Baby is healed with first personalized gene-editing treatment

This is incredible work. Its jaw dropping to learn that something like this is possible at all. Sometimes I wish I could work for a company whose products make a meaningful positive contribution to the work.

Do companies like this have a need for SWEs? Are there opportunities for a backend SWE without any background in hardware or biology?

> Do companies like this have a need for SWEs? Are there opportunities for a backend SWE without any background in hardware or biology?

Of course they do. Biology and medical research can't get enough software people. But they're not as well funded as advertising or spying companies, for example, so you might have to take a significant pay cut.

I wouldn't pigeon hole yourself as a "backend engineer". Why do people do that? Software is software. The bit that matters is the core model and algorithms etc. Whether it's exposed as a web server, a CLI or just a library is a peripheral detail.

It's totally possible for a decent software engineer to learn just enough biology to get by. The limiting factor might be your interest, though. But if you have that then go for it. Get a book on genomics right now.

Yes. Aldevron and IDT are two companies (owned by danaher) that collaborated to make this happen. They have multiple authors listed in the NEJM article.

https://jobs.danaher.com/global/en/search-results?keywords=S...

Mark Behlke's group at IDT is the force behind a LOT of the development of CRISPR, but they are relatively unknown

I run a small software team at a small biotech working on diseases with small patient populations, and the answer is yes x 1000. The issue is that in drug companies, software isn't the product, so SWEs will never make as much money nor be as much of a priority as in tech-proper.

There are two categories of software we need help with:

1. Salesforce for science. We don't have big data in terms of volume; we have big data in terms of heterogeneity. Tons of small data sets that need context to be interpreted, including measuring uncertainty. This software, often called an eLN or LIMS, is offered by expensive vendors who each have their custom, locked-in implementations. Every organization needs customization on top of this that can be developed and change with the changing direction of the bench scientists.

2. Informatics tools. Much of the heavier computational tools (bioinformatics, molecular dynamics, stats) were developed by academic labs, who don't have the training or incentives to create sustainable software. Alternatively, they are made by vendors who write software on short-term contracts, so they don't have expertise in house. Our mass spec vendor told us to put their analysis servers on our Citrix so employees could access it. Citrix! If you can convince those vendor to hire you and rewrite their software, please do.

Despite cool tools like alphafold making headlines, the software needs in drug development are more mundane. We need people who are excited to sit down with bench scientists and help them figure out how very normal tools can be applied to their work.