help the wet lab team and piloting computational workflows that can ultimately increase value down the line and reduce current bottlenecks of plant-based production.
And we’re betting that the trends in computational bio and AI will continue. SwiftPharma wants to stay ahead of the curve on that front and wants to build top-level computational expertise. So arguably, my most important job at SwiftPharma is to make the company future proof regarding computational biology and AI, given these assumptions of continued progress. And I definitely stand by these assumptions. Not only do we see general AI research continuing to make progress, but teams that apply AI to biology are also increasingly coming out with spectacular results. The fields are still developing, and many more mistakes to be made, but iteration per iteration, things do get better and better.
Onward!
Dimi