4 ms·

The thing is this kind of idea is not new. Finding new targets is hard science that needs a ton of experiments to validate that your theoretical models even wo

by bbgm 11y ago

The thing is this kind of idea is not new. Finding new targets is hard science that needs a ton of experiments to validate that your theoretical models even work. For now this is low risk and no cost to the pharma partner, but it's a not a new model and in my experience not one that works.

timr 11y ago
"The thing is this kind of idea is not new." ...most startup companies aren't doing anything new. How many different food-delivery services has YC funded? Photo-sharing services? Video startups? AirBnB wasn't anything new in 2007, either. Dropbox was criticized because everyone knew that file sharing had been done before. This goes back to what I was saying about biotech being stodgy: the one thing the software industry has going for it is that it's willing to fling seed capital at re-tread ideas. If success is mostly about being in the right place for luck to occur, then the secret is putting enough companies in a place to experience luck. I think that's basically what YC does. So-called "biotech investors" tend to want to wait around for commercially ready tech to just fall out of academic labs, so that they can avoid putting any investment at all into R&D. There are probably a lot of inexperienced teams that could make a business in biotech if only they had access to cash.
- w1ntermute 11y ago
  > ...most startup companies aren't doing anything new. How many different food-delivery services has YC funded? Photo-sharing services? Video startups? AirBnB wasn't anything new in 2007, either. Dropbox was criticized because everyone knew that file sharing had been done before. There's a fundamental difference between trying something again where the customers weren't receptive and trying something again where the product couldn't be created. Customer reception can change over time, often quite rapidly and drastically, making previously failed business models successful (ex: Webvan -> Instacart). But nature doesn't just change (at least not over short timescales). Moreover, as cge explains elsewhere in this thread, you cannot really iterate in biotech: > Good ideas in software might not catch on, but good ideas in science more often than not turn out to be entirely wrong. Do a closed beta of your software, too, and while your users might not end up liking the software much, it's very unlikely that it's just going to fundamentally fail to work at all. Clinical trials can often end up that way. Contrast this to business model-based innovation in tech, where a slight tweak can be the difference between a unicorn and a dud.
  - timr 11y ago
    The difference between success and failure in biotech lead generation is finding a good lead. That's something that is strongly influenced by luck. I can point to famous researchers who have made entire careers out of this sort of momentary serendipity, actually.
    - w1ntermute 11y ago
      Yes, that is exactly my point. You cannot iterate your way to a serendipitous discovery.
      - timr 11y ago
        Actually, that's the only way you get to a serendipitous discovery: you make lots of shots, and some of them go in the goal.
        w1ntermute 11y ago
        > you make lots of shots, and some of them go in the goal That's not iteration, that's banging your head against a wall and praying for a miracle. Iteration implies methodically and continuously moving towards an optimal solution, not heading back to the RNG after each failed attempt.
  - chenja 11y ago
    We definitely didn't invent systems biology for drug discovery. But Google didn't invent search engines either, I think that we have a fresh and novel approach which is really differentiated by the details. Another thing I think is different about the industries is that while there are tons of food delivery and photo-sharing startups, there's no really effective/disease modifying treatments for common diseases such as Alzheimer's disease, frontotemporal dementia, ALS, etc, so I think there's plenty of space for any number of new approaches to be tested in the field. I feel it's more worthwhile than pumping billions more into failed antibodies against beta amyloid, as seems to be the trend nowadays.
- bbgm 11y ago
  Biotech startups with a computational method of target discovery that is "different from the norm at Big Pharma" have been around at least since the late 90s. The problem is targets are cheap. Validating those targets is expensive and is the rate limiting step. I have no problems with these companies existing. They should and can tackle some hard problems and develop algorithms and methods that are difficult to pursue in Big Pharma. The problem is that too many are presented as silver bullets that will magically cure xyz, and that's just false.
  - timr 11y ago
    Yeah, I know what you're saying here, and I don't disagree. I only disagree with the comment that they aren't "doing something new". It's sufficient to do some old thing better in some way that matters to existing customers -- and that's an implementation detail that will never come out of a TechCrunch press release.
  - chenja 11y ago
    We have been actively validating targets, and in fact Alice's PhD work was centered on performing the in vitro and in vivo validation experiments for computational drug leads. We aren't asking for people to believe in magic, and ultimately we hope that our preclinical experiments will reveal whether or not we have something.

by bbgm 11y ago

timr 11y ago

"The thing is this kind of idea is not new." ...most startup companies aren't doing anything new. How many different food-delivery services has YC funded? Photo-sharing services? Video startups? AirBnB wasn't anything new in 2007, either. Dropbox was criticized because everyone knew that file sharing had been done before. This goes back to what I was saying about biotech being stodgy: the one thing the software industry has going for it is that it's willing to fling seed capital at re-tread ideas. If success is mostly about being in the right place for luck to occur, then the secret is putting enough companies in a place to experience luck. I think that's basically what YC does. So-called "biotech investors" tend to want to wait around for commercially ready tech to just fall out of academic labs, so that they can avoid putting any investment at all into R&D. There are probably a lot of inexperienced teams that could make a business in biotech if only they had access to cash.

w1ntermute 11y ago
> ...most startup companies aren't doing anything new. How many different food-delivery services has YC funded? Photo-sharing services? Video startups? AirBnB wasn't anything new in 2007, either. Dropbox was criticized because everyone knew that file sharing had been done before. There's a fundamental difference between trying something again where the customers weren't receptive and trying something again where the product couldn't be created. Customer reception can change over time, often quite rapidly and drastically, making previously failed business models successful (ex: Webvan -> Instacart). But nature doesn't just change (at least not over short timescales). Moreover, as cge explains elsewhere in this thread, you cannot really iterate in biotech: > Good ideas in software might not catch on, but good ideas in science more often than not turn out to be entirely wrong. Do a closed beta of your software, too, and while your users might not end up liking the software much, it's very unlikely that it's just going to fundamentally fail to work at all. Clinical trials can often end up that way. Contrast this to business model-based innovation in tech, where a slight tweak can be the difference between a unicorn and a dud.
- timr 11y ago
  The difference between success and failure in biotech lead generation is finding a good lead. That's something that is strongly influenced by luck. I can point to famous researchers who have made entire careers out of this sort of momentary serendipity, actually.
  - w1ntermute 11y ago
    Yes, that is exactly my point. You cannot iterate your way to a serendipitous discovery.
    - timr 11y ago
      Actually, that's the only way you get to a serendipitous discovery: you make lots of shots, and some of them go in the goal.
      - w1ntermute 11y ago
        > you make lots of shots, and some of them go in the goal That's not iteration, that's banging your head against a wall and praying for a miracle. Iteration implies methodically and continuously moving towards an optimal solution, not heading back to the RNG after each failed attempt.
- chenja 11y ago
  We definitely didn't invent systems biology for drug discovery. But Google didn't invent search engines either, I think that we have a fresh and novel approach which is really differentiated by the details. Another thing I think is different about the industries is that while there are tons of food delivery and photo-sharing startups, there's no really effective/disease modifying treatments for common diseases such as Alzheimer's disease, frontotemporal dementia, ALS, etc, so I think there's plenty of space for any number of new approaches to be tested in the field. I feel it's more worthwhile than pumping billions more into failed antibodies against beta amyloid, as seems to be the trend nowadays.
bbgm 11y ago
Biotech startups with a computational method of target discovery that is "different from the norm at Big Pharma" have been around at least since the late 90s. The problem is targets are cheap. Validating those targets is expensive and is the rate limiting step. I have no problems with these companies existing. They should and can tackle some hard problems and develop algorithms and methods that are difficult to pursue in Big Pharma. The problem is that too many are presented as silver bullets that will magically cure xyz, and that's just false.
- timr 11y ago
  Yeah, I know what you're saying here, and I don't disagree. I only disagree with the comment that they aren't "doing something new". It's sufficient to do some old thing better in some way that matters to existing customers -- and that's an implementation detail that will never come out of a TechCrunch press release.
- chenja 11y ago
  We have been actively validating targets, and in fact Alice's PhD work was centered on performing the in vitro and in vivo validation experiments for computational drug leads. We aren't asking for people to believe in magic, and ultimately we hope that our preclinical experiments will reveal whether or not we have something.