Eli Lilly invests $2.75 billion in British Silicon Intelligence, AI-driven drug development. Is the "GPT Moment" here?

Source: Geek Park

Author: Hu Lin Wu Wang

Another traditional industry has officially “fallen in love with AI.”

On March 29, local time, American pharmaceutical giant Eli Lilly announced a strategic partnership with Hong Kong-listed AI pharmaceutical company Insilico Medicine, with an upfront payment of $115 million, plus subsequent milestone payments, bringing the potential total value to $2.75 billion, along with future sales tiered royalties.

This number made the entire industry pause for a second—has the “GPT moment” for AI pharmaceuticals arrived?

01 AI Drug Development, from “Story” to “Real Money”

Before today, the concept of AI drug discovery felt more like a story that has been repeatedly told but never concluded. Startups securing funding, big companies entering the field, academic endorsements… But every time someone asked, “Have you really produced a drug for patients?” the answer was always ambiguous.

This money from Eli Lilly represents a clear shift in stance.

In fact, Eli Lilly is also accelerating its “AI transformation.”

At the J.P. Morgan Healthcare Conference in March, Eli Lilly announced a $1 billion joint innovation AI laboratory with NVIDIA, specifically aimed at addressing long-standing challenges in the pharmaceutical field. In the same month, NVIDIA partnered with Novo Nordisk to accelerate drug discovery using the Gefion sovereign AI supercomputer.

And that’s not all. In February, Takeda Pharmaceuticals signed a collaboration worth over $1.7 billion with AI company Iambic Therapeutics, aiming to discover new drugs for cancer and other diseases using AI. On March 27, Quotient Sciences and Intrepid Labs announced a long-term partnership to introduce the machine learning model ANDROMEDA into early drug development.

This is not an isolated instance; it’s a collective bet. As 2026 begins, the pharmaceutical industry has seen a flurry of major AI platform deals, with Eli Lilly, Sanofi, Novo Nordisk, Bayer… almost every top pharmaceutical company is rushing to sign contracts.

Industry analysts have more concrete figures: the AI drug discovery market is projected to be worth approximately $2.9 billion by 2025, expected to reach $5.1 billion by 2026, and exceed $13.4 billion by 2035.

However, while there is a lot of hot money, it does not mean that problems disappear.

02 How to Use AI to Design “New Molecules”?

Insilico Medicine is not a new company.

Founded by a Chinese scientist and headquartered in Hong Kong, it is one of the few companies that has truly advanced AI-generated drug molecules into clinical stages. Its core technology involves using generative AI to directly “design” new molecular structures rather than just screening existing compound libraries—this represents a fundamental difference in the technical approach.

The traditional drug discovery process typically goes like this: Identify targets → repeatedly screen millions of known compounds → find candidate molecules → lengthy optimization. This process generally takes over a decade and costs billions of dollars.

Insilico’s approach is somewhat like “drawing a key from scratch”—directly telling the AI, “This is what the lock looks like, you design a key that can open it.” Its end-to-end platform Pharma.AI encompasses three core steps: target discovery, molecular generation, and clinical outcome prediction, with the company claiming to have compressed some drug discovery cycles to under 18 months.

The CEO of Insilico stated bluntly: “The only company stronger than us in AI is Eli Lilly itself; no other company comes close.”

This sounds rather arrogant. But the fact that Eli Lilly is willing to pay this price is in itself a form of endorsement.

What Eli Lilly needs is not just an AI tool but a “production line” that can continuously generate drug candidates.

03 The $2.75 Billion Deal

However, to understand this deal, one must first grasp its structure.

The $115 million upfront payment is real money that is happening today, the kind that gets deposited into accounts. But the remaining over $2.6 billion consists of “milestone payments”—which will only be disbursed in phases once Insilico’s AI model successfully produces validated targets and candidate molecules that enter human trials and even complete clinical trials.

It can be viewed as a structure that uses “potential value caps” to express strategic intent while testing actual capabilities with “upfront investments.” For Eli Lilly, its balance sheet won’t immediately bear the pressure of $2.75 billion; for Insilico, every milestone payment acts as a public report card.

The industry’s assessment of this transaction structure is quite unified: it limits Eli Lilly’s direct risk while providing Insilico with the strongest commercial incentive—if you don’t deliver, you won’t get paid.

But therein lies the problem.

Drugs discovered by AI still ultimately have to pass human clinical trials. The failure rate in clinical trials is dishearteningly high across the pharmaceutical industry—approximately 90% of candidate drugs do not survive Phase II trials. Whether AI-generated molecules can truly break this curse still lacks sufficient data for an answer.

One industry observer’s judgment seems relatively fair: “The prediction for 2026 is that validation and disappointment will each account for about half. The field has moved from the speculation phase to early clinical validation, but the gap between promises and performance remains large.”

Without drugs ultimately reaching the market and receiving regulatory approval, the entire field of AI drug discovery is still in a very lengthy “proof of concept” stage.

No amount of large contracts can substitute for this outcome.

04 AI Attempts in Traditional Industries

When Eli Lilly decided to integrate AI into its core strategy rather than just the lab budget, the significance of this decision has transcended a mere business contract.

Looking back, one of the most apparent trends in the AI industry over the past two years has been “vertical penetration”—the capabilities of large models sinking into various specialized fields, from code generation and legal documentation to now molecular design. The pharmaceutical industry, often characterized as conservative, heavily regulated, and with extremely long R&D cycles, is theoretically one of the slowest sectors for AI penetration.

But the signals now are clear: the most conservative money has begun to flow.

Eli Lilly’s choice also has deeper industrial logic. Semaglutide has taken Novo Nordisk to the pinnacle of global pharmaceuticals, and Eli Lilly’s tirzepatide has also achieved great success in the weight loss market. This “GLP-1 war” has taught all pharmaceutical companies one thing: whoever finds the next “target” first will win the next decade.

And AI is currently the most likely tool to accelerate this “finding” process.

Insilico’s $2.75 billion today is less a transaction than an entry ticket—it announces to the entire industry that AI drug discovery has evolved from “research curiosity” to “commercial reality.”

In the next two to three years, if AI-discovered candidate molecules can demonstrate statistically significant advantages in clinical settings, then this “AI drug revolution” will truly have begun. If the molecules entering clinical trials still fail with traditional probabilities, the industry will undergo a cooling period, the trading frenzy will diminish, and Insilico will face real challenges.

No one knows the outcome.

But Eli Lilly’s $115 million check today is the most expensive vote so far.