You can read our research in the PDF attached. As always, we welcome any thoughts or feedback on our research.

Data Problems V1

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Disclaimer: The views and opinions expressed above are current as of the date of this document and are subject to change without notice. Materials referenced above will be provided for educational purposes only. None of the above will include investment advice, a recommendation or an offer to sell, or a solicitation of an offer to buy, any securities or investment products.

The central dogma of biotechnology is that therapeutics are more valuable than diagnostics. We think we should flip that on its head. Diagnostics are the silent champion of healthcare, influencing >60% of clinical decisions but only accounting for 2-4% of healthcare spend. Any additional investments would yield large returns for healthcare systems and patients.

—Andrew Hui & Wes Keelan

Diagnostics

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1. Pathology is limited by overgeneralized stratification

2. Diagnostics are critical but remain a fraction of healthcare spend

3. The trajectory of therapeutics and diagnostics are converging

4. Biomarkers are transitioning from simple to complex

5. Simple and scalable applications of standardized data in healthcare have been massively rewarded

6. Strong biomarkers compress biological complexity

7. Network medicine is the ultimate expression of convergence

8. Diagnostics must continuously measure network states, not just detect individual molecules

9. Diagnostic accessibility limits the evolution of disease management

10. Diagnostic innovation may be the key to breaking Eroom’s Law

Disclaimer: The information in this post is not intended to be and does not constitute investment or financial advice. You should not make any decision based on the information presented without conducting independent due diligence.

There is a lot to be said about the parallels between semiconductors and sequencing. Semis has Moore’s Law and biotech has Eroom’s Law. Illumina seems to be analogous to Intel: increased miniaturization, density, and lower costs. Much can be debated about how much weight this analogy holds, but what if there are seeds of truth in this reductionist and simple view?

I think there is, and that introduces wide implications. If sequencing is in the in the early innings of computing, what will the trajectory of evolution be? In a world that is fighting over semiconductor supremacy, will sequencing supremacy be next? Today, investors are ambivalent to publicly traded sequencing companies. The negative story is compelling: growth is slowing or limited, utility is plateauing… Today, few believe in the positive story - that reading the code of life is a key technological development that will revolutionize industry.

—Andrew Hui

Sequencingv3

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1. Sequencing is taking the same evolutionary path as semiconductors

2. Falling DNA sequencing costs unlock greater economic upside

3. Sequencing is key to enabling a biological paradigm shift

4. The value chain of sequencing has matured as sequencing costs have come down

5. Sequencing design space revolves around molecules and signal type

6. Enhancing clinical utility of the genome depends on the quality of datasets

7. The application layer has been the golden goose of the sequencing market

8. Sequencing is at a “strategic inflection point”

9. 10x technology factors will continue to drive value of the sequencing market forward

10. The next geopolitical battleground will be sequencers

11. Genomic data is the key to winning the biotech revolution

Disclaimer: The information in this post is not intended to be and does not constitute investment or financial advice. You should not make any decision based on the information presented without conducting independent due diligence.

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I’ve been thematically interested in security since Crowdstrike went public (I know, a little late to the game). There are many parallels between how the cybersecurity industry evolved and where the current biosecurity industry is.

A big catalyst was the exponential growth of computational technology in the world economy, and the dual-use nature of that. Biotechnology today sits at similar early innings: our ability to engineer and deploy biothreats is exponentially easier thanks to innovations in biotechnology.

The pandemic was a call on needing better biosecurity. However, conventional thought seems to think the government needs to be the one that underwrites it as a public good. And I don’t think so. It can and will be provided by the private sector.

—Andrew Hui

You can find the thesis in the PDF attached or within this post itself. Do let me know what your thoughts are in the comments, I am looking forward.

Biosecurity V1

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1. There is a rise in novel infections which creates more advanced persistent threats

2. Security growth needs to be parallel to the slope of the biotechnology curve

3. Value creation in biosecurity will be found in the security value chain

4. An effective response requires good monitoring

5. Incident response is the tip of the biosecurity spear

6. Endpoint security will come from using advances in diagnostic technology

7. We can learn lessons from the history of firewalls to build biological firewalls

8. The Crowdstrike Playbook: The more data you have, the better you are

9. The endgame is biosecurity ecosystem control

10. Predicting rain doesn’t count, building arks does

Disclaimer: The information in this post is not intended to be and does not constitute investment or financial advice. You should not make any decision based on the information presented without conducting independent due diligence.

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As an amateur camper, I must confess I have never run into a bear before. I’ve seen more financial bears, and they’re surely scarier than a real bear. Today, we’re seeing one right now in the biotech industry.

It is doom and gloom season, and for good reason. Portfolios are being shredded, companies are being destroyed, and careers are uncertain. Unlike a real bear, we can’t pull out the bear spray and yell at this one.

As pessimism has gotten worse over the decline of the industry in the last 5 years, today is a great time to look at the bear. Avoiding bears preserves wealth, but buying great companies in a bear market, given the great potential outcomes from biotech, is very profitable.

—Andrew Hui

You can find the thesis in the PDF attached or within this post itself. Do let me know what your thoughts are in the comments, I am looking forward.

Biotech Bear Market V2

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1. The anatomy of bubble.com

2. Biotech today is the inversion of bubble.com

3. What is the market mood? Depressed.

4. Skepticism calls for optimism when pessimism is excessive

5. The market thinks biotech will disappear, do you agree?

6. By watching the bear, we can observe the points that signal the market can only get better

7. The fundamentals of biotech have continuously improved while valuations have traded down

8. Today is the age of national capitalism

9. The new FDA is all about being fast and furious

10. Innovation is an imperative for developed economies

11. Regeneron has lived through multiple market moods and has delivered a 3000x return since IPO

12. If you don’t do macro, macro does you

Disclaimer: The information in this post is not intended to be and does not constitute investment or financial advice. You should not make any decision based on the information presented without conducting independent due diligence.

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So I’ve been browsing r/Biotech lately (thank you, Alexis Ohanian) and the homies are depressed. I’m sure we know people that went into the biology with a dream… and we ended up with many PhDs, so little academic positions, and now, so little biotech positions.

The story of biotech is the story of a cycle. Company formation is tied to the availability of funds. So time of easy money, excess company creation follows; during times of tight money, Darwinian selection, and bad companies die off.

Well… opportunity arises from every adversity, and biotech is no exception. Great companies and technologies are being punished along with the unsophisticated and incompetent teams. This thesis is a call to view the adversity biotech as a buying opportunity to support the companies and technologies of the future.

—Andrew Hui

You can find the thesis in the PDF attached or within this post itself. Do let me know what your thoughts are in the comments, I am looking forward.

Optionality V2

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1. Biotech cycles between platforms and assets

2. Cycles are a product of reflexive loops

3. Price reflects narratives and corrections undervalue optionality

4. Underpriced optionality only occurs in companies with unknowable and unknown futures

5. A framework for understanding optionality

6. Biotech companies are in a cyclical downturn with an unknowable and unknown future

7. “Transformational” advances have been punished for failing to live up to the hype

8. Knowing the strike conditions of an option is valuable

9. But not all optionality creates value

10. In conclusion

Before you go…

If you’ve got any thoughts, questions, or feedback, please drop me a line - I would love to chat! You can find me on X at @backshui or email (andrewhui65 [at] gmail).

If you are interested please subscribe. I will be counting on you to influence what I research…

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WTF happened to biotech? I’ve been fascinated by the increasing reliance on third parties in the development of biotech assets. The modern “biotech company” can just be an email address managing a project. Just sign contracts with a bunch of contract organizations and they’ll get the job done for you.

Is the dream of building a new big pharma company dead? The dream ushered in by the success of Genentech. This thesis is an exploration of the biotech system’s quest for capital efficiency. And more curiously, will it change?

—Andrew Hui

Biotech Efficiency V3

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1. Biotech is the business of outsourcing your business

2. Contract research is the toll bridge of biotech

3. Why outsource? You got to go fast

4. You need to go fast because time is limited

5. You either move fast or go bankrupt

6. The system incentivizes efficiency

7. Efficiency manifests in how the market rewards companies

8. The system will optimize for speed and efficiency

9. The picks and shovels of efficiency will be rewarded

10. Where to invest?

Before you go…

If you’ve got any thoughts, questions, or feedback, please drop me a line - I would love to chat! You can find me on X at @backshui or email (andrewhui65 [at] gmail).

If you are interested please subscribe. I will be counting on you to influence what I research…

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I graduated in 2021 and set out to build a biotech company. Truly a period of good times: the alt protein scene was booming (shoutout to Beyond), investment dollars were stacking up (thanks COVID), and being a young founder was all the hype (still is).

I wrote this piece almost as a form of therapy to reflect when shutting down my biotech company. In hindsight, our team made poor decisions led by venture incentives that took us down a poor path. We built everything to optimize for the next round and not longer-term durability. The ZIRP era was good until the music stopped.

This thesis is a review of the biotech business, how it functions, the inefficiencies it creates, and how to take advantage of them.

—Andrew Hui

You can find the thesis in the PDF attached or within this post itself. Do let me know what your thoughts are in the comments, I am looking forward.

Special Opportunities V1

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1. Biotech companies are high-sharpe ratio businesses

2. High-sharpe ratio businesses rely on venture capital

3. Most technologies and companies cannot be venture scaled

4. Reliance on venture capital undervalues biotech IP

5. Bad structural incentives further undervalues IP

6. From the late Charlie Munger…

7. Don’t make venture assumptions because you think you have to…

8. Venture incentives ignore good economic outcomes and set up structural weakness

9. Proper structures and incentives unlock value

10. Where to invest in biotech?

Before you go…

If you’ve got any thoughts, questions, or feedback, please drop me a line - I would love to chat! You can find me on X at @backshui or email (andrewhui65 [at] gmail).

Every week, I will publish a new thesis digging into an underrated theme that I find interesting. A teaser for the next piece in the pipeline…

If you are interested please subscribe. I will be counting on you to influence what I research…

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