5 ms·

It doesn't look like they funded many companies under the YC Bio RFP, where companies get $500K-1M for longevity products / treatments for aging related disease

It doesn't look like they funded many companies under the YC Bio RFP, where companies get $500K-1M for longevity products / treatments for aging related disease. I see one regen med company working on regenerating liver cells (Hepatx), and then a few diagnostics / synbio / research tools companies that don't seem to fit the YC Bio / longevity bucket. Wonder if there will be more tomorrow...

newman8r 8y ago
I'd love to work on a medical/biotech startup, but the barriers to entry seem so much bigger than a standard SAAS project. It seems like there's some progress towards cloud-labs that could reduce those barriers (https://www.emeraldcloudlab.com/ https://www.emeraldcloudlab.com/ looks interesting) - and that's something I want to learn more about.
- aaavl2821 8y ago
  The barriers to entry are certainly different, and maybe bigger, but I think there's a lot of misconception about what it takes to get a biopharma company started (i say biopharma rather than biotech bc biopharma is where the vast vast majority of VC money in healthcare goes). You usually need: * a team made up of a few molecular / cell biologists (analog to needing engineers for a SaaS) * solid early-stage science (could be nothing more than a few experiments to validate / build on a publication) * a well thought out experimental plan -- details of the initial work you'd do to validate your core hypotheses, why you chose those experiments and not others, and feedback from other smart scientists and investors to validate your design (this would be the analog of early product development, culminating in product-market fit over 12-24 months) * funding for your initial experiments: a few hundred thousand up to a few million The main difference is that 1) iteration cycles are much longer and more expensive in biopharma and 2) value inflection is more binary. So you need to be really thoughtful about every detail of your initial work. In recent years, biotech startups have actually been able to grow really big faster than tech startups. Kite and Juno were acquired for $12B and $9B less than 5 years after Series A -- getting to decacorn status faster than pretty much any software co I think including dropbox, snap, etc A lot of the initial work is done as a "virtual" company with no lab. There is a massive network of outsourced research groups that can do pretty much any experiment you want at high quality and reasonable cost
  - mmt 8y ago
    > A lot of the initial work is done as a "virtual" company with no lab. After that stage, if a true "wet lab" is necessary, one of the perceived barriers may be, especially for the majority of modern software professionals, the situation with lab computing. Interpreting what former colleague (who is now a YC biotech founder) recently explained to me, labs often face significant challenges in needing on-premises computer hardware. [1] For some labs (DNA sequencing being a notable example, with the cost of sequencers plummeting), the sheer quantity of raw data flowing from the instruments can make (fully) cloud-based processing prohibitively expensive, if not impossible [2]. Having on-site servers hardware can be necessary, but, as a self-fulfilling prophecy, the knowledge about how to do this (supposedly) "nightmare" task well has been dying out. The far bigger issue, applicable to the vast majority of not all labs, is all the computers attached to the instruments and lab automation equipment, which are, in general, running proprietary software on a broad spectrum of Windows versions, which the users (lab) patch/maintain/administer at their peril (lest the proprietary software and, thereby, the instrument itself, stop working). Unfortunately (for me), the on-site server problem is generally much less dire and painful than the instrument-control problem. It can also be solved just barely well enough to cut down the size of the raw data, at which point software people breath a huge sigh of relief because they can ship it to the cloud and pretend hardware doesn't exist. The instrument-control/Windows problem ends up being hugely labor-intensive even to approximate a solution involving decent security and reliability. It also can require a remarkable amount of learning things that might never be used again in ones career, such as how a particular vendor's software communicates with a particular model and version of that vendor's instrument (so worth it, if it means making virtualization possible!). There are lab automation companies attempting to provide this sort of thing as a service, but they're not numerous, and it's unclear if this kind of IT is, so far, just a services/consulting add-on. [1] I consider my expertise in this area to be differentiating part of my Ops skillset, so it was of particular personal interest. [2] On a workable scale. With enough money, it should be possible to bring even 10-gigabit fiber Internet anywhere, or move the lab somewhere that already has it, but not in zero/negligible time.

newman8r 8y ago

I'd love to work on a medical/biotech startup, but the barriers to entry seem so much bigger than a standard SAAS project. It seems like there's some progress towards cloud-labs that could reduce those barriers (https://www.emeraldcloudlab.com/ https://www.emeraldcloudlab.com/ looks interesting) - and that's something I want to learn more about.

aaavl2821 8y ago
The barriers to entry are certainly different, and maybe bigger, but I think there's a lot of misconception about what it takes to get a biopharma company started (i say biopharma rather than biotech bc biopharma is where the vast vast majority of VC money in healthcare goes). You usually need: * a team made up of a few molecular / cell biologists (analog to needing engineers for a SaaS) * solid early-stage science (could be nothing more than a few experiments to validate / build on a publication) * a well thought out experimental plan -- details of the initial work you'd do to validate your core hypotheses, why you chose those experiments and not others, and feedback from other smart scientists and investors to validate your design (this would be the analog of early product development, culminating in product-market fit over 12-24 months) * funding for your initial experiments: a few hundred thousand up to a few million The main difference is that 1) iteration cycles are much longer and more expensive in biopharma and 2) value inflection is more binary. So you need to be really thoughtful about every detail of your initial work. In recent years, biotech startups have actually been able to grow really big faster than tech startups. Kite and Juno were acquired for $12B and $9B less than 5 years after Series A -- getting to decacorn status faster than pretty much any software co I think including dropbox, snap, etc A lot of the initial work is done as a "virtual" company with no lab. There is a massive network of outsourced research groups that can do pretty much any experiment you want at high quality and reasonable cost
- mmt 8y ago
  > A lot of the initial work is done as a "virtual" company with no lab. After that stage, if a true "wet lab" is necessary, one of the perceived barriers may be, especially for the majority of modern software professionals, the situation with lab computing. Interpreting what former colleague (who is now a YC biotech founder) recently explained to me, labs often face significant challenges in needing on-premises computer hardware. [1] For some labs (DNA sequencing being a notable example, with the cost of sequencers plummeting), the sheer quantity of raw data flowing from the instruments can make (fully) cloud-based processing prohibitively expensive, if not impossible [2]. Having on-site servers hardware can be necessary, but, as a self-fulfilling prophecy, the knowledge about how to do this (supposedly) "nightmare" task well has been dying out. The far bigger issue, applicable to the vast majority of not all labs, is all the computers attached to the instruments and lab automation equipment, which are, in general, running proprietary software on a broad spectrum of Windows versions, which the users (lab) patch/maintain/administer at their peril (lest the proprietary software and, thereby, the instrument itself, stop working). Unfortunately (for me), the on-site server problem is generally much less dire and painful than the instrument-control problem. It can also be solved just barely well enough to cut down the size of the raw data, at which point software people breath a huge sigh of relief because they can ship it to the cloud and pretend hardware doesn't exist. The instrument-control/Windows problem ends up being hugely labor-intensive even to approximate a solution involving decent security and reliability. It also can require a remarkable amount of learning things that might never be used again in ones career, such as how a particular vendor's software communicates with a particular model and version of that vendor's instrument (so worth it, if it means making virtualization possible!). There are lab automation companies attempting to provide this sort of thing as a service, but they're not numerous, and it's unclear if this kind of IT is, so far, just a services/consulting add-on. [1] I consider my expertise in this area to be differentiating part of my Ops skillset, so it was of particular personal interest. [2] On a workable scale. With enough money, it should be possible to bring even 10-gigabit fiber Internet anywhere, or move the lab somewhere that already has it, but not in zero/negligible time.