Nov 14, 2025 · 1h 1m · a16z
The Brutal Truth About Biotech: Why $2B Per Drug Is Killing Innovation
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In this episode of The a16z Show, host Jorge Conde joins biotech experts Lada Nuzhna and Elliot Hershberg to analyze the structural, economic, and regulatory challenges facing biotech, while highlighting how novel AI tools, emerging drug modalities, and global competition are reshaping the future of healthcare.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. How this is scored →
The host as informed peer 5.5 Guest teaching 5.8 Guest disagreement 1.7 The host pushing back 2.4
speaking balance: gold is the host, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 21:39 Stanford Startup Beaten to Clinic by China
Lada directly challenges Elliot's optimistic framing that US zero-to-one invention provides an insulating moat, giving a concrete counterexample where Stanford Professor Irvin Weissman's cancer startup was beaten to the clinic by a Chinese competitor using an identical mechanism.
Hardest push from the host ▶ 19:57 Shortened Shelf Life of American InventionsHost Jorge Conde directly challenges Elliot's thesis that zero-to-one invention protects US biotech, arguing that fast-following global competitors drastically shrink the commercial half-life and exclusivity window of domestic breakthroughs.
Biggest teaching moment ▶ 52:24 Debunking First-Mover Advantage in Drug DiscoveryLada educates the host on the real mechanics of blockbuster drugs, dismantling the 'first-in-class' myth by highlighting how Humira succeeded as a third-to-market drug and how Pfizer misjudged patient appetite for injectable chronic therapies.
The host holds their own ▶ 48:26 Host's Regulatory Innovation FrameworkHost Jorge Conde demonstrates deep expertise by analyzing the market mechanics of orphan drug incentives versus chronic diseases, then detailing a concrete policy strategy to adopt global trial acceleration methods domestically.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | The host as informed peer | Guest teaching | Guest disagreement | The host pushing back | Why |
|---|---|---|---|---|---|---|
| The Macro Downturn vs. Scientific Progress: A Tale of Two Worlds | 4 | 5 | 1 | 1 | The host asks a broad state-of-the-union question to open the discussion. The guests explain the macro downturn, Eroom's law, EV-negative biotechs, and the paradox between depressed public valuations and rapid laboratory progress. | |
| Where Are the Trillion-Dollar Biotechs? Regulatory Realities | 6 | 5 | 1 | 2 | The host demonstrates strong familiarity by citing the XBI index and referencing the guest's written essay by title. Lada provides historical background on FDA regulatory expansion starting from the Thalidomide disaster through the AIDS crisis. | |
| Structural Bottlenecks and CRO Consolidation in Clinical Trials | 6 | 5 | 1 | 3 | Elliot breaks down how clinical trials are forced offshore and explains the structural entrenchment of consolidated CROs. The host synthesizes this into a focused argument on structural incentives versus pure technology or regulatory friction. | |
| Geopolitical Arbitrage: China's Clinical Trial and Regulatory Speed | 5 | 7 | 2 | 2 | Elliot delivers a historical timeline from 19th-century German dye makers to modern outsourced R&D geographic arbitrage. Lada details China's implied approval system and investigator-initiated trials that cut review timelines dramatically. | |
| America's Innovation Strategy: Zero-to-One Inventions vs. Fast Followers | 7 | 6 | 4 | 6 | The host pushes back against Elliot's optimistic view on American zero-to-one innovation by noting China's fast execution dramatically shortens innovation half-lives. Lada then directly counters Elliot's premise with a concrete example of a Stanford professor's startup getting beaten to the clinic by a Chinese competitor. | |
| Artificial Intelligence in Drug Discovery: Real Bottlenecks vs. Hype | 5 | 6 | 2 | 2 | Lada critiques current AI efforts for focusing primarily on preclinical stages rather than Phase 2 efficacy failures. Elliot outlines the three main drivers of Eroom's law in clinical development. | |
| Molecular Design Capabilities and the 'Better Than the Beatles' Problem | 6 | 6 | 2 | 4 | The host tests Elliot's framework by asking whether molecular design is a major bottleneck or a minor issue. Elliot explains poly-specific design challenges while Lada highlights the 'Better Than the Beatles' problem using PCSK9 and Repatha. | |
| Longevity, Preventive Healthcare, and Insurance Incentive Alignment | 6 | 6 | 1 | 2 | The host connects the guest's writings on longevity to systemic healthcare models. Lada details how multi-payer churn before age 65 eliminates financial incentives for private insurers to fund preventive longevity treatments. | |
| Defining Aging Science: Biomarkers, Prevention, and Public Health | 5 | 6 | 1 | 1 | Lada explains the lack of aging biomarkers and surrogate endpoints, comparing health outcomes to caloric restriction trials in monkeys on Western diets versus Japanese population baselines. | |
| Magic Wand Regulatory Wishlist and Global Best Practices | 7 | 6 | 2 | 5 | Elliot cites Carl June and highlights per-patient trial cost inflation from $10k to $500k. The host offers a counter-perspective on Lada's common disease orphan drug idea and proposes adopting global trial best practices domestically. | |
| What Makes a Biotech Drug a Blockbuster? | 4 | 7 | 3 | 1 | Lada refutes standard industry dogma regarding first-mover advantage, using Humira and Pfizer's abandoned GLP-1 program to prove that success stems from bold indication choices rather than novel biology. | |
| Tackling Aging Through Modality Breakthroughs | 5 | 6 | 1 | 1 | Lada shares her stealth startup's focus on modality breakthroughs, drawing an analogy to Human Genome Project cost reductions. Elliot describes how re-bundling synthetic biology, genomics, and AI models creates new venture opportunities. | |
| Infrastructure Platforms vs. Modality Companies in Bio | 6 | 5 | 1 | 1 | Elliot frames the bio platform debate by comparing potential biotech infrastructure providers to Illumina and Nvidia. The host closes by outlining their investment thesis of placing orthogonal bets across both modalities and infrastructure. |
Statements from this episode (41)
Nuzhna: Everyone in biotech will use AI within five years
“Everyone will be using AI and biotech industry five years from now.”
Hershberg: Public biotech market contains an enormous amount of EV-negative companies
“We have an enormous amount of EV negative public companies.”
Hershberg: Biotech experienced a 7-8 month IPO drought
“There was a stretch of seven to eight months where there were no biotech IPOs”
Nuzhna: One-fifth of public biotechs traded at or below cash balances
“Earlier this year we had something like one-fifths of public biotechs trading at or below their cash balances.”
Nuzhna: Drug development costs exceed $2 billion per approval
“We now spend more than two billion dollars per approved drug.”
Nuzhna: Biotech drug development uniquely combines engineering and scientific risk
“Approving drugs is really hard. It's probably one of the hardest areas of deep tech broadly, because it takes not only on engineering risk, but also on scientific risk.”
Nuzhna: FDA regulation has continuously increased except during the AIDS crisis
“Since the birth of this industry, we only had increasing regulation over time. I think there was like only one time in history of biotech where we made it easier to develop and approve new drugs. And that was during the ACE crisis where AIDS patients were just…”
Nuzhna: Biotech regulatory requirements have continuously increased since industry inception
“Since the birth of this industry, we only had increasing regulation over time.”
Nuzhna: FDA mandatory efficacy testing stems from historical thalidomide crisis
“Since then FDA started to require not just safety, but also efficacy in the approval process.”
Hershberg: Zero Amplify portfolio companies are running first-in-human trials in US
“So we have three companies in the next 12 to 18 months that will be starting first in human trials. You know, guess how many are actually doing their first studies in the United States?”
Hershberg: Clinical research market consolidated into 12 primary providers
“So it actually turns out that there's been this enormous consolidation of the clinical research organization market that's come down to about a dozen providers who have each done roughly 40 acquisitions across 30 years.”
Hershberg: Biotech startups generate two-thirds of newly approved drugs
“Biotech startups now make two thirds of the drugs that go to market.”
Nuzhna: Investigator-initiated trials in China cut review timelines by 5x
“With investigator-initiated trials your view timelines are cut five to six X.”
Nuzhna: China leads global development in in vivo CAR-T and gene editing
“They are now leading in, in VivoC RTs, they are leading in gene editing and gene therapy, and partially due to this ability to do those investigator-initiated trials.”
Hershberg: Restricting US-China biotech transactions via BIOSECURE Act is net negative
“I do think that there's some nuance in terms of how we think about regulation for this, right? It's probably not biosecure where you are totally trying to restrict Relationships and transactions between the U S and China, because that's just sort of net negati…”
Nuzhna: Preclinical spending is a minor portion of drug development cost
“Most of it's spent is not in preclinical stage. It's spent in validating safety and efficacy in humans. It's spent on commercialization stage, which is what happens after phase three clinical trials.”
Nuzhna: Phase 2 efficacy trials have the highest drug development failure rate
“The highest failure rate right now is phase two, which is efficacy.”
Nuzhna: AI will solve open biology questions before predicting drug efficacy
“Many big bio problems and open questions will be solved with AI way before we can predict efficacy for drugs.”
Nuzhna: AI virtual cell models are near realization with existing data
“Virtual cells is actually not that far out. I think we have all the necessary data to generate something like that.”
Hershberg: Drug development alpha relies on proprietary datasets and modeling tools
“To actually make something more beautiful and more potent at this stage of the game, the alpha probably is in really interesting data sets, new modeling tools and capabilities.”
Nuzhna: New therapeutic modalities face a "better than the Beatles" bottleneck
“So I think many new modalities will be bottlenecked by the Beatles, better than the Beatles problem.”
Hershberg: AI biology platforms where the platform is the product remain compelling
“This is where I'm sort of an unequivocal platform bull still is that I think like one of the most exciting opportunities for AI and biology is this sort of world that we're going to where the platform is the product, right?”
Nuzhna: US multi-payer insurance system disincentivizes early preventive healthcare
“The payer that pays the most for diseases of aged population is Medicare which kicks in after 65. Before then we have a multi-payer system where patients Tend to rotate their insurance every few years. And so there's really not much incentive for someone to co…”
Nuzhna: Eli Lilly's Alzheimer's trial tests GLP-1s as broad aging treatments
“I think this month Lilly is reading out their semaglutide in Alzheimer's trial, which is to me is a real test of whether it's An aging drug or not because it's well outside of the metabolic spectrum of diseases.”
Nuzhna: Medicare refused coverage for GLP-1 drugs in obesity care
“Medicare refused to cover GLP-I ones for obesity care.”
Nuzhna: Lifespan-extending drugs in animals remain untested in humans
“I think regulation is lagging behind science. I think we have multiple drugs that extend lifespan in mice and monkeys that never been tested for lifespan indications in humans.”
Nuzhna: Medicine will treat aging before understanding its underlying mechanisms
“I think we would be able to treat aging before we understand how to measure it or what it is or why it happens.”
Nuzhna: Modern medical stack can eliminate heart attacks for current generation
“And it does seem like we kind of hit a point where actually like our generation shouldn't die of heart attacks. It seems like we have everything to prevent high cholesterol in people from, like you can take antibodies sRNAs, small molecules, sun gene editors. …”
Nuzhna: Caloric restriction is only proven lifespan extender in monkeys
“The only documented effect for lifespan that we have in monkeys is caloric restriction. We know that we can add about two and a half years to 25 year median lifespan in monkeys by calorically restricting them.”
Hershberg: Clinical trial costs per patient ballooned from $10,000 to $500,000
“So when George Yonkopoulos started Regeneron, it cost about 10,000 dollars per patient in trial. That's ballooned to 500,000 dollars.”
Nuzhna: US will remain the primary exit market for biotech companies
“And even if Chinese population will continue to grow, US will still remain the biggest market for biotech companies to exit at.”
Nuzhna: 50% of FDA drug approvals in 2024 were orphan drugs
“And today, 50% of drugs approved in twenty-twenty-four were all orphan drugs.”
Nuzhna: Humira succeeded as the first human monoclonal antibody, not first-to-market
“Humira was also not the first TNF-alpha antibody out there. It was like third to market, third TNF-alpha antibody to be approved, but it was the first human monoclonal antibody, one of the first ones to be approved. And all the previous ones were antibodies fr…”
Nuzhna: Biotech companies should avoid being contrarian on novel biological mechanisms
“And I think biology is like one of the areas where you really don't want to be contrarian. You don't want to be the only company pursuing some obscure mechanism. Usually you want to have some literature validation, but in both of these cases, it was either a b…”
Nuzhna: A GLP-1-style race is emerging for muscle loss drugs
“I think muscle is in a similar space right now where for a while people weren't treating sarcopenia as a real indication because it's sort of muscle loss in elderly, but there is now a similar race to JLP wants to go and develop drugs for muscle.”
Nuzhna: Biological breakthroughs stem from new modalities, not target discoveries
“Every time I think about where the biggest breakthroughs and successes in biology came from, it was always served from some type of technology or process or technique and rarely from like discovering a new target.”
Nuzhna: Treating aging with existing modalities is an uphill battle
“I think aging is in a somewhat similar space in that it's a massive multifactorial disease, and if we rely on existing modality approaches, it would just be an uphill battle to try and treat it.”
Hershberg: Re-bundling biotech tools into integrated platforms is the primary opportunity
“I think that in biotech, we're in this sort of moment where there's a lot of opportunity in re-bundling. The types of platforms that I see that I'm super excited about Are this composite of incredible synthetic biology and genomics tools plus modeling you know…”
Nuzhna: Bullish on gene editing, epigenetic editing, and extrahepatic LNP targeting
“I think we are starting to see light at the end of the tunnel with gene editing, epigenetic editing more tailored targeting approaches where no longer do our LNPs just go to the liver. We can now target HCCs, we can target kidney, we can target potentially bra…”
Hershberg: Certain funded AI biology firms do not plan to develop drugs
“There's a lot of AI and biology companies that are raising a lot of capital and some just have no aims to make drugs.”
Hershberg: Illumina grew next-generation sequencing sales from zero to over $10B
“So at one point Illumina sold exactly zero dot zero dollars of next generation sequencing technology to the industry, right? That turned into over ten billion dollars of sales and, you know, independent large listed companies where their cost of goods sold wer…”