D.A. Wallach Explains Why Biotech VC Is So Different

Key Takeaways Copied to clipboard!

• Biotech investing is fundamentally different from traditional tech VC because it involves pricing options based on extremely low probabilities of success (e.g., 5% for small molecules) over very long time horizons.  Copied to clipboard!
• Deal sourcing in biotech VC is often easier than in tech due to a scarcity of capital relative to the caliber of academic ideas, but the critical challenge is bridging the 'valley of death' from academic concept to commercial product.  Copied to clipboard!
• The US drug pricing system, which offers a large profit bounty via legalized monopolies (patents), is the primary driver for pharmaceutical innovation globally, and lowering this bounty would reduce the total pool of money available for drug development.  Copied to clipboard!

Segments Expand All Collapse All

Guest’s Career Transition

Copied to clipboard!

(00:05:37)

• Key Takeaway: D.A. Wallach’s career path transitioned from musician to VC via an early investment in Spotify, leading to an interest in healthcare after investing in telemedicine.
• Summary: Wallach views his current role as being a ‘record producer for scientists,’ drawing a parallel between combining art and commerce in music and combining medicine and capitalism in healthcare. His entry into VC was through a successful early investment in Spotify, which sparked his interest in the venture world. A subsequent investment in the telemedicine startup Doctor on Demand opened his eyes to the complexities of the U.S. healthcare system.

Biotech vs. Tech Investing

Copied to clipboard!

(00:08:13)

• Key Takeaway: Biotech investing relies on pricing options based on ultimate potential scale times very low probabilities of success, unlike tech where traction metrics are more immediate.
• Summary: Typical biotech companies are valued as a ‘bag of options,’ where success probabilities are inherently low (e.g., 5% for small molecules to FDA approval). A good biotech investor needs a higher batting average than a tech investor, though the magnitude of wins is generally lower. This contrasts with tech, where success often follows a clearer power law distribution with larger outlier wins.

Sourcing Biotech Opportunities

Copied to clipboard!

(00:11:04)

• Key Takeaway: Biotech deal sourcing is easier than in saturated tech markets because there is less capital chasing a high volume of good ideas originating from university research infrastructure.
• Summary: The biotech venture market historically had a scarcity of capital relative to the quality of ideas, making sourcing easier than in the crowded software space. These ideas primarily emerge from the US university and research infrastructure, creating a ‘valley of death’ in translation. Large pharmaceutical companies specialize in this translational work, which is difficult for academic inventors to manage alone.

Tech Bio vs. Traditional VC

Copied to clipboard!

(00:15:29)

• Key Takeaway: Biotech values ‘gray hair’ and deep experience due to the high cost and commitment of clinical programs, contrasting with the tech industry’s ‘fail fast’ ethos.
• Summary: Unlike tech, where pivoting is easy, a biotech clinical program commitment costs tens of millions of dollars, making experienced founders highly valued. The ’tech bio’ movement hypothesizes that young, clever founders can disrupt the industry, partly due to new infrastructure like CROs and the advent of AI. However, proving AI’s predictive power requires billions spent on clinical trials, making current claims speculative.

AI’s Role in Drug Discovery

Copied to clipboard!

(00:21:10)

• Key Takeaway: While AI like AlphaFold offers genuine breakthroughs in fundamental science, its immediate impact on drug development is limited because the primary bottleneck remains expensive, time-consuming human clinical trials.
• Summary: AI is amazing in life sciences, exemplified by breakthroughs like AlphaFold predicting protein structures, which is fundamental to drug discovery. However, most current AI tools primarily feed more ideas into the top of the development funnel. The core challenge is the necessity of testing drugs in living human beings to prove safety and efficacy, a process AI cannot yet fully simulate.

Regulatory Hurdles in Drug Approval

Copied to clipboard!

(00:25:39)

• Key Takeaway: The FDA’s high bar for proving both safety and efficacy is a major time and cost factor, though regulatory standards could be lowered, as is occurring in China to boost productivity.
• Summary: The only way to confirm a drug’s safety and effectiveness is through human trials, which are inherently time-consuming and expensive, regardless of regulatory changes. While lowering the FDA bar could speed things up, the current system prioritizes patient trust in proven safety and efficacy. China is deliberately moving its regulatory environment to approve more drugs faster to gain a structural advantage.

US vs. China Biotech Competition

Copied to clipboard!

(00:31:11)

• Key Takeaway: China is structurally positioned to become the dominant force in biotechnology over the next two decades due to regulatory efficiency, talent repatriation, and higher volume clinical trial capacity.
• Summary: China holds significant advantages in drug development speed, including regulatory efficiency and the return of highly trained scientific talent educated in the US. US companies are increasingly outsourcing research and clinical development processes to Chinese organizations. Trust in Chinese clinical trial data has increased significantly after successful replication of key findings in Western trials.

Alpha in Public Biotech Investing

Copied to clipboard!

(00:34:05)

• Key Takeaway: Active investors can generate alpha in publicly traded biotech stocks because specialized firms with PhD-level expertise can accurately value companies where generalists often follow during sector rotations.
• Summary: Unlike much of the public equity market, active managers consistently demonstrate alpha in biotech due to the need for deep scientific analysis to assess value and success probability. Generalist investors often follow the lead of these specialists, driving sector rotations that impact funding for smaller companies. The recent biotech downturn was caused by high discount rates from rising interest rates combined with generalists exiting the sector.

Incentives and Drug Pricing

Copied to clipboard!

(00:37:41)

• Key Takeaway: The high price of drugs in the US is a direct consequence of the US market serving as the primary profit pool that incentivizes global pharmaceutical innovation via legalized monopolies (patents).
• Summary: The US market offers the largest bounty for drug development, driven by a societal commitment to access advanced drugs first, which results in higher domestic prices compared to countries where governments negotiate prices. The size of this profit pool, dictated by patent law, determines the level of innovation that occurs globally. Shortening patent life or imposing strict price controls would reduce this incentive, leading to less drug development.

Trust in Scientific Expertise

Copied to clipboard!

(00:41:11)

• Key Takeaway: Erosion of public trust in scientific expertise stems partly from poor communication during crises like COVID-19, necessitating greater transparency from scientists to maintain the industry’s societal permission to exist.
• Summary: Miscommunication regarding data, such as mask efficacy or vaccine data presentation during COVID-19, understandably eroded public trust in scientific institutions. Medicine is currently on a long journey from being ‘witchcraft’ to a true science, evidenced by many common practices lacking rigorous evidence. Transparent communication from scientists is crucial to engender the trust required for the biotech industry’s continued existence.

Patient Autonomy vs. Socialized Costs

Copied to clipboard!

(00:44:37)

• Key Takeaway: Patients should ultimately have almost all say in their medical treatment decisions, but when medical costs are socialized, standards must exist regarding what care is appropriate for collective funding.
• Summary: Physicians should function as consultants supporting the patient’s final decision, as it is their body. However, when society socializes medical costs, there is a need for agreed-upon standards for appropriate expenditures. Private insurance companies are viewed as adding almost zero value to the US healthcare system by making decisions about appropriate medical care.

AI Impact on Music Creation

Copied to clipboard!

(00:46:21)

• Key Takeaway: While AI will generate original music, true artistic expression requires deep craft knowledge, as relying solely on language prompts inherently erodes the resolution and expansiveness of musical communication.
• Summary: Musicians feel anxiety about AI, similar to artists during the rise of Spotify, though AI is expected to increase overall recorded music revenue. Artists will use AI tools to create original and cool outputs, as music is fundamentally communication. However, separating craft (like mastering scales on a piano) from creation limits the nuance and options available to the artist compared to deep instrumental knowledge.