Biotech Investing: Navigating Low Probabilities, China's Rise, and AI's Limits

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Original Title: D.A. Wallach Explains Why Biotech VC Is So Different
Biotech Investing: Navigating Low Probabilities, China's Rise, and AI's Limits - Episode Image

TL;DR

  • Biotech investing requires managing extremely low probabilities of success (5% for small molecules), necessitating portfolio construction that accounts for individual project unlikelihood to yield profitable outcomes.
  • The "valley of death" in biotech, the transition from academic discovery to commercial product, requires specialized translational expertise that large pharmaceutical companies possess and startups often lack.
  • China holds a significant structural advantage in global biotech due to faster clinical trial execution, a growing talent pool returning from the US, and deliberate regulatory acceleration.
  • The US drug pricing model, which rewards innovation through a large bounty, necessitates higher prices than other countries that actively negotiate drug costs and limit access.
  • Biotech's public market success hinges on generalist investors, whose sector rotation significantly impacts IPOs and funding for clinical trials, despite specialist firms' deep scientific expertise.
  • The transition from music to biotech investing shares parallels in managing creative endeavors with commercial viability and navigating the uncertainty of identifying future successes.
  • The core bottleneck in drug development remains human clinical trials, which are time-consuming and expensive, and current AI advancements primarily enhance the top of the idea funnel without solving this fundamental constraint.

Deep Dive

Biotech venture capital presents a unique investment paradigm characterized by extreme uncertainty and long development timelines, where success hinges on navigating low probability outcomes rather than predictable growth metrics. This necessitates a distinct analytical approach focused on the translation of scientific breakthroughs into viable commercial products, a process that demands specialized expertise and patient capital, and where China is increasingly poised to become a dominant global player due to regulatory advantages and a burgeoning talent pool.

The core challenge in biotech investing lies in assessing the potential of early-stage scientific discoveries, where the probability of a drug progressing from initial concept to FDA approval is remarkably low, often around 5% for small molecules. This necessitates a portfolio strategy that embraces a power-law distribution of returns, similar to tech, but with potentially lower magnitudes of upside per individual win. Unlike software companies with measurable traction like client acquisition and churn rates, biotech investments are fundamentally options on future therapeutic successes, with valuations heavily influenced by potential market scale multiplied by an uncertain probability of success. This inherent uncertainty, coupled with the lengthy development cycles, requires investors to possess deep scientific understanding and a long-term perspective, often favoring experienced professionals with a history of navigating failures.

The landscape of biotech innovation is also being shaped by a debate between traditional industry veterans and a newer wave of "tech bio" investors. The latter, often younger founders from Silicon Valley, hypothesize that AI and cloud-like infrastructure will democratize drug development, allowing for agile innovation akin to the tech sector. However, the prevailing view among established biotech investors is that the industry’s complexity and the sheer cost and time required for clinical trials -- approximately $30-40 million and often a decade or more -- still favor experienced individuals who understand the rigorous, iterative process of proving drug safety and efficacy in human beings. While AI shows promise in accelerating early-stage discovery, the ultimate bottleneck remains the human clinical trial phase, a process that cannot be fully simulated and where regulatory hurdles, though potentially streamlined in regions like China, still demand significant time and capital.

Furthermore, China is emerging as a significant force in global biotechnology, presenting a structural shift with distinct advantages. Its regulatory environment is becoming more efficient, enabling faster and higher-volume clinical trials. This is attracting talent previously educated in the US and is increasingly leading US companies to outsource research and clinical development processes to Chinese entities. While direct investment in China poses challenges for those unfamiliar with the language and market nuances, the trend towards globalized biotech development suggests that quality and data from Chinese trials are gaining credibility, potentially leveling the playing field for international markets. This dynamic, alongside the high cost of drug development in the US, which is partly subsidized by a willingness to pay premium prices for early access to novel therapies, creates a complex global ecosystem where innovation and market access are intricately linked to economic and regulatory choices.

The financial incentives driving drug development are heavily skewed by the US market, which offers the largest potential profit pool through a system that prioritizes early access to new medicines. This is enabled by a legalized monopoly granted through patent law, a construct that could be altered by shortening patent lives or by governments directly negotiating prices, thereby influencing the pace and scale of future drug development. The public's trust in the pharmaceutical industry, however, is a critical factor, and it has been eroded by communication breakdowns and a perception that scientific expertise is not always transparently applied. Rebuilding this trust requires a commitment to rigorous evidence-based practices and clearer communication from scientists, policymakers, and academia. Ultimately, while AI may offer new tools, the fundamental challenges of scientific validation, regulatory approval, and market economics will continue to define the biotech investment landscape, with China playing an increasingly pivotal role.

Action Items

  • Audit biotech investment process: Identify 3-5 key heuristics for evaluating drug candidates beyond scientific merit (ref: probability of success, market potential).
  • Create framework for evaluating translational work: Define 5 criteria for assessing a university research idea's potential to become a commercial product.
  • Track 3-5 Chinese biotech companies: Monitor their clinical trial progress and regulatory approvals to assess global market impact.
  • Measure US vs. China clinical trial efficiency: Calculate average trial duration and cost for 5-10 comparable drug candidates.
  • Analyze regulatory pathways: Compare FDA approval timelines and data requirements with those in China for 3-5 therapeutic areas.

Related Episodes

Key Quotes

"I tell people now my job is like being a record producer for scientists so there's a little bit of a parallel there but the other is that I think there's a unique challenge in music to combining art and commerce and in healthcare there's a similar parallel challenge which is how do you combine medicine and capitalism which don't naturally go together very well."

D.A. Wallach draws a parallel between his past career as a musician and his current role in biotech investing, highlighting the shared challenge of integrating creative or scientific endeavors with commercial realities. Wallach suggests that both fields require navigating the complex relationship between art and commerce, or in the case of healthcare, medicine and capitalism.

"The base case is like a 5 probability of success from the original idea to an FDA approval and a marketed drug. Now you get to a higher sort of prior probability with antibodies or so called biologics other classes of drugs that are intrinsically more likely to work than small molecules but still in every case you're dealing with very low probabilities of success."

D.A. Wallach explains the inherent risk in biotech investing, noting the low probability of success for drug candidates moving from initial concept to FDA approval. Wallach specifies that while certain drug types like antibodies may have a higher chance of success than small molecules, the overall likelihood of any individual project working remains low.

"The producer analogy makes a ton of sense and you know there are probably a lot of musicians who are really brilliant really great musicians but for whatever reason the lightning doesn't strike where they are or doesn't strike nearby and they don't take off prime many brilliant scientists etcetera but the path from brilliant science to commercial blockbuster can often i assume be tricky or dispiriting uh in many ways etcetera."

Joe Weisenthal acknowledges D.A. Wallach's analogy of a record producer for scientists, recognizing that many brilliant individuals, whether musicians or scientists, may not achieve commercial success. Weisenthal suggests that the journey from groundbreaking scientific discovery to a successful commercial product is often fraught with difficulty and discouragement.

"The challenge that's the so called valley of death that people sometimes talk about in our industry there are just an immense number of cool ideas if you go into any university in our country but such a small number of them is ever going to cross that chasm and part of that is that the expertise and the personnel required to do that translational work is not the same expertise that is required to do the inventing in the first place."

D.A. Wallach describes the "valley of death" in the biotech industry, where numerous promising ideas originating from universities struggle to transition into viable products. Wallach explains that this chasm exists because the skills needed for the initial invention are different from those required for the subsequent translational work to bring a product to market.

"The tragedy of our moment is that the only way to figure out if drugs are safe and effective is to try them in human beings living breathing human beings and that is extraordinarily time consuming and incredibly expensive financially."

D.A. Wallach highlights the significant challenges in drug development, stating that the necessity of testing drugs in human subjects to determine safety and efficacy is both time-consuming and financially burdensome. Wallach identifies this human testing phase as a critical bottleneck in bringing new therapies to market.

"I think the nuance with which one can communicate through music is a function of how many options you perceive in other words if you know the piano inside out you're aware of so many creative choices that are at your disposal at any given moment and if your ability to express yourself is squeezed down to what you can put into a natural language prompt now those musical ideas are having to pass through the medium of language to be realized and that inherently erodes the resolution and the expansiveness with which you can express yourself."

D.A. Wallach explains how a deep understanding of an instrument, like the piano, allows for a greater range of creative expression due to the awareness of numerous available options. Wallach posits that when musical ideas are filtered through language prompts for AI generation, the resolution and breadth of expression are inherently diminished.

Resources

External Resources

Books

  • "Spotify" by D.A. Wallach - Mentioned as the company D.A. Wallach first invested in, which sparked his interest in venture capital.

Articles & Papers

  • "Big Pharma’s Patent Cliff Puts China Front and Center" (Bloomberg.com) - Referenced as further reading related to the discussion on biotech and China.
  • "Novartis Strikes Deal With UK Biotech for Up To $1.7 Billion" (Bloomberg.com) - Referenced as further reading related to the discussion on biotech and China.

People

  • D.A. Wallach - Guest, biotech investor, and former lead singer of Chester French.
  • Milton Friedman - Economist, whose view on the FDA's role in drug approval was discussed.
  • Bernie Sanders - Politician, whose views on drug pricing and pharmaceutical profits were referenced.
  • Demis Hassabis - Mentioned for his work with DeepMind and AlphaFold, which won a Nobel Prize.
  • Sam Altman - Mentioned in relation to the promise of AI and its potential for drug discovery.
  • Brian Armstrong - Mentioned as someone D.A. Wallach cold-emailed to initiate an investment in Coinbase.
  • Tim - Friend of D.A. Wallach, with whom he discussed Chinese biotech.

Organizations & Institutions

  • Chester French - Former band of guest D.A. Wallach.
  • Time BioVentures - Company co-founded by D.A. Wallach.
  • Doctor on Demand - Telemedicine startup in which D.A. Wallach made an early investment.
  • SpaceX - Startup D.A. Wallach was involved with.
  • Ripple - Startup D.A. Wallach was involved with.
  • Coinbase - Company D.A. Wallach invested in after cold-emailing Brian Armstrong.
  • Palantir - Company mentioned in relation to AI and its impact on workers.
  • IBM - Company mentioned for its role in helping AI access data.
  • Odoo - Business software platform discussed as an all-in-one solution.
  • Wayfair - Online retailer mentioned for home goods and Black Friday deals.
  • Kroger - Grocery store now available on DoorDash for delivery.
  • Lowe's - Retailer mentioned for holiday savings on tools.
  • Rubrik - Company mentioned for its AI agent monitoring platform.
  • DeepMind - Mentioned for AlphaFold's breakthrough in protein structure prediction.
  • Stanford University - Mentioned in the context of young founders in biotech.
  • The Federal Reserve - Mentioned for sponsoring the Fed Challenge competition.

Websites & Online Resources

  • oddlots@bloomberg.net - Email address for submitting questions for the Odd Lots podcast AMA episode.
  • discord.gg/oddlots - Discord server for the Odd Lots podcast.
  • bloomberg.com/subscriptions/oddlots - Subscription page for the Odd Lots newsletter.
  • omnystudio.com/listener - Website for listener privacy information.
  • screenfortype1.com - Website mentioned for learning more about screening for type 1 diabetes.
  • odoo.com - Website to try Odoo for free.
  • wayfair.com - Website for Wayfair's Black Friday deals.
  • duo.com - Website for Cisco Duo's fishing resistance solutions.
  • xiidra.com - Website for information on Xiidra dry eye treatment.
  • cvs.com - Website for CVS.

Podcasts & Audio

  • Odd Lots - The podcast where this discussion is taking place.
  • Comedown with Aaron and Carissa - Podcast mentioned by Aaron Andrews.

Other Resources

  • AI (Artificial Intelligence) - Discussed extensively in relation to its impact on various industries, including biotech, music, and work.
  • Biotech VC (Venture Capital) - Discussed as a distinct area of venture capital with unique characteristics.
  • Type 1 Diabetes - Mentioned in the context of screening and family risk.
  • Black Friday Sale - Promotional event mentioned by Wayfair.
  • Healthcare Episodes - Mentioned as a topic the podcast intends to cover more.
  • Chinese Biotech - Discussed as a growing area with significant advantages.
  • Small Molecules - A major area of drug development with a low probability of success.
  • Antibodies/Biologics - Classes of drugs with a higher probability of success than small molecules.
  • Power Law Distribution - A concept in investing where a few companies generate most of the returns.
  • Valley of Death - The challenging phase of translating academic concepts into marketable products.
  • Contract Research Organization (CRO) - Organizations that provide outsourced services for drug development.
  • Tech Bio - A movement of Silicon Valley tech investors entering the biotech space.
  • AlphaFold - A DeepMind discovery using machine learning to predict protein structures.
  • Gemini - AI model mentioned as being used by the speaker.
  • Chat GPT - AI model previously used by the speaker.
  • Clinical Trials - Discussed as a time-consuming and expensive process for drug approval.
  • FDA (Food and Drug Administration) - Regulatory body discussed in relation to drug approval standards.
  • Milton Friedman's View on FDA - The idea that the FDA should only assess safety, not efficacy.
  • Supplement Industry - Mentioned as an example of a market with less regulatory oversight.
  • Patent Law - Discussed as a mechanism that creates legalized monopolies for drug companies.
  • Masks - Mentioned in the context of early COVID-19 communication.
  • Vaccine Efficacy - Discussed in relation to transparency in data presentation.
  • Witchcraft and Sorcery - Historical context for the origins of medicine.
  • Drug Ads on TV - Discussed as a cultural difference in the US healthcare system.
  • Private Insurance Industry - Critiqued for adding little value to the US healthcare system.
  • AI Generated Music - Discussed as a potential impact on musicians.
  • Spotify - Mentioned as a platform that increased revenue for the recorded music business.
  • Scales on the Piano - Used as an analogy for the craft required to master an instrument.
  • Natural Language Prompt - Mentioned as a medium through which musical ideas are realized with AI.
  • Moral Hazard - A concept mentioned in relation to a previous podcast guest.
  • Dinosaur Bias - The assumption that legacy industries are outdated and can be improved by younger tech-focused individuals.
  • Fed Challenge - A high school economics competition sponsored by the Federal Reserve.
  • Greenspan - Former Chairman of the Federal Reserve, seen by the speaker in high school.
  • Lottery Tickets - Used as an analogy for the high uncertainty and potential rewards in biotech investing.
  • Commercial Hit - The goal for bands and companies in their respective industries.
  • Dodge - A company mentioned as an example of a failed premise.

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