Koller: Theranos never published peer-reviewed papers or disclosed raw data
Daphne Koller · a16z Podcast | Breaking Into Bio · Jan 2, 2019 · at 23:58
Daphne Koller uses Theranos as a negative example of corporate transparency during a discussion on establishing scientific credibility in healthcare startups.
0:00 / 0:19exact quote · 19.6s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“We all know Theranos, you know, that's an extreme example, but, ah, the fact that they never had a peer-reviewed publication, they never presented their data in any way, they kept even potential customers from looking at the raw data, I mean, those are all really bad things for a company to do, even if you're not Theranos.”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Daphne Koller
Koller: General artificial intelligence is not right around the corner
“I think one of the big risks that we run as a machine learning community is the incredible amount of hyperbole that's going on right now, where it's like, we're gonna have general intelligence right around the corner. We're not. Ok, we really aren't.”
Koller: Insitro will deliver AI-discovered medicines to patients by 2030
“The hope is that by the end of the Of this decade, we will have built this process, we will have run through it a number of times, we will have delivered some medicines to patients in our first tranche of indications, but then we will have learned enough from …”
Koller: Biological ML requires exploiting domain structure due to dataset limits
“We're still not in the large, large data regime where, you know, blind architectures that don't exploit structure of the problem can just work out of the box. So you really have to understand your problem domain and figure out how to exploit the structure that…”
Koller: insitro operates a unique data factory generating biological data on spec
“So one of the things that we have at Insitro that is truly unique is we have a data factory. We have put together the tools that have been developed by people who are taking pluripotent stem cells, which are cells from you or me or anyone in this audience and …”
Koller: Insitro runs genome-wide CRISPR screens in two weeks
“When they're all in a pool, you eliminate all of those artifacts, and all of a sudden you have the ability to measure a genome-wide CRISPR screen, basically, so, 20,000 genes in the genome, all modifying the same cellular background in the same dish with a dif…”
Koller: Human technician variance is a primary signal in biological ML
“When you do biological experiments, one of the strongest signals when you apply machine learning to it is what was the technician who actually did the experiments? You could read that very clearly off the cells because they behave a little bit differently.”