Or: Biology is really hard, and returns to investors in the space have been pretty tame, and taken longer than promised (expected). See commentary by Peter Thiel in Zero to One for more on this topic. In response to this reality, one tactic is to create a narrative that sells the vision of biotech as a tech or engineering discipline to an investor audience that is naive about biology and uber bullish on tech eg, this article). "Biology? It's just engineering, we can engineer things, we'll just engineer biology (please invest in us as if we're tech]". Never mind that engineering is a tradition built on minimizing variation, while biology is a science founded on understanding a built-in mechanism for generating variation. "Life finds a way". Indeed. I've been on numerous synbio projects and one thing is certain, evolution is always driving against the engineered design. And by driving against, I mean undoing. Entropy might slowly undue engineering, but mutation and selection? It's an entropic accelerant for engineered outcomes. Also, engineering is about "parts" and synbio is constantly dreaming of building things by putting parts (promotors, genes, etc) together from a catalogue. In reality, biology is interactions, where the expression of almost everything is dependent on the context of all the other parts. So outcomes aren't simply "the sum of the parts". When they are it's for a minority of cases. Finally, as you scale a process (say from a test tube to a 1,000,000L industrial sized fermentation tank, biology almost never cooperates.
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).
This seems a fairly narrow view. In my field (oncology), there are many drugs saving lives that are the result of what is engineering in biological systems. Certain immunomodulating antibodies are the most recent example, one of which is earning it's pharma company many billions of dollars a year. Another proven class of drug is conjugating chemotherapy to the back end of an antibody. These drugs have undergone incremental improvement, with the latest versions showing greatly enhanced efficacy. This to me meets the criteria for engineering. Then there are CAR T cells. Researchers in this field actively describe their work as 'immuno-engineering'.
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.
An enthusiastic way to look at this is that success will be very uneven in a field that is not well developed.
That points towards acceleration.
I agree that great advances in biotech have come from bioengineering (all the way back to Genentech, the first biotech company) and I think that a lot of great advances in biotech will continue to come from bioengineering.
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
The top selling check-point inhibitors ie "immunotherapy", Keytruda and Opdivo, were not found by anything remotely resembling 'engineering'. It was a traditional lab science and drug discovery. If anything those two drugs have expanded their lead commercially, with no other PD1 drug approaching it. None of the top 10 selling Abs are drug-conjugated. CAR-T is struggling mightily in the clinic - it is the opposite of "scalable" due to the personalized nature, and has a terrible side-effect profile.
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.
I see you have a specific idea about what ‘true bioengineering’ should look like. But you have just made this up, based on your own ideas, which I simply reject.
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.
Dear Gatsky, My point is not that there is no engineering or no biotech in the world - to the contrary. There is antibody engineering, biomedical engineering, and many other types of engineering. I am a computational biologist. I actually worked at the George Church Lab, playing with the Polonator (an early sequencer prototype). I started a computational biology company (Seven Bridges Genomics), and then spun a biotech from it. So I truly believe in engineering.
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.
https://blogs.sciencemag.org/pipeline/archives/2017/05/12/tu...
>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 see the ‘One True Engineer’ has shown up. Comparing bridge building to engineering antibodies is absurd, a x10^12 error in scale. A better comparison would be to semiconductors, where you will find many ongoing failures, even in current production runs. Also, the mere fact that it is difficult to engineer something doesn’t mean it isn’t ‘engineered’, another absurd contention.
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.
Biotech venture has actually outperformed tech venture in recent years. But the venture firms that have done well are specialist venture funds that only do biotech.
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
[0] https://www.baybridgebio.com/blog/top_vcs_2018.html
I'd be careful reading too much into data on top performing funds. The law of large numbers makes it so that smaller funds are more likey to outperform (and underperform) since they have higher variance. Couple that with the strong correlation that speciality funds are more likely to be smaller and it's not surprising.
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?
The small funds on that list are all tech funds. The larger funds are all biotech.
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 was more referencing the tweet which looked at the performance of a particular vintage of those funds: https://mobile.twitter.com/zavaindar/status/1159660549615116... none of which reached $1 billion vs the largest funds on the second page https://mobile.twitter.com/zavaindar/status/1159660549615116...
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.
Sure, biology might be profitable investment for those who know it well but I think the important part of the GP is that biology doesn't have the potential to "explode" in the fashion that chips exploded with Moore's law.
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.
But it's only people who live (and think) in clean room environs like computing that imagine biology is amenable to engineering. It's really not.
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.
But it's only people who live (and think) in clean room environs like computing that imagine biology is amenable to engineering. It's really not.
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.
Yeah, wake me up with bioinformaticians (computer programming + biology + statistics) make more than computer programmers.
It's an incredibly interesting field, but over-hyped, extremely hard and not particularly profitable.
Yep true. But you also missed out that biotechs are trying to cure/treat serious diseases like cancer etc and not simply trying to sell more advertising.
No good deed goes unpunished!
This will be an unpopular opinion, but do you think that money could be better spent on other health initiatives like prevention? Is spending 10-100k per month so rich people in developed countries can live a few months longer really that much more moral?
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).
I'd be really disappointed if your opinion is unpopular. I completely agree and find it depressing to see how our culture admires Gates as an idol of altruism. He's had impact, sure, in the same way that someone with an infinite river has the ability to extinguish forest fires but extinguishes a few brush fires instead... just enough to outpace his competitors and lock in the perception of being most benevolent.
Worst form of social darwinism EVER.
A sibling comment in this thread also applies here. "No good deed goes unpunished!"
For lung cancer - yep - banning smoking would not only massively reduce the rates, but also other lung diseases - China is heading for an absolute epidermic here.
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?
It's actually very profitable and only overhyped by people that aren't currently profiting from it.
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
As a sector or select lucky funds? Source?
Nasdaq biotech 3y: +20%
Nasdaq tech 3y: +75%
As a sector. One source is here: https://lifescivc.com/2016/11/biotech-venture-capital-mythbu...
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
Thanks, I haven't been following closely, I should start pitching VCs!
This is spot on, I graduated with a degree in genetics and cannot articulate this any better.
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.
>>> Entropy might slowly undue engineering
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.
Veeva raised $4M in VC to build CRM for life sciences and currently has a $21B market cap. It's one of the 15 or so best exits of the last decade.
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.
Yup, and this piece had nothing more than the same fluff we have been hearing the past 15 yrs about bio"tech". Until we can literally simulate a biological system in software (then discovering a new drug would be more deterministic), it will always be a discovery discipline, not an engineering one.
We're 100 years away from that, at least at human-scale.
Have you seen the magic that protein engineers have produced? GCaMP6f for instance? You’re right in that it’s still discovery science and is hard but we are making large strides towards proper engineering in certain domains.
This reminds me of the same discussion back in the late 90's
"Life finds a way", Jurassic Park jokes aside, was the moral of the whole saga: Thou shall not mess with systems you do not understand.
Taleb talks about caution all the time for a reason, complex systems are, indeed, complex.
And here I thought the moral was "thou shall not be stupid or arrogant".
The only way we can understand a complex system is by messing with it.
At which level of abstraction?
At any. To verify your models about a system, you need to prod it and see if it responds the way your model predicted. Passive observations alone usually aren't enough to even build a correct model. Whether you're interested in understanding low level mechanics or high-level system behavior, the procedure is the same.
This is where ethics come into play
I think there is messing to find out how it works (works best with man-made technology), and there's applying/marketing stuff that we don't yet understand.
The latter would naturally be dishonest, i.e. malicious. Not (merely) stupid.
I like your style.
I agree with you. I don't think you can learn anything without messing with it and it's in our best interest to learn and mess with it. On the other hand I most certainly would not want to see the SV mentality applied to a field that could bring about a global pandemic.
Oh hell no! I used to joke here that people will eat their hats for the "move fast and break things" ethos when somebody starts Uber for Biotech, complete with sociopathic management and utter disregard for law and safety.
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".
Like Theranos?
Theranos mostly fooled investors. I worry about companies that mess with the rest of society. "Uber for Biotech" is essentially a recipe for huge loss of life.
IIRC they also faked and sent out incorrect blood test results for many, many patients.
I stand corrected.
Ha, didn't think of that when I wrote it, that's a good point. I looked at it from a Talebian perspective, so to say, and forgot about that approach.
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.
I don’t see much issue with it. Today’s investing is faith based. Is it better to invest in WeWork or Uber? Why?