# funnels

if you look closely at the fabric of reality you see it made of funnels, all sort of funnels that move along the arrow of time obeying to  the principle of attrition. What lies at one

Used to the funnels of digital marketing, the funnel of medical R&D looks even more demanding, moving at its own glacial pace

The overall process from idea to product can therefore take from 9 to 16+ years to complete. Furthermore, historically only one in 20 compounds that start the development process ever become marketed drugs. This is not an enterprise for people with a low tolerance for failure or for those who need immediate gratification.”

“In general, the investment needed in discovery to carry out all the work to identify a potential new medicine can range from $25 to$30 million. This is what it takes just to get to Phase 1. Interestingly, these early costs tend to be fairly standard because it generally takes the same number of scientists and similar resources to discover a new drug for rare diseases as it does for drugs to treat the most prevalent conditions. Similarly, Phase 1 testing also tends not to vary among new medicines and so these studies amount to $10–$15 million per compound. At Phase 2, costs vary depending on the information that is needed to justify the major Phase 3 trials. Thus, a Phase 2 program can cost between $60 and$100 million. However, all of the costs to this point are dwarfed by the ultimate Phase 3 program. Before Phase 3, perhaps as many as 500 people have been studied with the new drug. Phase 3, however, involves thousands of patients in many different complex studies and testing for periods that can last for years. The large investment in Phase 3, anywhere from $400 to$800 million, requires full approval at the highest levels of a company.”

John LaMattina “Drug Truths”

Roivant, funded by Softbank. Unbundling and efficiency come to Pharma R&D

“Roivant goes looking for drugs stuck in turnaround—not because of problems with the science, but because of corporate changes-of-plan. “Once we take over those drugs, the same cultural attributes that allowed us to focus on specific drugs rather than general therapeutic categories allow us to focus on the process by which those drugs can be accelerated to the finish line,” Ramaswamy says

Drugome: Roivant has mapped 30,000 potential drugs, 2,000 mechanisms of action, and 10,000 endpoints this way—all from publicly available, mostly free databases.

# AI diffusion curve

1 some AI has percolated into AWS; Azure and other cloud services

2 some AI is done quietly under the hood in great many tech companies

3 in some companies AI has enabled uniue features, but the company does not go around selling “my AI will change your business” but rather “I alone have a cool feature you can’t do without

4 AI is applied to non-tech real world problems where data are in silos away from google and china

of course there is a stack of cloud, algos, devices that allow to unbundle old world problems.

Ai is a tech that is defining its S-curve much like databases, ML is the new SQL “\over the past few decades we moved through databases, ‘productivity’, client-server, open-source, SaaS and Cloud. In parallel with new client platforms, we had new waves of architecture or development model, and that’s really a better way to look at machine learning – ML is the new SQL (and maybe crypto is in part the new open source)”

https://www.ben-evans.com/benedictevans/2019/10/4/machine-learning-deployment

# Technology company or not ?

AVC: give software valuations only to software company becuase onlòy those can sustain >75% gross margins. Software is eating the world but still software companies have higher margins than non SW. The Great Public Market Reckoning

Stratechery follows Christensen in saying that a technology company is one that can offer something intrinsically more valuable thanks to disruption – What is a tech company?

Bill Gurley replies to AVC with his 2011 mammoth post on startups valuation titled All Revenue is Not Created Equal: The Keys to the 10X Revenue Club

Mauboissin Competitive Advantage Period or CAP that explains valuation in firms with lasting competitive advantage Competitive Advantage Period “CAP,” The Neglected Value Driver

in the news, IPO’s of pure tech (SaaS etc) outperform transactional platforms and hardware first https://twitter.com/DKThomp/status/1183898414695755776

# drones, cruise missiles and strategic balance

cheap cruise missiles with autonomous GPS guide are a new threat, do they change the strategic balance? More

https://www.thedrive.com/the-war-zone/29874/the-strike-on-saudi-oil-facilities-was-unprecedented-and-it-underscores-far-greater-issues

Economst wrote about cheaper missile, rocket galore in 2012

not really related, sort of catch all post, 2008 RAND war games featuring Cina and US carriers

# Building moats

Moats, growing popular concept

frameworks and charts from Measuring the Moat from here:

also Measuring the Moat – Credit Suisse by Mauboissin sound Porter framework of industry and competition analysis

Strateachery’s Moat Map relating to difference Platforms vs. Aggregators, network effects internlized vs. externalized

(Ryan Reeves 3d collecting all strategic frameworks ) https://twitter.com/investing_city/status/1176629867594387456

# von Neumann defines games

“Chess is not a game. Chess is a well-defined form of computation. You may not be able to work out all the answers, but in theory there must be a solution, a right procedure in any position. Now real games,” he said, “are not like that at all. Real life is not like that. Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do. And that is what games are about in my theory.” (von Neumann)

From “Strategy” Lawrence Freedman

# VC power curve

6% of the deals make 60% of the profits

VC’s performance is driven by how big are their hits, not how many their flops

from Ben Evans “In Praise of Failure”

found on Chen of a16z  “Why startups are hard — the math of venture capital returns tells the story”

Found at Fred Wilson’s https://avc.com/2019/09/the-hit-rate/

the rate of return of the whole VC industry correlates perfectly with the share of investment generation 10X+ returns

# Mc Luhan quote on tools

“We shape our tools and thereafter our tools shape us” — Marshall McLuhan

Ben Evans “Hence, channeling Marshall McLuhan, new tools start out being made to fit the existing workflows, but over time the workflows change to fit the tools.”

https://www.ben-evans.com/benedictevans/2015/5/21/office-messaging-and-verbs

In a post speaking of Slack and sw envirnments for productivity

“Ironically, Lotus Notes, one of the earliest corporate messaging programs, was intended to be much more than email, calendaring and so on – there was a vision of a unified development environment, database and messaging system – ‘groupware’. It didn’t quite work out like that, and actually using Lotus Notes as I had to 15 years ago was rather like using an email client built with Microsoft Access – theoretically possible but not a very good idea. OLE in the 1990s was another concept that didn’t quite work, embedding pieces of one program’s document inside another. But today, Facebook’s platform on the desktop is pretty much Ray Ozzie’s vision built all over again but for consumers instead of enterprise and for cat pictures instead of sales forecasts – a combination of messaging with embedded applications and many different data types and views for different tasks. Hence, one could propose one future model as ‘Facebook for the enterprise’, but with the platform, not the social, being the point of the analogy.”

started from a post on Microsoft capitulation, giving up on Windows everywhere which in hindsight helped to go back on top of the tech world

https://www.ben-evans.com/benedictevans/2015/7/8/capitulation

This is turning into Ben Evans quotes “That is, Google tests new opportunities to see if they fit in the same way that a shark bites a surfer to see if they’re a seal. If not, you don’t change Google to fit the opportunity – you spit out the surfer (or what’s left of him). ”

Google as a “vast machine learning engine”