Summary & Insights
0:00:02 Hi and welcome to the inaugural edition
0:00:04 of the A16Z BioJournal Club.
0:00:05 I’m Hannah.
0:00:08 Our goal here is to take an interesting new research paper
0:00:10 in the field and talk about why it’s cool,
0:00:12 break down a little of the science involved,
0:00:14 and consider what the implications of this research
0:00:15 for industry might be.
0:00:17 So in our first take, A16Z General Partner
0:00:21 on the Bio Fund Jorge Conde and Deal Team Partner Andy Tran
0:00:24 chat with me about two papers recently published.
0:00:27 The first transposon encoded CRISPR/CAS systems
0:00:30 direct RNA guided DNA integration
0:00:33 was published by a group under Samuel H. Sternberg
0:00:36 at Columbia in nature of June 2019.
0:00:39 The second is RNA guided DNA insertion
0:00:42 with CRISPR associated transposases
0:00:45 with a team under Feng Zhang from the Broad Institute
0:00:48 published in science also in June 2019.
0:00:50 We talk about what these papers are all about
0:00:53 in the field of CRISPR development and beyond.
0:00:54 This mini podcast is available
0:00:57 as part of our new A16Z Bio Newsletter.
0:01:00 So if you like it and you want to hear more or read more,
0:01:05 please sign up for the newsletter at a16z.com/subscribe.
0:01:07 Let’s talk about what specifically is happening here.
0:01:10 What does, what a transposon encoded CRISPR/CAS system
0:01:13 direct RNA guided DNA integration?
0:01:14 Like, what does that actually mean?
0:01:16 Can you help me understand what was the interesting science
0:01:17 that was going on here?
0:01:18 – Yeah, so what’s really interesting
0:01:19 in the field of CRISPR lately,
0:01:22 and actually a few papers that came out in the recent times
0:01:26 developed a way to basically use these transposon machinery
0:01:28 inside the cell and use CRISPR to direct it
0:01:30 into a specific place in the genome
0:01:34 and really edit the genome without cutting it open at all.
0:01:36 So you can think of it as this scarless type
0:01:37 of genetic modification.
0:01:39 – Essentially what a transposon is,
0:01:42 is this sort of phenomenon that’s been observed
0:01:44 of where you have sort of these genes
0:01:46 that jump into the genome.
0:01:47 – It’s kind of mysterious what the jumping
0:01:48 is really used for.
0:01:50 People surmise that, you know, potentially, you know,
0:01:54 it helps, you know, the cells and organism evolved in general.
0:01:56 So what this paper shows is to utilize
0:01:58 this CRISPR machinery known as Cascade,
0:02:02 and it’s formed by, you know, CASS6, CASS7, CASS8 proteins
0:02:04 to really insert genes into the genome.
0:02:08 And this Cascade protein is directed to the chromosome
0:02:11 by using guided RNA, you know, CRISPR machinery,
0:02:15 and it then binds to this transposase-associated protein,
0:02:18 TNIQ, and it allows them to recruit
0:02:20 these transposable elements and then effectively integrate
0:02:22 the gene into the genome.
0:02:25 And this is super powerful because now we’re able to,
0:02:27 you know, add genes in the genome directly
0:02:29 and precisely without cutting it open.
0:02:32 It’s a scarless way to modify the genome.
0:02:35 – So in some ways, this is almost like if CRISPR
0:02:38 is about surgically inserting or editing DNA,
0:02:41 this is almost in many ways like plastic surgery, right?
0:02:42 It’s scarless. – Ah, right, right.
0:02:45 – It doesn’t leave a mark and therefore in some ways
0:02:48 it’s less risky from an intervention standpoint
0:02:49 on the genome side.
0:02:51 – What it really boils down to is that
0:02:53 this machinery utilizes a way
0:02:56 to really efficiently integrate genes into the cell,
0:02:58 into the genome specifically,
0:02:59 without having to cut it open at all.
0:03:02 And to the metaphor of the surgery,
0:03:04 this is really important in the whole context
0:03:06 of gene therapy as a whole, right?
0:03:08 ‘Cause when we started off in gene therapy,
0:03:09 we had these random integration
0:03:12 of these trans genes into the cell.
0:03:15 And, you know, this was a more stochastic process.
0:03:17 So think of it almost as, you know,
0:03:20 the arrival of this paper and papers like it
0:03:24 are showing us that we’ve gotten to a point
0:03:28 where we have a fully programmable ability
0:03:32 to integrate new genes or new DNA into a genome
0:03:34 without having to first open up
0:03:36 or break apart the DNA to do that.
0:03:38 – So let’s go back and actually situate it
0:03:40 into the development of the science,
0:03:42 what it represents for where we’ve gotten
0:03:44 from where we began.
0:03:45 – Yeah, so if you want to do the really,
0:03:47 the fast forward montage version of this.
0:03:49 – Yeah, the 80s montage.
0:03:51 – Yeah, exactly, so I’m sure you’ll put
0:03:52 in the pop music behind it.
0:03:55 – Right, yeah, and the overalls in the paintbrushes.
0:03:56 – He always started in the 60s.
0:03:57 – In the time motion.
0:03:58 – Yeah, let’s go.
0:04:00 – But look, I mean, if you go all the way back,
0:04:02 you know, one of the earliest sort of technologies
0:04:04 that came to the fore was the discovery
0:04:05 of something called the restriction enzyme.
0:04:07 And the restriction enzyme was this ability
0:04:10 to take this protein that could cut DNA
0:04:12 at these predetermined sites,
0:04:15 essentially open up the DNA,
0:04:19 and then you could introduce new genetic material,
0:04:20 and it would eventually integrate randomly,
0:04:23 but it would integrate into that DNA.
0:04:25 That’s what gave us the ability to do
0:04:27 or recombinant DNA technology,
0:04:29 which gives rise to the entire biotech field.
0:04:32 One of the earliest applications of biotechnology is
0:04:35 getting bacterial systems to integrate human insulin
0:04:38 so that we could coax bacteria to make that drug
0:04:41 or human insulin on our behalf, of course, to treat diabetics.
0:04:43 So that starts the whole field.
0:04:45 Now, you know, if you sort of move forward,
0:04:46 the objective always has been,
0:04:51 can you cure disease by repairing
0:04:55 or replacing what’s broken in DNA?
0:04:58 And so the whole field of gene therapy arises
0:04:59 with this idea that, you know,
0:05:02 can we introduce a corrected version
0:05:05 of a non-functional gene in a patient
0:05:06 and have it do the job
0:05:08 that the non-functional gene cannot do?
0:05:12 The first version was just put that gene
0:05:16 into a viral vector, into almost like a delivery vehicle,
0:05:18 introduce that into patient cells,
0:05:20 that gets taken in by the cells,
0:05:22 and the gene just starts to sort of do its job.
0:05:23 It integrates randomly in the genome,
0:05:24 but it does the job it needs to do.
0:05:26 Hopefully it integrates, or maybe it doesn’t,
0:05:28 but it just does the job to compensate
0:05:30 for some mutated gene.
0:05:33 Yeah, so it’s basically almost a parallel support system
0:05:35 that the cell has.
0:05:37 We just had the first gene therapies approved
0:05:39 over the course of the last couple of years.
0:05:42 If you look at the spark therapy, gene therapy drug for,
0:05:44 this rare inherited form of blindness.
0:05:47 And so that was one big advance forward.
0:05:49 Now, that is introducing a full gene
0:05:51 and just hoping it gets taken up by the cell.
0:05:52 Just kind of throw it in the mix.
0:05:54 Yeah, throw it in the mix and it has its own risk.
0:05:56 The original discovery of CRISPR-Cas9,
0:05:59 that system, the way that system works
0:06:02 is by making what’s called a double-stranded break
0:06:03 in the DNA molecule.
0:06:04 So if you think of, you know,
0:06:07 we all remember DNA from high school biology
0:06:10 as sort of the beautiful double helix.
0:06:12 So imagine sort of cutting that double helix in two
0:06:14 and making an end of it, right?
0:06:17 And then, you know, and then putting it back together.
0:06:18 That’s not riskless, right?
0:06:20 And by the way, it’s very well known
0:06:22 and documented that one of the big setbacks
0:06:25 that the gene therapy field had a couple of decades ago
0:06:27 was when they ran a clinical trial
0:06:28 at the University of Pennsylvania,
0:06:31 there was a patient named Jesse Gelsinger
0:06:32 who died after receiving the therapy
0:06:34 just because there’s a lot of risk associated
0:06:37 with introducing, you know, a viral capsid with a gene
0:06:39 into a cell system, into human being
0:06:41 where you could have a catastrophic result
0:06:41 and that patient died.
0:06:44 And that actually put a big pause on how we thought
0:06:47 about developing gene therapies for humans.
0:06:49 But that approach will have
0:06:51 and does have therapeutic potential.
0:06:52 And there are several companies
0:06:56 that are pursuing developing CRISPR-Cas9-based therapeutics.
0:06:58 As that advanced in parallel,
0:07:02 we started to see other gene or genome editing technologies
0:07:03 come to the fore.
0:07:06 The first one was one known as zinc finger nucleases,
0:07:08 which really didn’t have as much uptake
0:07:10 as one would expect
0:07:13 because it’s just very hard to deal with these proteins.
0:07:16 – How zinc fingers work is that you actually use these proteins
0:07:18 to bind onto DNA sequences.
0:07:21 And every time you want to iterate to find a new target,
0:07:22 cost tens of thousands of dollars
0:07:24 in a few months to develop one protein.
0:07:26 – So it’s enormously expensive and labor intensive.
0:07:27 – Exactly.
0:07:28 So it never really caught on like wildfire
0:07:30 in the community, right?
0:07:31 – It’s a very bespoke process.
0:07:34 It’s one of the type of thing.
0:07:36 And then there were other technologies.
0:07:38 There was Talens,
0:07:40 which was a bit better than zinc finger nucleases,
0:07:45 but really the big sort of shift in the field
0:07:47 was the arrival of CRISPR.
0:07:49 – And so when scientists discovered CRISPR,
0:07:52 they noticed that it was just always constant evolutionary
0:07:55 warfare between bacteriophages and bacteria
0:07:56 for billions of years.
0:07:58 – Bacteriophages are viruses.
0:07:58 – Yes.
0:08:03 – And so when these viruses inject their viral genome
0:08:04 into the bacteria,
0:08:06 you can think of it as the bacterial immune system,
0:08:10 whereas they’re able to sense these little snippets
0:08:11 of viral genome,
0:08:13 they would create a vaccination card from it,
0:08:14 and then they’ll put it back into this,
0:08:16 what is known as this CRISPR array.
0:08:18 And this would be like a vaccine card
0:08:20 or a vaccine database, if you will.
0:08:22 So every time it recognizes that foreign viral sequence.
0:08:23 – Right, then it knows what to do.
0:08:25 – It would know how to snip it away, right?
0:08:27 And then people have hijacked this machinery.
0:08:31 So what if we can program this outside of bacteria
0:08:32 and use it in human cells
0:08:35 and program it to sense not viral DNA,
0:08:38 but specific targets in the human genome.
0:08:42 And then then we can program and effectively target
0:08:44 anywhere we want in the cell, right?
0:08:46 – So now bring us forward to today.
0:08:48 So is this new development,
0:08:50 does it mean that the therapeutic potentials
0:08:52 are essentially less risky?
0:08:54 Or are there new possibilities
0:08:56 that we haven’t been able to do before?
0:08:56 Or both?
0:08:59 – Basically, you know, it’s really powerful
0:09:01 because when we talk about the first gen of gene therapy
0:09:03 to the second gen of CRISPR,
0:09:05 this paper really represents this third wave
0:09:07 in this scarless genomic editing.
0:09:10 This is basically genomic surgery at its finest, right?
0:09:13 You know, when we think about laparoscopic surgery
0:09:15 and all these advanced surgery tools,
0:09:16 we want to have, you know,
0:09:19 basically a scarless methodology of doing surgery.
0:09:21 This is a way to really cleanly integrate,
0:09:23 you know, genomic segments into the cell
0:09:25 without even touching, right?
0:09:28 And then this also represents an even broader tool
0:09:31 of, you know, the entire, you know, genomic toolkit landscape.
0:09:33 – The real promise on the near term side
0:09:37 is that we get to a point where you can make
0:09:40 scarless integrations of genetic material into the DNA.
0:09:42 So it’s less traumatic in that regard.
0:09:44 So if you can do that more precisely,
0:09:46 there’s less scar tissue that hopefully is, you know,
0:09:48 a better intervention altogether.
0:09:50 So that holds great promise from a potential
0:09:53 for future therapeutics based on this type of technology.
0:09:55 I think the other thing that’s worth noting
0:09:57 is that in a relatively short period of time,
0:10:01 the programmability of these kinds of systems
0:10:04 has improved dramatically.
0:10:06 So the kinds of things that we could do,
0:10:09 that we can do now with, you know, with CRISPR
0:10:11 based on these kinds of advances
0:10:15 gives us a very broad repertoire and toolkit to work with,
0:10:17 whether it’s for therapeutic applications
0:10:18 or for diagnostic applications
0:10:20 or for any other number of things.
0:10:25 When most people think about CRISPR developing CRISPR
0:10:26 for human health,
0:10:28 they’re thinking about therapeutic applications.
0:10:31 But the reality is there’s also a lot of potential
0:10:32 for diagnostic applications.
0:10:34 So going back to the original discovery
0:10:35 of the CRISPR-Cas system,
0:10:38 this was essentially the memory banker immune system
0:10:40 for bacteria to remember what viruses
0:10:41 had attacked it before
0:10:43 so they could protect themselves going forward.
0:10:47 And the way it does that is by essentially cutting
0:10:49 that viral genetic material.
0:10:52 So it’s ineffective essentially basically, you know,
0:10:56 cutting it off at its Achilles heel, so to speak.
0:10:57 And so as you can imagine,
0:11:00 if you’re hijacking that capability
0:11:01 for therapeutic purposes,
0:11:03 you could also hijack that capability
0:11:05 for diagnostic purposes.
0:11:07 And a way that that could potentially work, for example,
0:11:12 is if you know what bacteria or what virus
0:11:15 or even what, you know, mutation in DNA you’re looking for
0:11:18 in say a human sample, a blood sample
0:11:20 or urine sample or anything like that.
0:11:24 If it’s present, it will get cut by the right CAS system.
0:11:27 You program the CRISPR-Cas system to say,
0:11:31 these are the sequences of genetic material
0:11:33 that I am looking for in the sample.
0:11:34 This is basically the search engine.
0:11:36 Like you’re doing essentially a Google search.
0:11:38 – And you basically just look for the kill switch
0:11:40 to have been activated.
0:11:41 – You just look for the identifier.
0:11:42 So you basically say,
0:11:44 if I want to look in this patient’s sample,
0:11:47 let’s say I want to look for a specific bacteria
0:11:48 or a specific virus
0:11:51 or specific genetic mutation associated with disease,
0:11:53 you can say, if you find the presence
0:11:55 of any one of these sequences,
0:11:56 those are almost like the search terms,
0:11:58 cut them and when you cut them,
0:12:00 you can essentially engineer the system
0:12:02 to send out some sort of a reporter,
0:12:04 a reporter, usually it’s a visual marker.
0:12:06 And so basically if it lights up,
0:12:08 it’s because the CRISPR-Cas system cut the DNA
0:12:10 you told it to look for.
0:12:12 So that has a potential diagnostic application
0:12:13 and you could run that diagnostic
0:12:15 essentially without a lab, right?
0:12:16 ‘Cause it just happens with the biology.
0:12:19 So a whole other kind of new tool, essentially.
0:12:21 – Yeah, and I think the diagnostic applications
0:12:23 for these kinds of technologies
0:12:26 are actually pretty intriguing
0:12:28 because most of the way we do diagnostics
0:12:33 is based on developing some very specific biological
0:12:34 or chemical assays.
0:12:36 So look for something and if so,
0:12:38 have the reaction take place
0:12:40 and one that I can visualize and quantify
0:12:42 or quantitate in some way.
0:12:44 But here you’re just basically letting the biology
0:12:45 do the work for you.
0:12:47 In the CRISPR toolkit,
0:12:51 a lot of the initial applications was using
0:12:53 CRISPR-Cas9, this one nucleus.
0:12:56 And actually the diagnostic application
0:12:57 that Jorge was talking about
0:12:59 was actually using these other nucleas
0:13:01 known as Cas13 and Cas12.
0:13:04 And so all these different CRISPR proteins,
0:13:08 Cas9, 12, 13, X, Y, that we’re continuing to discover
0:13:11 has all different fundamental applications, right?
0:13:12 Even fundamentally changing
0:13:14 what these CRISPR nucleases even do.
0:13:15 It doesn’t even cut anymore.
0:13:17 It can do scarless editing.
0:13:20 And then we can even add different applications on it.
0:13:22 There’s new applications adding,
0:13:24 deaminase is just to do base editing.
0:13:28 So we can really do single base pair resolution editing.
0:13:30 There’s really the final frontier of precision
0:13:32 in terms of genomic modification.
0:13:34 And I think what’s really important is that
0:13:36 we’ve really seen this shift from
0:13:38 when it became this random bespoke science
0:13:40 and really turning into full-fledged,
0:13:42 modified engineering tool.
0:13:44 And this paper that we talk about here
0:13:47 is not only a great representation
0:13:49 of this engineering biology thesis,
0:13:53 but also a pretty huge potential step change
0:13:54 for the field as a whole.
0:13:56 – You can program this to turn genes up and down
0:13:58 as opposed to just editing them.
0:14:01 There’s even work that’s ongoing to use this technology
0:14:03 to image DNA directly,
0:14:04 which is a pretty remarkable thing
0:14:07 because since this is acting locally on DNA,
0:14:10 you can add all kinds of agents to make it imageable.
0:14:12 So therefore, you can observe chromatin
0:14:14 or genome structure directly.
0:14:16 So there’s a lot that can be done with this technology,
0:14:20 and you hear the old adage about the pickaxes for the gold.
0:14:22 And with these toolkits,
0:14:25 I mean, we are quite literally panning for gold here.
0:14:28 I mean, where these things get found,
0:14:31 they’re found in soil and in ocean vents.
0:14:32 – New York City subways.
0:14:34 – The New York City subway.
0:14:37 So these people are quite literally looking in nature
0:14:39 because nature has ingenious ways
0:14:41 to do a lot of the things that we’re trying to do
0:14:45 from an engineering biology or programmable biology standpoint.
0:14:50 And so I think it’s a remarkable moment to take pause
0:14:53 and see how far this technology has come
0:14:55 in a relatively short period of time.
0:14:58 This generation’s recombinant DNA or restriction enzymes
0:15:01 that really gave rise to the biotechnology industry.
0:15:03 I think this tool kit, this CRISPR tool kit,
0:15:06 as we’re describing it and discussing it,
0:15:07 represents sort of the next frontier
0:15:10 for what will happen in biology.
0:15:13 So an incredible development of precision
0:15:15 in what the tools can do and at the same time,
0:15:17 a huge expansion of what that will enable us
0:15:18 to do going forward.
0:15:20 Thank you guys so much for joining us.
0:15:23 Should I say on the A16Z Journal Club?
0:15:23 – No, no, please don’t say that.
0:15:24 – Yeah, okay.
0:15:34 [BLANK_AUDIO]
0:00:04 of the A16Z BioJournal Club.
0:00:05 I’m Hannah.
0:00:08 Our goal here is to take an interesting new research paper
0:00:10 in the field and talk about why it’s cool,
0:00:12 break down a little of the science involved,
0:00:14 and consider what the implications of this research
0:00:15 for industry might be.
0:00:17 So in our first take, A16Z General Partner
0:00:21 on the Bio Fund Jorge Conde and Deal Team Partner Andy Tran
0:00:24 chat with me about two papers recently published.
0:00:27 The first transposon encoded CRISPR/CAS systems
0:00:30 direct RNA guided DNA integration
0:00:33 was published by a group under Samuel H. Sternberg
0:00:36 at Columbia in nature of June 2019.
0:00:39 The second is RNA guided DNA insertion
0:00:42 with CRISPR associated transposases
0:00:45 with a team under Feng Zhang from the Broad Institute
0:00:48 published in science also in June 2019.
0:00:50 We talk about what these papers are all about
0:00:53 in the field of CRISPR development and beyond.
0:00:54 This mini podcast is available
0:00:57 as part of our new A16Z Bio Newsletter.
0:01:00 So if you like it and you want to hear more or read more,
0:01:05 please sign up for the newsletter at a16z.com/subscribe.
0:01:07 Let’s talk about what specifically is happening here.
0:01:10 What does, what a transposon encoded CRISPR/CAS system
0:01:13 direct RNA guided DNA integration?
0:01:14 Like, what does that actually mean?
0:01:16 Can you help me understand what was the interesting science
0:01:17 that was going on here?
0:01:18 – Yeah, so what’s really interesting
0:01:19 in the field of CRISPR lately,
0:01:22 and actually a few papers that came out in the recent times
0:01:26 developed a way to basically use these transposon machinery
0:01:28 inside the cell and use CRISPR to direct it
0:01:30 into a specific place in the genome
0:01:34 and really edit the genome without cutting it open at all.
0:01:36 So you can think of it as this scarless type
0:01:37 of genetic modification.
0:01:39 – Essentially what a transposon is,
0:01:42 is this sort of phenomenon that’s been observed
0:01:44 of where you have sort of these genes
0:01:46 that jump into the genome.
0:01:47 – It’s kind of mysterious what the jumping
0:01:48 is really used for.
0:01:50 People surmise that, you know, potentially, you know,
0:01:54 it helps, you know, the cells and organism evolved in general.
0:01:56 So what this paper shows is to utilize
0:01:58 this CRISPR machinery known as Cascade,
0:02:02 and it’s formed by, you know, CASS6, CASS7, CASS8 proteins
0:02:04 to really insert genes into the genome.
0:02:08 And this Cascade protein is directed to the chromosome
0:02:11 by using guided RNA, you know, CRISPR machinery,
0:02:15 and it then binds to this transposase-associated protein,
0:02:18 TNIQ, and it allows them to recruit
0:02:20 these transposable elements and then effectively integrate
0:02:22 the gene into the genome.
0:02:25 And this is super powerful because now we’re able to,
0:02:27 you know, add genes in the genome directly
0:02:29 and precisely without cutting it open.
0:02:32 It’s a scarless way to modify the genome.
0:02:35 – So in some ways, this is almost like if CRISPR
0:02:38 is about surgically inserting or editing DNA,
0:02:41 this is almost in many ways like plastic surgery, right?
0:02:42 It’s scarless. – Ah, right, right.
0:02:45 – It doesn’t leave a mark and therefore in some ways
0:02:48 it’s less risky from an intervention standpoint
0:02:49 on the genome side.
0:02:51 – What it really boils down to is that
0:02:53 this machinery utilizes a way
0:02:56 to really efficiently integrate genes into the cell,
0:02:58 into the genome specifically,
0:02:59 without having to cut it open at all.
0:03:02 And to the metaphor of the surgery,
0:03:04 this is really important in the whole context
0:03:06 of gene therapy as a whole, right?
0:03:08 ‘Cause when we started off in gene therapy,
0:03:09 we had these random integration
0:03:12 of these trans genes into the cell.
0:03:15 And, you know, this was a more stochastic process.
0:03:17 So think of it almost as, you know,
0:03:20 the arrival of this paper and papers like it
0:03:24 are showing us that we’ve gotten to a point
0:03:28 where we have a fully programmable ability
0:03:32 to integrate new genes or new DNA into a genome
0:03:34 without having to first open up
0:03:36 or break apart the DNA to do that.
0:03:38 – So let’s go back and actually situate it
0:03:40 into the development of the science,
0:03:42 what it represents for where we’ve gotten
0:03:44 from where we began.
0:03:45 – Yeah, so if you want to do the really,
0:03:47 the fast forward montage version of this.
0:03:49 – Yeah, the 80s montage.
0:03:51 – Yeah, exactly, so I’m sure you’ll put
0:03:52 in the pop music behind it.
0:03:55 – Right, yeah, and the overalls in the paintbrushes.
0:03:56 – He always started in the 60s.
0:03:57 – In the time motion.
0:03:58 – Yeah, let’s go.
0:04:00 – But look, I mean, if you go all the way back,
0:04:02 you know, one of the earliest sort of technologies
0:04:04 that came to the fore was the discovery
0:04:05 of something called the restriction enzyme.
0:04:07 And the restriction enzyme was this ability
0:04:10 to take this protein that could cut DNA
0:04:12 at these predetermined sites,
0:04:15 essentially open up the DNA,
0:04:19 and then you could introduce new genetic material,
0:04:20 and it would eventually integrate randomly,
0:04:23 but it would integrate into that DNA.
0:04:25 That’s what gave us the ability to do
0:04:27 or recombinant DNA technology,
0:04:29 which gives rise to the entire biotech field.
0:04:32 One of the earliest applications of biotechnology is
0:04:35 getting bacterial systems to integrate human insulin
0:04:38 so that we could coax bacteria to make that drug
0:04:41 or human insulin on our behalf, of course, to treat diabetics.
0:04:43 So that starts the whole field.
0:04:45 Now, you know, if you sort of move forward,
0:04:46 the objective always has been,
0:04:51 can you cure disease by repairing
0:04:55 or replacing what’s broken in DNA?
0:04:58 And so the whole field of gene therapy arises
0:04:59 with this idea that, you know,
0:05:02 can we introduce a corrected version
0:05:05 of a non-functional gene in a patient
0:05:06 and have it do the job
0:05:08 that the non-functional gene cannot do?
0:05:12 The first version was just put that gene
0:05:16 into a viral vector, into almost like a delivery vehicle,
0:05:18 introduce that into patient cells,
0:05:20 that gets taken in by the cells,
0:05:22 and the gene just starts to sort of do its job.
0:05:23 It integrates randomly in the genome,
0:05:24 but it does the job it needs to do.
0:05:26 Hopefully it integrates, or maybe it doesn’t,
0:05:28 but it just does the job to compensate
0:05:30 for some mutated gene.
0:05:33 Yeah, so it’s basically almost a parallel support system
0:05:35 that the cell has.
0:05:37 We just had the first gene therapies approved
0:05:39 over the course of the last couple of years.
0:05:42 If you look at the spark therapy, gene therapy drug for,
0:05:44 this rare inherited form of blindness.
0:05:47 And so that was one big advance forward.
0:05:49 Now, that is introducing a full gene
0:05:51 and just hoping it gets taken up by the cell.
0:05:52 Just kind of throw it in the mix.
0:05:54 Yeah, throw it in the mix and it has its own risk.
0:05:56 The original discovery of CRISPR-Cas9,
0:05:59 that system, the way that system works
0:06:02 is by making what’s called a double-stranded break
0:06:03 in the DNA molecule.
0:06:04 So if you think of, you know,
0:06:07 we all remember DNA from high school biology
0:06:10 as sort of the beautiful double helix.
0:06:12 So imagine sort of cutting that double helix in two
0:06:14 and making an end of it, right?
0:06:17 And then, you know, and then putting it back together.
0:06:18 That’s not riskless, right?
0:06:20 And by the way, it’s very well known
0:06:22 and documented that one of the big setbacks
0:06:25 that the gene therapy field had a couple of decades ago
0:06:27 was when they ran a clinical trial
0:06:28 at the University of Pennsylvania,
0:06:31 there was a patient named Jesse Gelsinger
0:06:32 who died after receiving the therapy
0:06:34 just because there’s a lot of risk associated
0:06:37 with introducing, you know, a viral capsid with a gene
0:06:39 into a cell system, into human being
0:06:41 where you could have a catastrophic result
0:06:41 and that patient died.
0:06:44 And that actually put a big pause on how we thought
0:06:47 about developing gene therapies for humans.
0:06:49 But that approach will have
0:06:51 and does have therapeutic potential.
0:06:52 And there are several companies
0:06:56 that are pursuing developing CRISPR-Cas9-based therapeutics.
0:06:58 As that advanced in parallel,
0:07:02 we started to see other gene or genome editing technologies
0:07:03 come to the fore.
0:07:06 The first one was one known as zinc finger nucleases,
0:07:08 which really didn’t have as much uptake
0:07:10 as one would expect
0:07:13 because it’s just very hard to deal with these proteins.
0:07:16 – How zinc fingers work is that you actually use these proteins
0:07:18 to bind onto DNA sequences.
0:07:21 And every time you want to iterate to find a new target,
0:07:22 cost tens of thousands of dollars
0:07:24 in a few months to develop one protein.
0:07:26 – So it’s enormously expensive and labor intensive.
0:07:27 – Exactly.
0:07:28 So it never really caught on like wildfire
0:07:30 in the community, right?
0:07:31 – It’s a very bespoke process.
0:07:34 It’s one of the type of thing.
0:07:36 And then there were other technologies.
0:07:38 There was Talens,
0:07:40 which was a bit better than zinc finger nucleases,
0:07:45 but really the big sort of shift in the field
0:07:47 was the arrival of CRISPR.
0:07:49 – And so when scientists discovered CRISPR,
0:07:52 they noticed that it was just always constant evolutionary
0:07:55 warfare between bacteriophages and bacteria
0:07:56 for billions of years.
0:07:58 – Bacteriophages are viruses.
0:07:58 – Yes.
0:08:03 – And so when these viruses inject their viral genome
0:08:04 into the bacteria,
0:08:06 you can think of it as the bacterial immune system,
0:08:10 whereas they’re able to sense these little snippets
0:08:11 of viral genome,
0:08:13 they would create a vaccination card from it,
0:08:14 and then they’ll put it back into this,
0:08:16 what is known as this CRISPR array.
0:08:18 And this would be like a vaccine card
0:08:20 or a vaccine database, if you will.
0:08:22 So every time it recognizes that foreign viral sequence.
0:08:23 – Right, then it knows what to do.
0:08:25 – It would know how to snip it away, right?
0:08:27 And then people have hijacked this machinery.
0:08:31 So what if we can program this outside of bacteria
0:08:32 and use it in human cells
0:08:35 and program it to sense not viral DNA,
0:08:38 but specific targets in the human genome.
0:08:42 And then then we can program and effectively target
0:08:44 anywhere we want in the cell, right?
0:08:46 – So now bring us forward to today.
0:08:48 So is this new development,
0:08:50 does it mean that the therapeutic potentials
0:08:52 are essentially less risky?
0:08:54 Or are there new possibilities
0:08:56 that we haven’t been able to do before?
0:08:56 Or both?
0:08:59 – Basically, you know, it’s really powerful
0:09:01 because when we talk about the first gen of gene therapy
0:09:03 to the second gen of CRISPR,
0:09:05 this paper really represents this third wave
0:09:07 in this scarless genomic editing.
0:09:10 This is basically genomic surgery at its finest, right?
0:09:13 You know, when we think about laparoscopic surgery
0:09:15 and all these advanced surgery tools,
0:09:16 we want to have, you know,
0:09:19 basically a scarless methodology of doing surgery.
0:09:21 This is a way to really cleanly integrate,
0:09:23 you know, genomic segments into the cell
0:09:25 without even touching, right?
0:09:28 And then this also represents an even broader tool
0:09:31 of, you know, the entire, you know, genomic toolkit landscape.
0:09:33 – The real promise on the near term side
0:09:37 is that we get to a point where you can make
0:09:40 scarless integrations of genetic material into the DNA.
0:09:42 So it’s less traumatic in that regard.
0:09:44 So if you can do that more precisely,
0:09:46 there’s less scar tissue that hopefully is, you know,
0:09:48 a better intervention altogether.
0:09:50 So that holds great promise from a potential
0:09:53 for future therapeutics based on this type of technology.
0:09:55 I think the other thing that’s worth noting
0:09:57 is that in a relatively short period of time,
0:10:01 the programmability of these kinds of systems
0:10:04 has improved dramatically.
0:10:06 So the kinds of things that we could do,
0:10:09 that we can do now with, you know, with CRISPR
0:10:11 based on these kinds of advances
0:10:15 gives us a very broad repertoire and toolkit to work with,
0:10:17 whether it’s for therapeutic applications
0:10:18 or for diagnostic applications
0:10:20 or for any other number of things.
0:10:25 When most people think about CRISPR developing CRISPR
0:10:26 for human health,
0:10:28 they’re thinking about therapeutic applications.
0:10:31 But the reality is there’s also a lot of potential
0:10:32 for diagnostic applications.
0:10:34 So going back to the original discovery
0:10:35 of the CRISPR-Cas system,
0:10:38 this was essentially the memory banker immune system
0:10:40 for bacteria to remember what viruses
0:10:41 had attacked it before
0:10:43 so they could protect themselves going forward.
0:10:47 And the way it does that is by essentially cutting
0:10:49 that viral genetic material.
0:10:52 So it’s ineffective essentially basically, you know,
0:10:56 cutting it off at its Achilles heel, so to speak.
0:10:57 And so as you can imagine,
0:11:00 if you’re hijacking that capability
0:11:01 for therapeutic purposes,
0:11:03 you could also hijack that capability
0:11:05 for diagnostic purposes.
0:11:07 And a way that that could potentially work, for example,
0:11:12 is if you know what bacteria or what virus
0:11:15 or even what, you know, mutation in DNA you’re looking for
0:11:18 in say a human sample, a blood sample
0:11:20 or urine sample or anything like that.
0:11:24 If it’s present, it will get cut by the right CAS system.
0:11:27 You program the CRISPR-Cas system to say,
0:11:31 these are the sequences of genetic material
0:11:33 that I am looking for in the sample.
0:11:34 This is basically the search engine.
0:11:36 Like you’re doing essentially a Google search.
0:11:38 – And you basically just look for the kill switch
0:11:40 to have been activated.
0:11:41 – You just look for the identifier.
0:11:42 So you basically say,
0:11:44 if I want to look in this patient’s sample,
0:11:47 let’s say I want to look for a specific bacteria
0:11:48 or a specific virus
0:11:51 or specific genetic mutation associated with disease,
0:11:53 you can say, if you find the presence
0:11:55 of any one of these sequences,
0:11:56 those are almost like the search terms,
0:11:58 cut them and when you cut them,
0:12:00 you can essentially engineer the system
0:12:02 to send out some sort of a reporter,
0:12:04 a reporter, usually it’s a visual marker.
0:12:06 And so basically if it lights up,
0:12:08 it’s because the CRISPR-Cas system cut the DNA
0:12:10 you told it to look for.
0:12:12 So that has a potential diagnostic application
0:12:13 and you could run that diagnostic
0:12:15 essentially without a lab, right?
0:12:16 ‘Cause it just happens with the biology.
0:12:19 So a whole other kind of new tool, essentially.
0:12:21 – Yeah, and I think the diagnostic applications
0:12:23 for these kinds of technologies
0:12:26 are actually pretty intriguing
0:12:28 because most of the way we do diagnostics
0:12:33 is based on developing some very specific biological
0:12:34 or chemical assays.
0:12:36 So look for something and if so,
0:12:38 have the reaction take place
0:12:40 and one that I can visualize and quantify
0:12:42 or quantitate in some way.
0:12:44 But here you’re just basically letting the biology
0:12:45 do the work for you.
0:12:47 In the CRISPR toolkit,
0:12:51 a lot of the initial applications was using
0:12:53 CRISPR-Cas9, this one nucleus.
0:12:56 And actually the diagnostic application
0:12:57 that Jorge was talking about
0:12:59 was actually using these other nucleas
0:13:01 known as Cas13 and Cas12.
0:13:04 And so all these different CRISPR proteins,
0:13:08 Cas9, 12, 13, X, Y, that we’re continuing to discover
0:13:11 has all different fundamental applications, right?
0:13:12 Even fundamentally changing
0:13:14 what these CRISPR nucleases even do.
0:13:15 It doesn’t even cut anymore.
0:13:17 It can do scarless editing.
0:13:20 And then we can even add different applications on it.
0:13:22 There’s new applications adding,
0:13:24 deaminase is just to do base editing.
0:13:28 So we can really do single base pair resolution editing.
0:13:30 There’s really the final frontier of precision
0:13:32 in terms of genomic modification.
0:13:34 And I think what’s really important is that
0:13:36 we’ve really seen this shift from
0:13:38 when it became this random bespoke science
0:13:40 and really turning into full-fledged,
0:13:42 modified engineering tool.
0:13:44 And this paper that we talk about here
0:13:47 is not only a great representation
0:13:49 of this engineering biology thesis,
0:13:53 but also a pretty huge potential step change
0:13:54 for the field as a whole.
0:13:56 – You can program this to turn genes up and down
0:13:58 as opposed to just editing them.
0:14:01 There’s even work that’s ongoing to use this technology
0:14:03 to image DNA directly,
0:14:04 which is a pretty remarkable thing
0:14:07 because since this is acting locally on DNA,
0:14:10 you can add all kinds of agents to make it imageable.
0:14:12 So therefore, you can observe chromatin
0:14:14 or genome structure directly.
0:14:16 So there’s a lot that can be done with this technology,
0:14:20 and you hear the old adage about the pickaxes for the gold.
0:14:22 And with these toolkits,
0:14:25 I mean, we are quite literally panning for gold here.
0:14:28 I mean, where these things get found,
0:14:31 they’re found in soil and in ocean vents.
0:14:32 – New York City subways.
0:14:34 – The New York City subway.
0:14:37 So these people are quite literally looking in nature
0:14:39 because nature has ingenious ways
0:14:41 to do a lot of the things that we’re trying to do
0:14:45 from an engineering biology or programmable biology standpoint.
0:14:50 And so I think it’s a remarkable moment to take pause
0:14:53 and see how far this technology has come
0:14:55 in a relatively short period of time.
0:14:58 This generation’s recombinant DNA or restriction enzymes
0:15:01 that really gave rise to the biotechnology industry.
0:15:03 I think this tool kit, this CRISPR tool kit,
0:15:06 as we’re describing it and discussing it,
0:15:07 represents sort of the next frontier
0:15:10 for what will happen in biology.
0:15:13 So an incredible development of precision
0:15:15 in what the tools can do and at the same time,
0:15:17 a huge expansion of what that will enable us
0:15:18 to do going forward.
0:15:20 Thank you guys so much for joining us.
0:15:23 Should I say on the A16Z Journal Club?
0:15:23 – No, no, please don’t say that.
0:15:24 – Yeah, okay.
0:15:34 [BLANK_AUDIO]
¿Y si cada escéptico de doce años que pregunta “¿para qué voy a usar esto?” tuviera razón en lo esencial sobre la escuela? El economista Bryan Caplan sostiene que nuestro sistema educativo funciona menos como un lugar para aprender habilidades útiles y más como un dispositivo de señalización elaborado y costoso. En su visión, el valor principal de un título no es lo que aprendes, sino lo que comunica a los empleadores sobre tu inteligencia, responsabilidad y conformidad. Si bien esto hace de la educación una inversión personal racional, crea un problema social de inflación de credenciales, donde se requieren títulos cada vez más costosos para los mismos trabajos, sin un aumento correspondiente en la productividad real.
Caplan profundiza en la evidencia que respalda este modelo de señalización, señalando que los adultos retienen sorprendentemente poco del conocimiento académico que se les enseñó —desde historia y ciencia hasta idiomas extranjeros—. Cuestiona la defensa común de que las escuelas enseñan “cómo pensar”, citando investigaciones psicológicas que muestran que la transferencia del aprendizaje entre dominios es notoriamente débil. La conversación explora las sombrías implicaciones: una enorme mala asignación de fondos públicos, una carrera sin fin de demandas educativas crecientes y un sistema que fracasa con dos tercios de los estudiantes que siguen una trayectoria universitaria a pesar de beneficios improbables.
La discusión luego pasa a las soluciones potenciales, donde surge el idealismo de Caplan. Aboga por un cambio drástico hacia la educación vocacional y los aprendizajes, que se centran en impartir habilidades concretas y prácticas con un valor social más claro. Es profundamente escéptico de simplemente inyectar más dinero al sistema actual o confiar en la elección de escuela para revolucionar los resultados, ya que cree que los incentivos fundamentales siguen desalineados hacia la señalización. En última instancia, sugiere de manera provocativa que una verdadera mejora podría requerir una forma de “austeridad educativa” para romper el ciclo de inflación de credenciales, junto con una separación de la escuela y el estado para fomentar una innovación real.
Perspectivas Sorprendentes
- El Plan de Estudios Olvidado: A pesar de años de instrucción, el conocimiento promedio de los adultos en materias como historia, gobierno y ciencia es “tan cercano a cero” que no puede explicar plausiblemente la prima salarial de un título.
- El Mito de “Aprender a Aprender”: La investigación en psicología educativa sugiere firmemente que la transferencia de habilidades como el pensamiento crítico del aula a problemas del mundo real es mínima a menos que se solicite explícitamente, desmintiendo una justificación común para una amplia educación en artes liberales.
- La Señalización Explica las Trampas: Caplan plantea que el modelo de señalización explica lógicamente las trampas estudiantiles —es un intento de imitar los rasgos (como la responsabilidad) de un estudiante de alto rendimiento para obtener las mismas recompensas en el mercado laboral, lo que solo funciona si la mayoría de las personas que obtienen calificaciones altas no hacen trampa.
- El Vínculo Débil de la Educación con el Desarrollo Nacional: Los datos internacionales sugieren que, aunque la educación aumenta enormemente los ingresos de un individuo en países en desarrollo, tiene un efecto mucho menor en el crecimiento económico nacional, alineándose con la visión de que la educación a menudo señala rasgos preexistentes en lugar de crear nuevo capital humano.
Conclusiones Prácticas
- Considera Seriamente las Trayectorias Vocacionales: Para estudiantes desinteresados por la academia tradicional, la educación vocacional y los aprendizajes pueden proporcionar habilidades valiosas, tasas de finalización más altas y sólidos retornos en el mercado laboral sin la carrera armamentista de señalización.
- Busca Habilidades, No Solo Credenciales: Al invertir en educación, prioriza conscientemente adquirir habilidades prácticas demostrables sobre simplemente coleccionar credenciales, especialmente en campos donde portafolios o certificaciones pueden mostrar la habilidad directamente.
- Aplica “Piel en el Juego” a las Creencias: Adopta el hábito de Caplan de estar abierto a apostar por tus creencias; poner incluso una pequeña cantidad de dinero en juego obliga a una evaluación más disciplinada, probabilística y racional de tus propias opiniones.
- Expón a los Jóvenes a Opciones Realistas: En lugar de una exposición académica genérica, aboga por programas que permitan a los jóvenes probar una amplia gama de trabajos y oficios del mundo real para descubrir intereses y aptitudes genuinas antes.
E se todo adolescente cético de 12 anos perguntando “quando vou usar isso na vida?” estivesse essencialmente certo sobre a escola? O economista Bryan Caplan argumenta que nosso sistema educacional funciona menos como um lugar para aprender habilidades úteis e mais como um dispositivo de sinalização elaborado e custoso. Em sua visão, o valor principal de um diploma não está no que você aprende, mas no que ele comunica aos empregadores sobre sua inteligência, diligência e conformidade. Embora isso torne a educação um investimento pessoal racional, cria um problema social de inflação de credenciais, onde diplomas cada vez mais caros são exigidos para os mesmos empregos, sem um aumento correspondente na produtividade real.
Caplan mergulha nas evidências que apoiam esse modelo de sinalização, apontando que os adultos retêm surpreendentemente pouco do conhecimento acadêmico que lhes foi ensinado—da história e ciência aos idiomas estrangeiros. Ele desafia a defesa comum de que as escolas ensinam “como pensar”, citando pesquisas psicológicas que mostram que a transferência de aprendizagem entre domínios é notoriamente fraca. A conversa explora as graves implicações: uma enorme má alocação de fundos públicos, uma esteira de demandas educacionais crescentes e um sistema que falha com dois terços dos estudantes mantidos no caminho da faculdade apesar de benefícios improváveis.
A discussão então se desloca para possíveis soluções, onde o idealismo de Caplan emerge. Ele defende uma mudança drástica para a educação vocacional e os aprendizados, que se concentram em transmitir habilidades concretas e práticas com valor social mais claro. Ele é profundamente cético quanto a simplesmente injetar mais dinheiro no sistema atual ou contar com a escolha escolar para revolucionar os resultados, pois acredita que os incentivos fundamentais continuam desalinhados com a sinalização. Por fim, ele sugere provocativamente que uma verdadeira melhoria pode exigir uma forma de “austeridade educacional” para romper o ciclo da inflação de credenciais, juntamente com uma separação entre escola e Estado para fomentar a inovação real.
### Insights Surpreendentes
– **O Currículo Esquecido:** Apesar de anos de instrução, o conhecimento médio dos adultos em matérias como história, governo e ciência está “tão próximo de zero” que não pode explicar plausivelmente o prêmio salarial de um diploma.
– **O Mito de “Aprender a Aprender”:** Pesquisas em psicologia educacional sugerem fortemente que a transferência de habilidades como o pensamento crítico da sala de aula para problemas do mundo real é mínima, a menos que explicitamente solicitada, desmascarando uma justificativa comum para a ampla educação em artes liberais.
– **A Sinalização Explica a Cola:** Caplan postula que o modelo de sinalização explica logicamente a cola dos estudantes—é uma tentativa de personificar as características (como a diligência) de um aluno de alto desempenho para obter as mesmas recompensas no mercado de trabalho, o que só funciona se a maioria das pessoas tirando notas altas *não estiver* colando.
– **A Fraca Ligação da Educação com o Desenvolvimento Nacional:** Dados internacionais sugerem que, embora a educação aumente bastante a renda de um *indivíduo* em países em desenvolvimento, ela tem um efeito muito menor no crescimento econômico *nacional*, alinhando-se com a visão de que a educação muitas vezes sinaliza características pré-existentes em vez de criar novo capital humano.
### Conclusões Práticas
– **Considere Caminhos Vocacionais a Sério:** Para estudantes desengajados com o acadêmico tradicional, a educação vocacional e os aprendizados podem fornecer habilidades valiosas, taxas de conclusão mais altas e fortes retornos no mercado de trabalho sem a corrida armamentista de sinalização.
– **Busque Habilidades, Não Apenas Credenciais:** Ao investir em educação, priorize conscientemente a aquisição de habilidades práticas demonstráveis, em vez de apenas colecionar credenciais, especialmente em áreas onde portfólios ou certificações podem mostrar a habilidade diretamente.
– **Aplique “Pele no Jogo” às Crenças:** Adote o hábito de Caplan de estar aberto a apostas em suas crenças; colocar até uma pequena quantia em jogo força uma avaliação mais disciplinada, probabilística e racional de suas próprias opiniões.
– **Exponha os Jovens a Opções Realistas:** Em vez de uma exposição acadêmica genérica, defenda programas que permitam aos jovens experimentar uma ampla gama de empregos e ofícios do mundo real para descobrir interesses e aptidões genuínos mais cedo.
Caplan mergulha nas evidências que apoiam esse modelo de sinalização, apontando que os adultos retêm surpreendentemente pouco do conhecimento acadêmico que lhes foi ensinado—da história e ciência aos idiomas estrangeiros. Ele desafia a defesa comum de que as escolas ensinam “como pensar”, citando pesquisas psicológicas que mostram que a transferência de aprendizagem entre domínios é notoriamente fraca. A conversa explora as graves implicações: uma enorme má alocação de fundos públicos, uma esteira de demandas educacionais crescentes e um sistema que falha com dois terços dos estudantes mantidos no caminho da faculdade apesar de benefícios improváveis.
A discussão então se desloca para possíveis soluções, onde o idealismo de Caplan emerge. Ele defende uma mudança drástica para a educação vocacional e os aprendizados, que se concentram em transmitir habilidades concretas e práticas com valor social mais claro. Ele é profundamente cético quanto a simplesmente injetar mais dinheiro no sistema atual ou contar com a escolha escolar para revolucionar os resultados, pois acredita que os incentivos fundamentais continuam desalinhados com a sinalização. Por fim, ele sugere provocativamente que uma verdadeira melhoria pode exigir uma forma de “austeridade educacional” para romper o ciclo da inflação de credenciais, juntamente com uma separação entre escola e Estado para fomentar a inovação real.
### Insights Surpreendentes
– **O Currículo Esquecido:** Apesar de anos de instrução, o conhecimento médio dos adultos em matérias como história, governo e ciência está “tão próximo de zero” que não pode explicar plausivelmente o prêmio salarial de um diploma.
– **O Mito de “Aprender a Aprender”:** Pesquisas em psicologia educacional sugerem fortemente que a transferência de habilidades como o pensamento crítico da sala de aula para problemas do mundo real é mínima, a menos que explicitamente solicitada, desmascarando uma justificativa comum para a ampla educação em artes liberais.
– **A Sinalização Explica a Cola:** Caplan postula que o modelo de sinalização explica logicamente a cola dos estudantes—é uma tentativa de personificar as características (como a diligência) de um aluno de alto desempenho para obter as mesmas recompensas no mercado de trabalho, o que só funciona se a maioria das pessoas tirando notas altas *não estiver* colando.
– **A Fraca Ligação da Educação com o Desenvolvimento Nacional:** Dados internacionais sugerem que, embora a educação aumente bastante a renda de um *indivíduo* em países em desenvolvimento, ela tem um efeito muito menor no crescimento econômico *nacional*, alinhando-se com a visão de que a educação muitas vezes sinaliza características pré-existentes em vez de criar novo capital humano.
### Conclusões Práticas
– **Considere Caminhos Vocacionais a Sério:** Para estudantes desengajados com o acadêmico tradicional, a educação vocacional e os aprendizados podem fornecer habilidades valiosas, taxas de conclusão mais altas e fortes retornos no mercado de trabalho sem a corrida armamentista de sinalização.
– **Busque Habilidades, Não Apenas Credenciais:** Ao investir em educação, priorize conscientemente a aquisição de habilidades práticas demonstráveis, em vez de apenas colecionar credenciais, especialmente em áreas onde portfólios ou certificações podem mostrar a habilidade diretamente.
– **Aplique “Pele no Jogo” às Crenças:** Adote o hábito de Caplan de estar aberto a apostas em suas crenças; colocar até uma pequena quantia em jogo força uma avaliação mais disciplinada, probabilística e racional de suas próprias opiniões.
– **Exponha os Jovens a Opções Realistas:** Em vez de uma exposição acadêmica genérica, defenda programas que permitam aos jovens experimentar uma ampla gama de empregos e ofícios do mundo real para descobrir interesses e aptidões genuínos mais cedo.
Two recent scientific journal papers show what’s possible when CRISPR moves from cutting DNA tool to a full-fledged platform — expanding its toolkit for medicine across R&D, therapeutics, and diagnostics:
”Transposon-encoded CRISPR-Cas systems direct RNA-guided DNA integration” in Nature — by Sanne Klompe, Phuc Vo, Tyler Halpin-Healy, and Samuel Sternberg (of Columbia University)
”RNA-guided DNA insertion with CRISPR-associated transposases” in Science — by Jonathan Strecker, Alim Ladha, Zachary Gardner, Jonathan Schmid-burgk, Kira Makarova, Eugene Koonin, and Feng Zhang (of the Broad Institute)
What do these two papers — both about techniques for getting rid of the need to cut the genome to edit it — make possible going forward, given the ongoing shift of biology becoming more like engineering? Where are we in the wave of the genome engineering ”developer community” building on top of CRISPR with a constantly growing suite of programmable functionalities? a16z bio general partner Jorge Conde and bio deal team partner Andy Tran chat with Hanne Tidnam about these trends — and these two papers — in this short internal hallway-style conversation, part of our new a16z Journal Club series.
This podcast is also part of our new a16z bio newsletter, which you can sign up for at a16z.com/subscribe
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