1/ Platforms are the geese that lay the golden eggs of biotech: blockbuster drugs. Yet most platforms produce few, if any, eggs. 🥚

But fertile geese are coming. 🦆

@heyjudka @a16z and I explore how productive platforms will transform biotech. 🧵 👇

a16z.com/2021/01/08/bio…
2/ Biotech has historically had a multi-armed bandit problem.

Spend each incremental dollar feeding the goose? Or invest it in incubating a golden egg?

Companies tend to starve their platform in order to nurture a potential product. Image
3/ But a new wave of productive platforms changes that calculus.

The shift from bespoke craftsmanship to industrialized drug development will transform what we can make, how (and how fast) we make it, and how the industry is structured.
4/ These industrialized platforms are built on powerful technologies—biological engineering, AI—that give us enhanced superpowers:

to *interrogate* dark corners of biology,

to *intervene* against disease w/ programmable medicines.
5/ This is biotech’s industrial age. With upfront platform investments, benefits accrue and compound to “stamp out” better processes + products over time.

These platforms are the foundation on which many future applications—therapeutics, diagnostics—will be built.
6/ We’ve seen the benefits of industrialization. @illumina enabled interrogation at scale—to decode entire genomes virtually overnight. Now we’re seeing the rise of intervention platforms: @moderna_tx built a machine that designed an mRNA vaccine in 48hrs.
a16z.com/2020/12/18/mod…
7/ Industrialized platforms support multiple models:

Vertical integration—build a machine to make products at increasing speed, scale + sophistication.

Horizontal infrastructure—build components, capabilities + interfaces to power many machines: the API economy for bio. Image
8/ So if you’re a platform company, which do you choose—vertical or horizontal? Traditionally you would nurture your own golden eggs.

But that’s not the only path. Maximizing value may mean providing the picks and shovels to the gold rush.
9/ For vertical players: What’s the value of integration; is the whole greater than the sum of its parts?

Is there compounding potential for products where v3.0 is built on the foundations of v2.0?

Is there a single, super valuable vertical that dwarfs other applications?
10/ For horizontal players: What is the breadth of your platform (who needs your widgets)?

How critical is your cog for powering machines (how valuable are your widgets)?

How do you prove your technology works (when are your widgets validated)?
11/ Vertical: @TmunityTx, Lyell fully-integrated to focus on complex CAR T engineering + manufacturing processes.

Horizontal: @adimab @AbCelleraBio (antibody optimization), @Dyno_Tx @AcuitasLLC (DNA/RNA delivery) sell critical components/capabilities broadly across industry.
12/ If biology has taught us anything, it’s that rich ecosystems support multiple winners—and that models evolve.

So this is about where to start, and how to win, not where you’ll end. The journey is treacherous—put your eggs in the right baskets.
🥚🧺
a16z.com/2021/01/08/bio…

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More from @JorgeCondeBio

13 Jan
1/ Biotech is a tough business.

There are 10,000+ human diseases out there. How do startups w/ promising platforms choose where to focus?

Choose wisely. @andy23tran @a16z & I offer a framework for finding your Platform-Disease Fit (PDF)
🧵👇

a16z.com/2021/01/08/pla…
2/ Finding PDF early in life is essential to success.

Your first disease tends to become your adjective: “Acme Co, a cancer company…”.

So what funnel criteria do you use? Image
3/ First step: find your superpower. What’s your platform edge?

It’s not enough to solve a problem; what problem can you uniquely solve?

Can you tackle an unknown or unreachable area of disease biology?

Can you dramatically improve on or leapfrog competitors?
Read 15 tweets
12 Jan
1/ Engineered biology (like cell + gene therapy) is a powerful tool for TREATING disease. What if biology could be engineered to FIND disease too?

In 2018 I met @cyriac1 Roeding & Sam Ghambir, a pioneer in early cancer detection. Their company, Earli, proposed to do just that. Image
2/ Earli’s mission is to detect cancer early so it can be treated.

As a leading cancer physician, and father to a child that succumbed to the disease, it was a deeply personal mission for Sam.

@goearli is a testament to his life’s work.

stanmed.stanford.edu/2016fall/milan…
3/ Developed in Sam’s lab at Stanford, Earli’s technology can program bits of biology to force cancer cells to reveal themselves—a “synthetic biopsy” to precisely locate cancer cells inside the body so they can be treated, early.
Read 8 tweets
11 Jan
1/ “The price of a drug should never be the rate-limiting factor to patient access.” — Alexis Borisy, EQRx CEO. @EQRxINC raises $500 million Series B in service of their mission to bring important new medicines to society at radically lower prices.

eqrx.com/press-release/…
2/ The Series B investor syndicate includes life science specialists, mutual funds and other generalist funds—as well as payers + health systems that cover more than 20% of insured lives in the US.
3/ Launched just one year ago, EQRx has built a deep pipeline; it has disclosed late-stage cancer programs targeting PD-1, PD-L1, EGFr, CDK4/6. In partnership with health systems + payers, EQRx estimates it could save the US healthcare system 50-70% of drug spend in key diseases.
Read 4 tweets
18 Dec 20
1/ Another big day for COVID-19 vaccines! FDA panel votes to recommend emergency use authorization for Moderna’s mRNA vaccine.

@Moderna_tx CEO @Sbancel shares HOW they made a vaccine *in less than a year* w/ me + @omnivorousread on @a16z Bio Eats World

a16z.com/2020/12/18/mod…
2/ Within 48 hrs(!) of having a digital copy of the virus genome, Moderna designed a vaccine - the exact version now being shipped - without having access to the physical virus.

This is *the machine that made the vaccine*

We used to grow our vaccines; now we can print them.
3/ The tech works by delivering mRNA instructions for cells to make a protein. In this case, the vaccine is delivering instructions for making the SARS-CoV-2 spike protein (so our immune system learns to attack it).

@sbancel describes it as sorta like making chocolate mousse :)
Read 10 tweets
31 May 19
1/ Recently $NVS announced a $2.1m gene therapy, the most expensive medicine in history. Gene therapies are potentially curative. How should we price them? How will we pay for them? Could a cure be considered a pre-existing condition? 🧬 💊
a16z.com/2019/05/30/cur…
2/ Rare disease therapies are expensive because: i) they treat devastating diseases, ii) patient pops are small, so biopharma recoups R&D investment w/ high price, iii) payors tolerate because limited risk of many patients in a given plan + limited # of new therapies to cover.
3/ Individually, rare diseases (by definition) affect few people; collectively, 30m Americans (1 in 10) suffer from one of 7000 rare diseases. There are now lots of gene therapies on the horizon for lots of rare diseases; many >$1m therapies in our future. How will we pay?
💰💰💰
Read 7 tweets
5 Jan 19
1/ A thought for early-stage bio companies on the eve of the upcoming #JPM19 networking bonanza in SF: Bio entrepreneurs, especially first-time founders, often underestimate the importance of analyzing and selecting potential disease areas
(thread 👇)
2/ Your resources are (probably) finite. Your platform may have broad potential but if your goal is to develop therapeutics (Tx) or diagnostics (Dx), you need a rigorous process/framework for selecting disease indications. It should be an early core competency for your company
3/ This is particularly important given how long, risky and expensive it can be to develop a new Tx or Dx. We’ve written previously on 16 pitfalls to avoid when building a computational Tx startup, many of which touch on this issue (especially #5) a16z.com/2018/04/30/bui…
Read 14 tweets

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