Let me take a crack at this. It’s not my AMA, but it’s a question that comes up periodically in bioinformatics - the cross disciplinary field that deals with data science/programming and biology.

Most importantly, the field already exists, and the low hanging fruit was mostly picked 30 years ago, when it was reasonably possible for a programmer to work on a problem that hadn’t been tackled yet, and automate something that the biologists hadn’t gotten around to.

Alas, those days are gone. Bioinformaticians are usually very competent programmers, and rarely can make use of people from computer science without training them in biology first. Biology, after all, is the field in which nature has evolved solutions to problems, and exceptions are more common than the rules they break.

Thus, time may be short in this field, but insight is truly the valuable commodity. Understanding how to interpret the biological data is far far more important than automation. While we do see machine learning helping somewhat, pattern finding and the patterns themselves are useless without someone to interpret them and decide if they’re real. Or worth following up on. Usually they aren’t. Biology data is inherently very noisy.

So, all of that is the long way of saying that longevity or curing cancer isn’t going to be a question of automating our way to a solution. If you want to understand the complexity of the problem, you would need to understand more about the problem itself. There’s no simple solutions here, and time is only part of the missing piece needed to make real progress.

How/do you anticipate overcoming regulatory hurdles associated with that type of use case? I can see how this data would be valuable, but this whole concept sounds like a giant HIPA violation as soon as you try and operationalize it.

ETA: I don't think the limiting factor on big data applications to public health is the lack of conceptual frameworks, I think it's a failure of this type of plan when the rubber hits the road. I'd rather be wrong, so tell me how I am!

What's the percent of chemicals your AI has discovered that would be classified as biological weapons?

I'll take the first recursion joke I can I'll take the first recursion joke I can I'll take the first recursion joke I can ...

They didn’t stop the trials mate.

Viagra was brought to market first for Pulmobary Hypertension, and is still on the market for that indication.

After release reports showed massive benefit in ED, this approval for that second indication was obtained.

It is still the major treatment option for pulmonary hypertension an otherwise very quickly lethal disease and now progression can be delayed by decades at best.

Mod did it but it's ok

Thanks, appreciate all your words

Great attitude. Whyd you delete this post though

Actually, before I decided to launch a global version of our backpack, we produced the local version and sold it to local customers and got good feedback from them. I know this product won't be for the masses, but there are parents who are willing to spend this amount of money to get their kids a good product. A great stepping stone makes me more believe that global customers will welcome our product too.

Is your algorithm compatible with Oligonucleotide therapeutics? Not quite small molecules but not quite biologicals either.

I’ve recently become obsessed with the idea of using AI and technology to solve the problem of human longevity. I want to figure out how to beat cancer and other diseases before they end up killing me or one of my loved ones.

I don’t understand why so many people are distracting themselves with random careers when they could be literally saving their own lives if they just went into medical research.

So my question for you is this:

How can I help you?

I am currently on a sabbatical, in between projects, and I’m looking for my next thing to dedicate my life to.

I am a software engineer with over 20 years of professional experience in the field. I have worked on tech and software in HIPAA healthcare environments as well as FERPA educational environments. I have helped maintain servers in physical data centers. I have built and scaled large virtual server systems. I have built numerous web apps and tools. I have built machine learning data pipelines and data warehouses. My most recent project was building out an ai voice home shopping assistant for a major retailer.

You say your most constrained resource is time. What if I could help with that?

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Do you guys need someone who can do CyTOF?

good answer :)

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did you just make this

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Thanks for the reply!

I see, thanks! Good to know the effort in running Folding@Home hasn't been made redundant by AI just yet, although I certainly look forward to developments in the field!

Are there any cases within drug discovery where the source distribution shifts such that it differs from the original dataset?

How often do you use the climbing wall?

Any great resources to find those people that you’re able to share?

Really a fascinating approach.

I can’t comment about all of our internal technologies. But! We did recently publish work with our collaborators at Genentech on benchmarking methods to builds maps of biology, which we evaluated on both our phenomics data and (publicly-available) 10x scRNA-seq (Perturb-seq) data – check it out here. So, draw your own conclusions…

Okay, thanks for the response. Do you see anything happening in the future?