As someone who's worked in drug discovery and development, I wish finding bio-markers and drugging targets were this easy so we could improve the lives of millions of patients. Patient phenotypic information is locked up in the clinic notes often as free text or is no longer entered very well at all because doctors are rushed seeing more patients. Tools like The human Phenotype ontology format help solve this problem and are being used in translational biomedical informatics. http://human-phenotype-ontology.github.io/downloads.html

It isn't easy.

A lot of folks in silicon valley percieve that the FDA is holding back leviathan innovation for drugs. Just not the case.

How is it possible that the technologies that most people think are important for drug discovery have become hundreds, thousands, or billions of times cheaper, while the cost of R&D, per drug discovered, increased roughly 100 fold between 1950 and 2010.

Even with all those great advances. Eroom's law is still a pervasive thing. The proof is in the pudding and suggests that brute-force techniques don't relate to ROI.

Patent System as is. We have a patent system that encourages developing drugs that interact with a small number of enzymes and molecules that we already know and understand how they operate. Low if not zero risk.

It turns out that predicting a protein's structure from it's amino acid chain sequence is really tough.

I think it's stupid to patent pathways, treatment methodologies, research tools, and assays. This is a paralyzing bottleneck for the industry.

But anyways, yeah, I'm excited to see what comes out of the NIH and things like this ontology tool.

I'm working on this problem

If I can help, feel free to reach out to me. :)

Thanks for the comment, kumarski! Excited to see a lot of awesome work being done here.

<3

Who is annotating the records?