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It was pretty incredible to open up https://vimeo.com/215926017 https://vimeo.com/215926017 and click at a random timestamp (29:30) and hear "we're trying to us

It was pretty incredible to open up https://vimeo.com/215926017 https://vimeo.com/215926017 and click at a random timestamp (29:30) and hear "we're trying to use AI to diagnose cancer by examining the DNA that's free-floating in your bloodstream." This is clearly the future, if it can work. That's probably one of the biggest startup ideas that you could possibly have. I hope that whoever's behind it is successful.

sjg007 9y ago
You don't need AI tor that.
- jessaustin 9y ago
  Yeah it seems like it's just lots of in vivo prototype tests plus statistics?
  - dboreham 9y ago
    "AI" is what we're calling statistics these days..
- avip 9y ago
  You need it raise money. Cancer + AI = $$$
entee 9y ago
Freenome is the company, they're doing interesting work but it's still early days. This isn't actually a very new idea, it's been floating around for years in academia (I've personally been hearing it about it for at least 5 years). The hard part isn't really the AI per se, it's getting enough DNA from the circulating copies (i.e. sample prep) and being lucky enough that the cancer you're trying to diagnose actually puts out enough DNA for you to measure at an early enough stage to be clinically relevant. In other words, if you can only get DNA when it's at stage 4 and metastatic, your DNA test isn't actually very useful. If you can get stage 1 cancers, now you're talking, but in those cases tumors tend to shed a lot less DNA (among other reasons because they're smaller). A very good friend of mine is their CSO, I think they've got a really cool idea and could indeed go far, but it's a fiendishly hard problem.
- sillysaurus3 9y ago
  As someone who has zero experience but is extremely interested, could you ELI5 why it's difficult to detect whether some DNA is cancerous? In other words, The hard part isn't really the AI per se, it's getting enough DNA from the circulating copies (i.e. sample prep) It sounds like there's a way to detect "This DNA is definitely cancerous," but the problem is that the test only works when you give it enough DNA. My question is, where does this "enough" criteria come from? Why doesn't it work with a single cell? (I know there are obvious reasons, but I don't know what they are.)
  - entee 9y ago
    These are all good questions, and full disclosure I know only the basics in this area. DNA can be identified as cancerous for a variety of reasons, though typically what you're looking for is some mutation you know to exist in cancer. This could be a single point mutation (insertion/deletion/change of a given DNA base pair), a loss/gain/modification of several adjacent base pairs, or whole scale genome rearrangements (deletion, insertion, inversion, replication) that will result in of two pieces of DNA being adjacent although you know they shouldn't be next to one another (see https://en.wikipedia.org/wiki/Philadelphia_chromosome https://en.wikipedia.org/wiki/Philadelphia_chromosome for a quite well known example). You could also look for copy number variation (gene X has way more or way fewer copies than expected). I'm probably missing some as well, but those are the biggies. To detect these, you're going to use either something like microarrays, QPCR, or DNA sequencing. Today people talk almost exclusively about high-throughput sequencing (HTS) because it has gotten quite cheap, gives you large amounts of data, can be made massively parallel and isn't as hindered by needing to know very precisely what you're looking for (microarrays and QPCR require somewhat more targeting; HTS also needs you to know what you're looking for, but not in quite the same ways). In all of those cases you need a sample of DNA (duh). These can all be made to work if you have a single cell in hand, it's tricky but sample prep does exist for single cells at a time. Trouble is, you need that cell in hand. There are about 5L of blood in the human body. A human cell will range from 1-10 pico-liters. You will take a blood sample of 2 milli-liters. Chances are pretty slim your one cell will be in that 2mL. Even if it is, there are billions of other cells in that 2mL adding additional noise. Usually though, we're looking at circulating DNA fragments with these technologies, and depending on the stage of the cancer and the type of cancer, there may be enough to pick up on in the blood. How to do that best is an area of active R&D. Just dug up review if you want to learn more: http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002205 http://journals.plos.org/plosmedicine/article?id=10.1371/jou...
ktu100 9y ago
In Los Angeles area, how does one get involved in these projects? I would like to volunteer at a local research lab. I am coming from a computer scientist background and would like to learn more about the medical space.
- entee 9y ago
  Look at the list of faculty for UCLA/USC in the Biochemistry or Bioengineering areas of focus. Find a lab or two that have a blurb that interest you, read a paper or two from those labs, then email the prof. Much like in CS/Software, it'll help if you've read a bit of their work and/or can show some way you could contribute directly. i.e. "I specialize in CS and did a side-project analyzing <gene_dataset_x> where I found <something_cool>. I read your <paper> and found <this_thing_you_did> was very cool for <insightful_reason>. I'd love to get more involved in the field and possibly find a volunteer position where I could contribute, would you have time to chat on the phone or over coffee sometime?" One place to look for genomic data: http://www.internationalgenome.org/data/ http://www.internationalgenome.org/data/ There are others, google around and if you could also look at https://www.plos.org https://www.plos.org journals to keep an eye out for new freely available articles in this and other areas of biology. Good luck! :)
- sjg007 9y ago
  NantWorks is basically doing this. You could get a job there. Otherwise academic labs and Cedar Sinai maybe.

sjg007 9y ago

You don't need AI tor that.

jessaustin 9y ago
Yeah it seems like it's just lots of in vivo prototype tests plus statistics?
- dboreham 9y ago
  "AI" is what we're calling statistics these days..
avip 9y ago
You need it raise money. Cancer + AI = $$$

entee 9y ago

Freenome is the company, they're doing interesting work but it's still early days. This isn't actually a very new idea, it's been floating around for years in academia (I've personally been hearing it about it for at least 5 years). The hard part isn't really the AI per se, it's getting enough DNA from the circulating copies (i.e. sample prep) and being lucky enough that the cancer you're trying to diagnose actually puts out enough DNA for you to measure at an early enough stage to be clinically relevant. In other words, if you can only get DNA when it's at stage 4 and metastatic, your DNA test isn't actually very useful. If you can get stage 1 cancers, now you're talking, but in those cases tumors tend to shed a lot less DNA (among other reasons because they're smaller). A very good friend of mine is their CSO, I think they've got a really cool idea and could indeed go far, but it's a fiendishly hard problem.

sillysaurus3 9y ago
As someone who has zero experience but is extremely interested, could you ELI5 why it's difficult to detect whether some DNA is cancerous? In other words, The hard part isn't really the AI per se, it's getting enough DNA from the circulating copies (i.e. sample prep) It sounds like there's a way to detect "This DNA is definitely cancerous," but the problem is that the test only works when you give it enough DNA. My question is, where does this "enough" criteria come from? Why doesn't it work with a single cell? (I know there are obvious reasons, but I don't know what they are.)
- entee 9y ago
  These are all good questions, and full disclosure I know only the basics in this area. DNA can be identified as cancerous for a variety of reasons, though typically what you're looking for is some mutation you know to exist in cancer. This could be a single point mutation (insertion/deletion/change of a given DNA base pair), a loss/gain/modification of several adjacent base pairs, or whole scale genome rearrangements (deletion, insertion, inversion, replication) that will result in of two pieces of DNA being adjacent although you know they shouldn't be next to one another (see https://en.wikipedia.org/wiki/Philadelphia_chromosome https://en.wikipedia.org/wiki/Philadelphia_chromosome for a quite well known example). You could also look for copy number variation (gene X has way more or way fewer copies than expected). I'm probably missing some as well, but those are the biggies. To detect these, you're going to use either something like microarrays, QPCR, or DNA sequencing. Today people talk almost exclusively about high-throughput sequencing (HTS) because it has gotten quite cheap, gives you large amounts of data, can be made massively parallel and isn't as hindered by needing to know very precisely what you're looking for (microarrays and QPCR require somewhat more targeting; HTS also needs you to know what you're looking for, but not in quite the same ways). In all of those cases you need a sample of DNA (duh). These can all be made to work if you have a single cell in hand, it's tricky but sample prep does exist for single cells at a time. Trouble is, you need that cell in hand. There are about 5L of blood in the human body. A human cell will range from 1-10 pico-liters. You will take a blood sample of 2 milli-liters. Chances are pretty slim your one cell will be in that 2mL. Even if it is, there are billions of other cells in that 2mL adding additional noise. Usually though, we're looking at circulating DNA fragments with these technologies, and depending on the stage of the cancer and the type of cancer, there may be enough to pick up on in the blood. How to do that best is an area of active R&D. Just dug up review if you want to learn more: http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002205 http://journals.plos.org/plosmedicine/article?id=10.1371/jou...

ktu100 9y ago

In Los Angeles area, how does one get involved in these projects? I would like to volunteer at a local research lab. I am coming from a computer scientist background and would like to learn more about the medical space.

entee 9y ago
Look at the list of faculty for UCLA/USC in the Biochemistry or Bioengineering areas of focus. Find a lab or two that have a blurb that interest you, read a paper or two from those labs, then email the prof. Much like in CS/Software, it'll help if you've read a bit of their work and/or can show some way you could contribute directly. i.e. "I specialize in CS and did a side-project analyzing <gene_dataset_x> where I found <something_cool>. I read your <paper> and found <this_thing_you_did> was very cool for <insightful_reason>. I'd love to get more involved in the field and possibly find a volunteer position where I could contribute, would you have time to chat on the phone or over coffee sometime?" One place to look for genomic data: http://www.internationalgenome.org/data/ http://www.internationalgenome.org/data/ There are others, google around and if you could also look at https://www.plos.org https://www.plos.org journals to keep an eye out for new freely available articles in this and other areas of biology. Good luck! :)
sjg007 9y ago
NantWorks is basically doing this. You could get a job there. Otherwise academic labs and Cedar Sinai maybe.