We teach a software engineering class at Stanford to help scientists do better science. Online courses coming soon.
We deliver workshops to biotech startups through incubators and biotech-focused funds.
There's a growing need in science for better written software.
America’s biopharmaceutical R&D engine consumes over $100 billion every year, and the costs continue to rise. The past decade has brought a cambrian explosion of new technology to accelerate the development of new medicines and scientific discovery, producing enormous amounts of data.
Take cryogenic electron microscopy for example. This went from collecting single integrated images to several terabytes of data per day. By 2025, the total amount of genomics data alone is is expected to equal or exceed the total of three other major producers of data: astronomy, YouTube, and Twitter.
To keep up, the use of machine learning, deep learning, and AI has exploded and become an essential part of the biotech industry. Bench scientists turn to bioinformaticians. Half of the most recent science papers are software-intensive projects, written by scientists who were never formally trained.
Our scientists are struggling.