insitro | Machine Learning for Drug Discovery | South San Francisco, CA | Full Time | Onsite
insitro is reinventing drug discovery by bringing cutting-edge machine learning in a closed loop with our high throughput robotic biology data factory.
What's interesting about this approach (TIL expansion) relative to other leading cellular immunotherapy approaches (CAR-T/NK and TCR) is that it doesn't rely on gene editing. Long term, I think genetically "programmable" cellular immunotherapies are more likely to win (e.g. because they can be programmed to overcome tumor immune suppression), but it's impressive that a durable response is achieved here with clonally expanded TILs.
I would put > 50/50 odds on there being a human alive today with at least one CRISPR-edited germline variant. I think the question is now how can we regulate/control CRISPR germline editing; not how can we prevent it.
Human embryo gene editing was reported in May 2015 (http://dx.doi.org/10.1007/s13238-015-0153-5). It's reasonable to assume that the editing took place significantly before the submission date, especially given reports that the paper was first rejected from several other journals on ethical grounds (http://www.nature.com/news/chinese-scientists-genetically-mo...). I'm not trying to suggest that these particular scientists have performed experiments on viable embryos also, but I'd be very surprised if someone hasn't.
Key question for digital health / biotech startups is whether direct to consumer (D2C) advertising for testing services (e.g. genetic carrier screening; cancer risk screening) would be included.
insitro is reinventing drug discovery by bringing cutting-edge machine learning in a closed loop with our high throughput robotic biology data factory.
Current software roles include:
- Machine Learning Engineer
- Data Engineer
- Head of Data Engineering
See: http://insitro.com/jobs or feel free to email me: [email protected]