Anthony Ao

Cross-border CGT strategist
Science → partnerships → market growth
APAC | Europe | MENA

[Naval @naval]

Software went from desktop-first to mobile-first, now going to agent-first.

[Alex Rives @alexrives]

Today we're announcing ESMFold2, an open scientific engine to power prediction, design, and discovery across protein biology.

The new model delivers state of the art performance on protein interactions, especially antibodies, a critical modality for therapeutics.

We have designed and validated miniprotein binders and single chain antibodies across five therapeutic targets that are important in cancer and immunology. We are seeing very high success rates, and affinities at levels consistent with therapeutic activity.

We’re also releasing an atlas of 6.8 billion proteins, and 1.1 billion predicted structures.

ESMFold2 is built on a state of the art language model that has been trained on billions of protein sequences.

A world model of protein biology emerges through language modeling.

We’ve used the techniques of mechanistic interpretability developed to understand large language models to understand the concepts ESM uses to represent proteins.

The model’s representation space has a compositional organization of features across scales, levels of complexity, and abstraction, that reflects and mirrors the understanding of protein biology developed through a century of empirical science.

This understanding emerges without prior knowledge, just from language modeling of protein sequences.

Language models are becoming a powerful substrate to understand and program biology.

The design of protein interactions is one of the most fundamental problems in biophysics, and has critical implications for the discovery of new medicines. A simple gradient based search with the model was able to discover high-affinity protein binders.

I'm excited by the potential this has to accelerate basic science and the understanding of proteins. And especially for the new avenues it opens up for therapeutic design and medicine.

[Anthropic @AnthropicAI]

We've raised $65 billion in Series H funding at a $965 billion post-money valuation, led by @AltimeterCap, Dragoneer, @Greenoaks, and @sequoia.

This investment will help us advance our research and expand our capacity to meet growing demand for Claude.

[Anthony Ao @cgtanthony]

@BioSignal

[Anthony Ao @cgtanthony]

The most aggressive bet in cell & gene therapy is being financed by a weight-loss drug.

$LLY has used $36B in GLP-1 cash flow to buy four different answers to genetic medicine's hardest problem: delivery.

Four deals. Four modalities.
Under 12 months.

🧵

[Anthony Ao @cgtanthony]

Full thesis — patent-cliff defenders, bear case, what to watch next — in this week's newsletter: https://t.co/7FxouzAPYQ

[Anthony Ao @cgtanthony]

The most aggressive bet in cell & gene therapy is being financed by a weight-loss drug.

$LLY has used $36B in GLP-1 cash flow to buy four different answers to genetic medicine's hardest problem: delivery.

Four deals. Four modalities.
Under 12 months.

🧵

[Anthony Ao @cgtanthony]

Fresh signal: $LLY's VERVE-102 Phase 1b data dropped 2 days ago.

Single infusion →
• Up to 88% PCSK9 reduction
• Up to 62% LDL-C reduction
• Durable 18 months
• No treatment-related SAEs

Phase 2 by end of 2026. First real evidence one of the four bets might land.

[Anthony Ao @cgtanthony]

https://t.co/kTw6pauOKb

[Anthony Ao @cgtanthony]

Eli Lilly just put $11B on the table on one bet: that the future of cell and gene therapy is in vivo.

Yesterday's $202M Engage Bio acquisition completed the set — and might be the most strategically important check of the four. 🧵

[Anthony Ao @cgtanthony]

The bigger pattern: Lilly is deploying GLP-1 cash into in vivo genetic medicines at a pace no other Big Pharma can match.

Coherent platform or four separate bets? That's the question I'm tracking.

Newsletter Monday. What should I cover? Reply below.