My story

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I first encountered the term "personalized medicine" at my first job out of undergrad. I had a degree in genetics and went to work for a small pharma called Vanda. It had been founded by the former head of pharmacogenomics from Novartis, and was doing some amazing work - developing a drug to treat schizophrenia, and developing a panel of genomic markers to predict who would respond to it. Unfortuntaely, while I was there, the FDA mistakenly rejected the NDA for this drug. They actually approved it eight months later after an appeal, but because of $$$, half the company had to be let go in that time. And so this whole groundbreaking framework for improving psychiatric treatment using precision medicine was lost.

In the meantime, I went and did a PhD in neuroscience, since I'd become fascinated with understanding how the brain works. I ended up doing my thesis on experience-dependent plasticity, since it struck me that the truly important stuff about what makes us who we are isn’t the genetics, which codes a blueprint for a brain, but the impact of our life experience on how our brains are wired.

It just so happened that the main finding of my graduate work was that even in early development, the brain essentially learns by sending information backward through circuits in order to tweak upstream connections. I discovered this about two months after the three "godfathers of AI" wrote this review in Nature describing how training artificial neural networks with this principles was allowing computers to see (and now just a decade later, think).

So, out of grad school, I did a fellowship in data science and went to work on human health data, excited to apply these amazing tools to understand and improve human health. I spent two years at a fantastic company called PatientsLikeMe, and then five years at a nonprofit focused on advancing PTSD research. Most of that time was spent working with patient health data to try to understand how we might better differentiate or sub-type psychiatric conditions to target treatments more precisely.

Over that time, I've watched hundreds of millions of dollars get poured into studying the biology of these conditions, all the while growing more and more convinced that a better way to approach this would be to focus first on the psychology. Something like depression can mean 100 different things to 100 different people, and by filtering through structured clinical interviews and the medical field's attempt at consensus, we are losing sight of what could easily be 10 different "types" of depression.

I also think mental health is at a point in the public conscious that it’s never been before. People are willing to talk openly about it. People understand a bit more of the causes of it, and the idea of crowd-sourcing the collection of this data is now possible in a way it wouldn’t have been five years ago. I think biomedical research is making and will continue to make amazing progress towards quantifying how our brain's function, and I think it’s likely that portable EEG devices over the next 5 to 10 years will improve to the point where collecting data at scale will be within reach.

So yeah, I set up this platform to test this idea, and try to build a dataset that could help toward this goal. (The team is me, and handful of friends/ex-colleagues I've bounced ideas off)

Take the baseline survey and see what it's about.

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