1. That graph completely omits the quality of the sequence data being generated (hint: it's pretty terrible).

2. Hyping up cheaper sequencing the way you are is nothing more than what Sydney Brenner referred to as "low-input, high-throughput, no-output biology" (video source: http://thesciencenetwork.org/programs/reading-the-human-geno...). Also see: http://wavefunction.fieldofscience.com/2015/03/cancer-genomi...

3. Here's a more useful Moore's law derivative that's seen in the life sciences: http://www.nature.com/nrd/journal/v11/n3/fig_tab/nrd3681_F1....

While cheaper sequencing hasn't really produced much in the way of new treatments (yet), I disagree that it hasn't been productive or that sequence data is of low accuracy. For example, it is striking to see how relatively little was known about Mendelian disease genes before 1990 (see https://www.genome.gov/Multimedia/Slides/GSPFuture2014/04_Mc..., slide 6, as an example for retinal diseases). I think one of the most frustrating things now is that the price of sequencing isn't continuing to decrease.

You bring up another good point about "Eroom's Law" in which pharma productivity is actually decreasing, and that article was actually one of the things that got us interested in trying to do something new. What we are trying to do is to help reverse that trend by doing something different than what large pharma companies are already working on - if we keep doing the same thing despite ever-decreasing productivity, then I don't see how we can expect the trend to change.

Wow. That last chart is really damning. It goes a long way to explaining why biotech has been such a moribund area of investment.

You can sequence as fast and as cheaply as you like, but the big-O on biological research is not our ability to generate DNA sequences.