Biology Is Eating the World
a16z.com
a16z.com
Biotech's dirty secret is that biology is Not engineering (it is still a discovery science)...but the music is still playing folks, dance on! (Sorry, it's early, I'm still pre caffeinated, and this topic always rankles me).
Taleb talks about caution all the time for a reason, complex systems are, indeed, complex.
The only way we can understand a complex system is by messing with it.
I'm only saying that we absolutely do need to poke complex systems to understand them, but we should do so responsibly. As the reply to the "playing god" saying goes: "we are as gods, we might as well get good at it".
In any case, I stand with what I meant: that complex systems should be treated with the highest degree of care, and with a "not-do-anything-by-default" mindset. The ramifications of interacting with it can, and surely will, be unpredictable.
It's an incredibly interesting field, but over-hyped, extremely hard and not particularly profitable.
Consider that orphan diseases are often not worked on due to either 1) not enough rich people have the disease or 2) only poor people have the disease so it's not worth it.
People in developing countries have serious diseases, but there's no money in it so no one is working on it (minus some efforts from people like Bill Gates).
Worst form of social darwinism EVER.
However, for those people that have or are going to get lung cancer or diabetes or other generally ( not always ) 'self-inflicted' diseases - should we just say - sorry - no treatment - it's you're own silly fault?
For heart disease - actually the best treatments are effectively preventative already - in cancer HPV vaccine is aimed at reducing cervical cancer - I've worked with the inventors of that.
In terms of 'whataboutery' of should you be spending money on rich peoples diseases ( whether self inflicted or not ), when you could save more lives in other countries with basic sanitation.
Well that's a whole different question - a question for collective action through governments or charity - not a question for commercial companies. Commercial companies have to find people able to pay for what they do ( which could be governments or charities ).
Personally I don't see why it needs to be either/or - ie why we can't we work on both cure's for cancer and provide clean water?
Returns to venture investments in biotech have outperformed tech in recent years, some new drugs are generating $5-10B within a few years of launch, and biopharma is the second biggest subsector of VC after software
Most people haven't heard of the top biotech VCs and companies because they don't blog or do podcasts but they are very good at what they do
And as another commenter said, some of these companies develop drugs that give people with cancer or infants with life threatening genetic disease many more years of healthy life and turn these conditions from death sentences to manageable chronic diseases
Nasdaq biotech 3y: +20%
Nasdaq tech 3y: +75%
Are you referring to Nasdaq as a whole when you say Nasdaq tech? The Nasdaq components aren't really representative of tech startups: https://www.nasdaq.com/market-activity/quotes/Nasdaq-100-Ind...
Biotech startups IPO at a much higher rate than tech startups and IPO on average 3 years after series a: https://www.baybridgebio.com/blog/ipo_2018_q12019.html
These IPOs give IRRs of 60% on average to series a investors: https://www.baybridgebio.com/blog/venture_returns_ipo.html
Biotech VC portfolios have low loss rates and greater portfolio concentration than tech VCs
There have been 10-15 new biotech unicorns a year since 2013 or so, on annual VC funding of $5-15B
There are plenty of other sources but i don't have access to them atm
Order / disorder transitions constitute a double edged sword. Indeed proteins, dna, rna possess crystalline structure. It may even require decades of microgravity incubation to unlock these oases of stability within the seas of chaos.
The great driver in Biotech is that results are immediately tangible. When we achieve the result that a 100 year old human preserves full memory recall and the neuroplasticity of a teenager. That will really be an accomplishment. One worth diverting even a small fraction of the current trillions spent on military hardware to hard tech bio R & D.
Synbio has been disappointing admittedly, but then engineering an organism is orders of magnitude more difficult than any engineering problem in existence. It is bottlenecked by the lack of a truly useful DNA synthesis platform. One day, when you can dial up a genome and have it into a cell in < 24 hours, and do it in a high throughput fashion, things will be very different. This will happen in under 10 years I think.
That points towards acceleration.
But the narrative that "biotech is becoming more like software" basically ignores the fact that engineering's impact in biotech is limited by our understanding of biology. The biggest challenge in drug discovery is that most targets arent good, and most disease models and in vitro systems are poorly correlated with clinical outcomes
You can engineer all you want, but if you are engineering a drug to optimally bind a target that isnt actually important for disease, all that engineering is wasted. Big pharma companies thought they could "solve" drug discovery with engineering / efficiency improvements in the early days of high throughput screening, but that only works if your biology is correct
The exciting thing about checkpoint inhibitors for cancer is that their targets are actually really important in cancer's strategy to avoid the immune system. The engineering work required is very impressive as well and built upon decades of innovation in that field, but the big pharma companies had a lot of that engineering expertise already I believe. Once they learned the importance of PD-1 / PD-L1 they could execute development campaigns using their existing infrastructure
TCRs are far from 'engineered' in any real sense, highly dependent on patient MHC and the specific neo-antigen, with no one able to rationally design from scratch a TCR.
Synbio's challenge is not necessarily engineering a genome faster. It's that no one knows what to make, per se. What should we print? We don't know how to design proteins or enzymes. Designing assays to measure a good vs bad design is often the rate-limiting step.
Your first paragraph glosses over all the work that goes into making a useful antibody candidate, a process of iterative modification to meet certain specifications. I don’t see a problem calling this engineering. Your point about market penetration as a judge of ‘engineeringness’ is also silly. There are antibody drug conjugates that serve a specific patient population very well, the fact they aren’t in your ‘top 10’ is irrelevant.
So what if CAR-T cells are struggling in the clinic? It is an entirely new treatment modality. There are people walking around who would be dead without it. You deride it because it isn’t an instant global panacea?
Your point about Synbio is also wrong. Leaders in the field just wrote a position piece in Science and genome writing was listed as one of the major challenges. You’re trying to tell me that George Church ‘doesn’t know what to build?’ Pure bunk.
Try to think of my argument as trying to add higher resolution to the debate, instead of being against/for your argument.
My main argument is against over-crediting what the software and algorithmic component of this is, precisely because I think it is too important. Another wider argument is are humans rationally designing anything / do we understand the wider design principles.
So let's go back to immunotherapy. Neither the target PD1/PDL1, nor the therapies themselves were enabled in particular by "in-silico" methods. Nivolumab and Pembrolizumab were not designed with much algorithmic or software input, but discovered through good old experiments / lab science/engineering. There is no human designer or algorithm in the world where if I give a target, they can rationally design an antibody. What we do is brute force + affinity selection / "directed evolution" to force nature come up with an answer still. We have no clue how to design it like one would design a bridge.
I think CAR-T is amazing technology - my point there remains: the therapies so far did not at use in-silico design of the Chimeric Antigen Receptor so far (the CAR part).. The low success in the clinic is precisely due to our inability to actually design these things properly. Similarly, neoantigen selection remains a big challenge due to lack of rational principles. A CAR is not too different from a TCR or Antibody, which we don't know how to rationally design.
I believe that genome writing is a major challenge. Again you are widely missing my point: Suppose you had a very cheap, abundant, perfect genome writer. What would we write? George, who was an advisor to my first company and kicked off our Hackathon, would be the first to admit that protein design is a major challenge.
Venter wrote an entire organism - and it was mycoplasma verbatim.
We are only able to copy nature or cajole it at the moment, because fundamentally we don't know how to design biology. It is because we don't really understand it very well, which makes it such an exciting time to be in the field.
None of this means these won't be done, or that teams around the world are not trying to do it this moment. There are amazing labs and companies working on these. What I am saying is more specific: Immunotherapy, CAR-T, or genome writing, in its first generation, as it exists, cannot be recruited as a showcase for computationally led, "in-silico" driven advances in biology.
I do believe this will change shortly.
>And that reshaping is a pretty lively process. Witness the news that Roche has had a major unexpected clinical failure with their antibody therapy Tencentriq (atezolizumab) in bladder cancer. This is another antibody targeting the PD-1/PD-L1 system, like Keytrude, Opdivo, etc. (in this case, it’s going after PD-L1 itself), and it was the first one approved against any form of bladder cancer. It’s also been approved for metastatic non-small cell lung cancer, which is a more traditional indication in this area, if by “tradition” we mean the last couple of years. The bladder cancer approval, though, was an accelerated one after just Phase II data, with re-evaluation to come after the Phase III numbers came in.
>Well, now they’re in, and the drug missed its primary endpoint. This not only puts Tencentriq’s continued approval for this indication in doubt, but it cannot be good news for the other companies in this space who are targeting it as well. Opdivo (nivolumab) from Bristol-Myers Squibb got approval in February, Pfizer and Merck KGaA’s Bavencio (avelumab) got a similar accelerated approval just a couple of days ago. Merck’s Keytruda (pembrolizumab), meanwhile, showed a good response Phase III (so much so that the trial was cut short), and is under review at the FDA, and there’s AstraZeneca’s entry in this area Imfinzi (durvalumab), too.
https://blogs.sciencemag.org/pipeline/archives/2015/11/17/ap...
>But a similarly targeted drug from Clovis Biotechnology, rociletinib (which is one of the recent acrylamide-containing irreversibly covalent kinase inhibitors), ran into some big trouble. The FDA wants more data, for one thing, and the reason that they want more data is that Clovis submitted preliminary clinical data to them earlier that have not held up. That was clearly done because they were in a race with AstraZeneca (and with time in general), but you’re walking on – or sprinting across – a flaming tightrope when you try something like that, and the results are clear. Clovis’ stock fell about 75% on the news
https://blogs.sciencemag.org/pipeline/archives/2018/02/02/a-...
>A closer look at the data, though, tells an even more different story. That overall POS figure is heavily dragged down by low success rates in oncology. Of the 41040 total pathways in the set, 17368 are for oncology (note that the same drug tried against two different types of cancer will show as two different pathways). The POS of everything outside of oncology is 20.9%, which the POS in oncology itself is 3.4%. If you look at lead indications, instead of all indications, the POS goes up overall (which is in line with earlier studies). But the Phase 2 to Phase 3 transition rate actually goes down a bit, interestingly. Oncology is still the lowest of bunch.
https://blogs.sciencemag.org/pipeline/archives/2017/01/23/i-...
>The timing of this report from the FDA is surely no accident, but it’s always a good time to think about this: the great majority of all drugs that enter clinical trials fail. They fail because they don’t do anyone any good, or because what good they might do is outweighed by some serious and unexpected harm. Around 90% of all compounds that start in the clinic never make it out. Even by the time you get to Phase III – and these are drugs that have apparently already worked in sick patients by that point – the failure rate is still nearly 40%. Drug projects fail constantly.
>It’s hard, sometimes, for people who’ve worked in other industries to appreciate this. Drug development is a unique combination of very high regulatory burden and very high failure rates, so it’s temping to say that the regulations cause the failures. But that isn’t true. Biology causes the high failure rates – specifically, our lack of understanding of biology.
Calling a field where, after spending tens of millions of dollars of development on a product, only 3.4% of them even work at all a branch of "engineering" is perhaps a novel perspective. If 19 out of 20 bridges promptly collapsed after being constructed, the word "engineering" might have different connotations.
As usual in biotech, when I see someone posting simple, obvious untruths for personal gain, I wonder: delusion, or mendacity? Fast DNA synthesis will not solve the actual bottleneck, which is, and has been for a century, clinical trials in humans.
I don’t work in biotech, and also don’t take kindly to being called delusional or a liar. The actual bottleneck isn’t human trials it’s better drugs, and even if trials were the bottleneck, why have you decided that bioengineering needs to be able to design a drug with guaranteed > X% chance of working before it gets to be called engineering? Also, you are ignoring all the other industrial, environmental and agricultural applications of synbio.
I'm writing some detailed articles on the topic, but check out this chart from Previn on the top performing funds from 2007-2015: https://mobile.twitter.com/zavaindar/status/1159660549615116...
All the $100M+ funds on this list are biotech funds: The column group, flagship, orbimed and foresite
Tech VCs have seen these returns and want in, but they have not been major players to date. In 2018 less than 10% of series a rounds in biopharma were led by tech VCs [0]
These days biotech startups can get very big very fast on comparable amounts as tech startups. But he structure in returns is such that you need more concentrated portfolios and low loss rates to do well
I think the narrative about biotech becoming more like tech is a way for tech investors to try to fit more power law driven portfolio strategy into biotech. Bioengineering advances have been incredibly important the last few years, but it is not really correct to compare the pace of product development and value creation in bioengineering to software engineering. I also think it's a bit of a red herring. Biotech VC has done fine on its own. If anything software VCs should take some tactics from biotech funds
A more accurate analysis would involve looking at all VCs and seeing if you can apply those rules in advance: What would your IRR be if you invested in all the specialty biotech funds as a basket?
Biotech funds are "specialist" but they aren't really small. Biopharma is a top 5 subsector of VC (by some estimates it is the 2nd biggest sector after software) and the largest sector by far of healthcare VC, with $17B+ invested in 2018. Orbimed manages $10B+ (though some of that is public equity). Flagship manages many billions (latest fund was $800M+). Foresite manages over $2B, last fund was $668M. Many other examples
I mentioned i was writing a longer post on the topic, that chart is a snapshot. If you invested in biotech VC as a basket recently it would outperform tech [0]. There's more recent data as well but i dont have the link offhand
[0] https://lifescivc.com/2016/11/biotech-venture-capital-mythbu...
I look forward to seeing how the newer larger biotech funds do/seeing more recent data during a time where public tech outperformed rest of public market.
And the thing is that it's easy to imagine such potential, it's easy to imagine that discoveries will accumulate sufficiently in biology that the field passes from being about discovery to being about engineering, which discoveries can be pumped out easily instead of being hard-won, limited and preliminary. But biology has so much variation and complexity and ad-hocery "all the way down" that nothing is ever as straightforward as you'd want it, nearly everything is done by hand even today and for a reason.
Unlike every kind of engineering and physical science, biology is wildly more complex and modulated by almost innumerable variables that are interdependent. I work in a large pharma, and one of the comments I hear often is "I'm amazed that any drug actually works as intended".
With 90% of validated compounds still failing after introduction into the human body (and the thousands of candidates new molecular entity candidate compounds that failed in vitro before that), the track record of human biology to engineered solutions is extremely poor and likely to remain so indefinitely. Just because new techniques are arising to manipulate the assembly language of the body does not mean they will have any better success in setting the right dials to the right settings among the myriad invisible gotchas of disease that inhabit that black box we call 'me'.
Until we can better know what's actually going on inside biology's many black box(es), no amount of engineering, no matter how precise, will reliably (and profitably) improve health outcomes. You can't engineer systems that you don't understand.
It's some people used to computing, it's some investors with a streak of optimism and it's some amateur pundits. Humans think in metaphors and "a machine" is one metaphor often used for life. It's not that good but the problem is pure vitalism is often the alternative and that's not good either.
Biology is very hard, it's more about discovery and iteration and a lot more deeper than tech.
Very few understand this, so it's been amalgamated with tech to promote the narrative.
I agree that comparing biology today to transistors in the 1950s might seem hubristic. But even if you don't buy that, I would bet on the notion that there are pretty massive opportunities at the intersection of tech and bio.
I work in Boston and there's tremendous activity in the life science space, as traditionally defined. Doesn't seem crazy to believe that market could support many billion-dollar companies that build picks and shovels.
Yep a tree.
It always amazes me that people get excited about a new car, new phone or a new software release from a technical angle ( not what you can do with it - that's fine ) - but also don't see the amazing machines called life all around us as interesting at all!
You are always the most complex type of machine in the room - by many orders of magnitude.
Yep, the risks are higher in biotech, yep the rewards are perhaps not as good as a Google etc, and it's way harder. On the other hand it's more interesting and in the end these companies are creating new treatments for cancer or heart failure etc.
Disclosure: I was part of a biotech 'unicorn'.
In terms of whether we are at the cusp of a biotech revolution - I'd say it really kicked off 20-30 years ago and is already here - the new wave of immuno-oncology drugs transforming cancer treatment are a good example.
I think the role of computers in the future is a little overhyped - it's necessary, but not the fundamental driver - the drivers are the new experimental technologies generating the data at unprecedented scale.
Imagine a disease/bug-prone, space inefficient, waste dropping, telemetry-less, allergy-inducing machine that requires continuous water deliveries and a multi-year build process. Yep a tree.
I won't try to tell you that you can't find trees and other biological constructs more interesting, and they certainly pose harder problems, but I'd think (and hope) that the future isn't overly complicated biotech adapted from even more complicated and wasteful natural systems. Right now we have to deal with heart failure and cancer because our crappy bodies are the best we've got, but I would think that the long-term future belongs to engineered systems that we can control, optimize, and understand.
Trees create habitat, buffer wind, provide shade, retain soil, and on and on. They're good at what they do.
Being good at what it does is somewhat negated by the other problems it creates, and the fact that some problems it solves are only needed for other suboptimal biological constructs in the first place. There are better ways to provide shade. There are better ways buffer wind. It's good at retaining soil and habitat...only for other biological constructs that suffer from similar problems. I'd be disappointed if our vision of the future is akin to really good soil retainers. Future tech shouldn't need soil at all.
I suspect this sort of nature-fawning is some kind of evolutionary bias; we find beauty in natural biology because we evolved to rely on it. Nature can certainly teach us a thing or two in a way that only millions of years of natural selection can, but tech that we control, optimize, and understand (ie. tech we can actually engineer) should eventually beat it in value.
Our natural systems on this planet blow our "tech" systems out of the water by orders of magnitude by their order of complexity and their capabilities. To try and trivialize a tree to the listed attributes without looking how it fits into our entire living ecosystem is so incredibly diminutive and a classic simple narrative of humanity thinking we control this planet and that it was built for our benefit. We are merely here at this moment in time, we might not exist in a thousand more years, a million years? Who knows.
Do you realize that they grow out of the air - ie all that bulk comes from captured atoms from the air, not stuff pulled in through the roots.
In terms of our crappy bodies - they are incredibly complex machines trillions of cells, each one unbelievably complex - it's astonishing they work at all.
But you are right eventually they fail - and natures answer is to simply reboot ( build a new body from scratch ) - the consciousness you are so keen to protect is simply RAM state that get's blitzed on reboot, while the cycle of life goes on....
We are made from mostly ( 99.85 % ) 11 elements - some gases, carbon, bit of metal
Not saying we shouldn't make stuff - just that people seem to have a blind spot on what we can learn from nature, and technically how amazing it is.
> I would think that the long-term future belongs to engineered systems that we can control, optimize, and understand.
And if we could understand, optimize and control biology - it would be so much more amazing - cells are nanobots - they can already sense, move, change shape to squeeze through gaps, replicate, signal, repair, kill, and control their environment.
In fact those trillion cells - cooperate to make you - you are a collection of cooperating nanobots. Take a look at some forms of life that take this to an extreme, that live as single cells and then come together to build a much more complex structure - https://en.wikipedia.org/wiki/Dictyostelium_discoideum
Big Hero 6 nanobots - biology - been there - done that.
Yes, cells are nanobots, but they're nanobots "designed"/evolved by nature with deeply complex goals and incentives often orthogonal to ours. Cells come with a lot of evolutionary baggage and many constraints owing to its extensive optimization.
From my perspective, it's like hijacking a crazy project that doesn't belong to us. It's not clear to me that taming insanely complex cells to serve our goals is better than building traditional engineering up to do the same thing.
I compare this tension to ARM vs x86 for mobile devices. Mobile devices uniquely require extreme power efficiency, and ARM processors are dominant because they satisfy that critical requirement even though they're less capable than other processors. Intel wanted to enter the mobile market and they already own the more capable x86 platform, but its power efficiency is a lot worse. Can Intel retrofit ARM-level power efficiency onto its deeply complex and desktop/server-optimized x86 processors before ARM builds up to x86's level of capability?
Honestly, I don't confidently know the answer and you could be right. But I think it's telling that centuries of medicine and decades of biotech have been a slow grind producing very narrow solutions (eg. invented a chemical cocktail to treat one type of cancer, tweaked a plant to contain more of a certain type of nutrient and be resistant to a handful of common diseases/bugs) while ground-up engineering is seemingly exponential, where today's tiny portable processor is orders of magnitude more advanced than the state of the art only a few decades before.
Yeah, nature and biology has a headstart, but we don't have to spend a thousand years figuring out how to develop an appendix.
You say we have made little progress in biology technology - yes and no.
Yes - there is so much more that could be done.
No - you are again ignoring the stuff in plain sight - the vast majority of our food comes from 'engineered' animals or plans - very little from wholly engineered chemical processes.
Breeding is low tech engineering - but it's still engineering - the productivity of commercial wheat is vastly superior to wild grasses for example.
Or look at the variety of dog breeds - each one developed for a particular purpose - from sheep herding & rabbit hunting to guiding blind people.
Now it's perhaps too easy, and not intellectually completely understood - but if you are focusing on outcomes - it's bloody effective.
The right virus - a tiny thing much smaller than a single cell - could wipe out a huge proportion of the population - it's happened in the past.
You can imagine a future where Iron Man fights for human survival with rockets, missiles and high tech, but you ignore biology at your peril.
MA: "Bio today is where information technology was 50 years ago."
Bio today is still in the pre-transistor era of IT. There is no tool that doubles our capabilities to manipulate molecular processes every 18 months. No, genome sequencing does not count, it is "read only." No, as amazing and as promising as it is, CRISPR does not count. For the present we continue to merely tinker, which is invaluable and necessary to more forward. Maybe once we figure out how to efficiently, reproducibly engineer enzymes, which truly accelerate molecular processes, we can claim that human-directed bio is eating the world. Until then, nature-driven bio is still on top.
To the other persons comment (sorry for not replying to your thread) - of course there are smart people at A16z though it is important to read that smart != correct.
Fortunately, medicinal chemists have fared better in silico, often employing computational techniques to reduce their search space for a compound desired behavior. But I think no one would describe their models of molecular docking / binding as manifestations of engineering or systems biology.
When I hear "iterative" design I think of shitty car infotainment or router software that only works half the time and never is updated/supported... Except its under my skin and I cannot get it out.
When I hear designer molecules + DNA I think of DRM and a lack of "right to repair" . But now its inside your body and the business owns it.. err you...
The idea that our understanding of molecular biology is as mature and stable as our understanding of the field effect transistor was in the 1950s is frankly laughable. I predict many many investors getting burnt by biotech, as well as some pretty nasty externalities if regulators buy the hype.
edit: improve sentence structure
For instance early genetic testing revealed a huge number of disorders that could be linked to single genes that changed the game for how a certain sub-population has kids and treatment for a handful of disorders. Then it turned out a lot of stuff was multigenic or only very partially genetic and progress has stalled. As genetic testing has gotten cheaper we have learned more, but actual usable insights are rare.
Or take lab grown insulin from 1980s, it was a huge deal, everyone worked on similar technologies and knock ins and for a handful of disorders it was a complete game changer that petered out medically speaking. It saw a weird second life in farming and GMOs for a time that helped improve processes but didn't really move the needle in a big way. Then as it got cheaper, and new more efficient tools emergedm it reexploded as the field of biologicals, which have been great drugs since the mid-2000s. And as the technology gets really cheap we are seeing products like lab meats, Impossible leading the charge there, emerge.
Now we are on CRISPR, RNA-sequencing, CAR-T, and tissue engineering all of which, when they hit will have massive impact, but then slow down for a bit until the next big thing revs up.
This parallels chemistry where the theories of thermodynamics and gas laws emerged, sped everything forward, then petered out. Then organic chemistry emerged using a lot of the ideas developed by the previous field, sped everything forward for a while then slowed down. Then inorganic and solid state chemistry etc. But there was never a 18 month doubling it was more like a 10 year lull followed by 1000x in 5 years, if you were counting for example, the number of compounds developed. You could smooth the curve and pretend it was like compute but it's not. We'll just look back in 20ish years, or even look back today at the 1950s, and say 'wow there is a lot of stuff in our life that was based on biological research where did that come from'. Just like someone in the 1940s would look back and be like 'wow where did all this plastic/metal fab come from'.
The risks with poorly conceived GMO's are so much higher... but fortunately the technology to do it has been out of the reach of all but a few large companies or institutes who have by and large been very careful.
But now the technology is becoming accessible even to individual enthusiasts.....
It's like nuclear technology becoming in reach of the ordinary citizen.
In my opinion, information medicines is the fantastic convergence of bio and tech, so I would look for biochemistry labs that focus on DNA and RNA.
Once you have a list of local research institutes, I can help you pick a lab to focus on. Then you just hammer them constantly by email and in person asking questions about the work until they hire you to wash the dishes :)
I like to start with some books and simple experiments at home, but have no idea where to begin.
In the past, I thought about going back to college. But I wasted enough of my time there and am still burned. Just give me the relevant bits, skip the fat. But I guess you really need some lab experience to really get biotech and that is not something you just get by yourself.
I also applied to some companies that work in biotech related ares, zero response (full-stack job offers). Well, I think I send one application and two inquiries, still no response. That was very irritating, as it did not happen before anywhere else. But all of them wrote that they want a bit of a bio background, so I attributed it to that.
The hubris on display here is typical of tech VCs, who eventually believe their own hype. If it's hard for humans to comprehend, just rub some machine learning on it... ignore that we're finally realizing that machine learning's limitations are significant, but that we can only discover how wrong they can be on results that humans can double-check.
And the naive application of software engineering buzzwords like "modular" and "iterative" to drug development and biological processes is seriously dangerous. You don't want to move fast and break things when we're talking about human health and genetics.
This article is full of misleading claims and overstatements of reality. It's easy to make things sound great when you entirely ignore the reality of existing and potential technology, but of course I don't expect anything different from these folks.
The horrors have just begun.
The closest thing I have is twenty-ish pages of notes I braindumped for a colleague who had just entered bioinformatics from computer science, but those already assumed lots of conversations and information already in place.
It's made even weirder because biology is three fields inextricably intertwined (genetics, physiology, natural history). For each one you can start at the beginning, but how do you provide some kind of linear path through all three at once?
I totally get your point, and it maddens me daily but I take the interesting + meaningful work/money tradeoff and enjoy being one of the best coders in a building (much harder in pure tech)
[1] http://madhadron.com/posts/2012-03-26-a-farewell-to-bioinfor...
My usual response these days is that if it's raising red flags for them, they should explore what troubles them until they have satisfied themselves rather than taking the word of some random guy on the Internet.
From here inside my head, I think my criticisms are still accurate, nor have I seen any actual refutation of them. Lots of ad hominems. Many people not understanding that terms like "computationally difficult" are precise terms of art, and have nothing to do with intellectual or conceptual difficulty.
With age and humility and, more importantly, absence, my attitude is probably better described as "meh."
http://rosalind.info/problems/list-view/
Biology for computer scientists:
https://wwcohen.github.io/GuideToBiology-sampleChapter-relea...
Imagine if you could just copy/paste your medical records in an email to change doctors. Or participate in a new medical study via a simple copy/paste. Or if you were in an acute care setting and your healthcare providers could instantly call up all your relevant medical history. We are going to enable those sort of things.
But more to your point, I understand health care costs are crazy (especially in the US), but I am concerned that capping health care expenditures will dis-incentivize companies from taking risks on new vaccines and therapies.
What the hell do they think doctors and other healthcare providers have done for all of history? What do they think surgery is? This is such fluffy hype, I feel insulted.
Bio has been touching all of our lives for a long time now, from vaccines to food to basic research yielding large advancements in medical understanding.
What we are on the precipice of may be personalized or customized biochemistry, which is something we desperately need if we ever want to attack diseases like cancer, enable radical regenerative intervention, or tackle the effects of aging.
On a side note, I feel that we should put a moratorium on the phrase "X is eating the world". Right now we're using it whenever something needs to be hyped and it's becoming quite cringy.
Mobile is eating the world (2016)
Software is eating the world (2011)
"England’s calculations suggested that groups of atoms that are driven by external energy sources can behave differently: They tend to start tapping into those energy sources, aligning and rearranging so as to better absorb the energy and dissipate it as heat...
England sees life, and its extraordinary confluence of form and function, as the ultimate outcome of dissipation-driven adaptation and self-replication."
https://www.quantamagazine.org/first-support-for-a-physics-t...
When a chimp uses a tool, like a long twig, to pull ants out of the ground, it has used basic engineering (tools) to solve a problem. The species advances because of this.
The single most important aspect of all of this is the metaphysics.
https://en.wikipedia.org/wiki/I_and_Thou
> Buber's main proposition is that we may address existence in two ways:
> 1. The attitude of the "I" towards an "It", towards an object that is separate in itself, which we either use or experience.
> 2. The attitude of the "I" towards "Thou", in a relationship in which the other is not separated by discrete bounds.
Biology is Thou.
- - - -
When Prof. Michael Levin talks about "What Bodies Think About: Bioelectric Computation Outside the Nervous System" (youtube.com) https://news.ycombinator.com/item?id=18736698 he keeps saying, "What if our technology could do this?"
The answer is, our technology already does "this". We are 4By-old nanotechnology. You've heard of Grey Goo? It turns out that the oceans are already "Blue" Goo.
https://en.wikipedia.org/wiki/Grey_goo
> Gray goo (also spelled grey goo) is a hypothetical global catastrophic scenario involving molecular nanotechnology in which out-of-control self-replicating machines consume all biomass on Earth while building more of themselves,[1][2] a scenario that has been called ecophagy ("eating the environment", more literally "eating the habitation").[3] The original idea assumed machines were designed to have this capability, while popularizations have assumed that machines might somehow gain this capability by accident.
https://en.wikipedia.org/wiki/Marine_bacteriophage
> Marine viruses, although microscopic and essentially unnoticed by scientists until recently, are the most abundant and diverse biological entities in the ocean. Viruses have an estimated abundance of 10^30 in the ocean, or between [10^6 and 10^11] per millilitre.
> Although marine viruses have only recently been studied extensively, they are already known to hold critical roles in many ecosystem functions and cycles.
We keep making discoveries (like the bacteriophages) that show us that we have no real idea what's going on in the biosphere, which includes our bodies. I think it behooves us to wait a few centuries before we go hog wild on the only known ecosystem in the entire Universe, eh?
#1 Brain today (unknown but someone like Terence Tao, Edward Witten, Magnus Carlsen, or Donald Trump) https://aiimpacts.org/brain-performance-in-flops/
#1 Supercomputer
performance: 148,600 TFlop/s
power: 10,096 kW
1# Brain
performance: 9,000 - 337,000 TFlop/s
power: 20 W.
Yeah, not really.
These measurements mostly rely on the entire brain firing all at once, while a real brain does not do that.
Or it was until recently, it’s hard to keep up.