Inflection Point Reached: AI + Biopharma Achieves Dual Breakthrough in Deal-Making and Profitability

Apr 08, 2026 15:48 CST Updated 15:48

XtalPi

Computation-Driven Innovative Drug R&D Provider

March 30,Insilico MedicineEntered into a global licensing collaboration with Eli Lilly, with a total value of up to $2.75 billion, and the $115 million upfront payment set an industry record. In just the first quarter of 2026, Insilico Medicine reached multiple collaboration deals.

March 25,XtalPiRelease of Financial Report: First Annual Profit Achieved, Revenue of 802.6 Million Yuan in 2025, a Year-on-Year Increase of 201.2%, Annual Profit of 134.6 Million Yuan, Adjusted Net Profit of 258.2 Million Yuan.

The密集落地的BD交易与亮眼的财务数据，成为观察AI制药行业的关键窗口，AI制药已迎来从“概念验证”走向“商业落地”的临界点。

BD Deals Intensely Land, Leading Players Realize Commercial Value First

The first quarter of 2026,Insilico MedicineBecoming the most active "player" this quarter. In January, it reached three BD deals with Servier, Hengtai Bio, and Qilu Pharma, earning $150 million just in upfront payments. In February, it partnered with Chemshark in the fields of central nervous system and autoimmune diseases. In March, it initiated collaborations with Japan's ASKA Pharma, Yuanyi Bio, and Eli Lilly.

Among them, the deal with Eli Lilly triggered an antitrust review by the U.S. Federal Trade Commission (FTC) due to its large scale. Through this collaboration, Eli Lilly obtained the exclusive sales rights to a GLP-1 diabetes drug developed using Insilico Medicine's AI technology, with an upfront payment of $115 million and a total amount potentially reaching $2.75 billion. So far, the total value of Insilico Medicine's major collaborations has accumulated to nearly $7.5 billion.

(Image Source: Insilico Medicine Official Website)

Insilico Medicine's competitiveness lies in its integrated generative AI platform, Pharma.AI. By utilizing the Pharma.AI platform, it can reduce the time from target discovery to Pre-Clinical Candidate (PCC) confirmation from the traditional average of 4.5 years to 12-18 months, significantly improving the efficiency of drug development.

(Image Source: Insilico Medicine)

While actively advancing its internal self-developed pipeline, Insilico Medicine is also promoting the commercial implementation of the Pharma.AI platform through software licensing and joint R&D models. On March 29, Insilico Medicine released its first earnings report since going public: during the reporting period, the company's software business revenue increased by 23.8% year-on-year, the number of customers rose by 18.3%, and it has now covered 13 of the top 20 global pharmaceutical companies.

(Image Source: XtalPi)

XtalPiSimilarly, it delivered an excellent annual report card — achieving profitability for the first time, with revenue of 802.6 million yuan in 2025, a year-on-year increase of 201.2%, net profit of 134.6 million yuan, and adjusted net profit of 258.2 million yuan, becoming the first Hong Kong-listed company in the AI for Science field to achieve profitability.

The company has established partnerships with 17 of the top 20 global pharmaceutical companies. By 2025, over five novel drugs that it has contributed to discovering will announce clinical progress. These span multiple drug modalities, including small molecules, antibodies, peptides, nucleic acids, and molecular glues, through its AI-driven drug discovery platform, which has successfully secured new drug collaboration agreements.

From Tools to Foundation, Multinational Pharmaceutical Companies Fully Increase Investment

As domestic companies accelerate the exploration of business model diversification,Zhangjiang Pharm Valley multinational enterprises have also upgraded AI from a single-point tool to the underlying infrastructure of R&D and production systems.

As early as 2023,Eli LillyAndInsilico MedicineHave already reached a software licensing cooperation based on the AI platform. In November 2025, Insilico Medicine announced a strategic drug discovery collaboration with Eli Lilly. Insilico Medicine will utilize its Pharma.AI platform to generate, design, and optimize candidate compounds for the innovative targets agreed upon by both parties. Insilico Medicine is entitled to receive up to over 100 million US dollars in revenue from this collaboration, including upfront payments, R&D milestone payments, and tiered net sales royalties after future drug commercialization.

(Image Source: NVIDIA)

Now, Eli Lilly's layout in the AI pharmaceuticals field is in full swing. In early 2026, Eli Lilly and NVIDIA established a joint innovation lab, planning to jointly invest $1 billion over five years to build a continuous learning system that combines dry and wet experiments. Eli Lilly's AI pharmaceutical factory, LillyPod, has been put into operation, marking it as the world's first AI pharmaceutical factory operated by a pharmaceutical company.

(Image source: Roche)

RocheIt also accelerates the integration of AI into businesses such as drug discovery, development, manufacturing, and the delivery of healthcare solutions.March 2026,RocheAnnounced the expansion of its existing partnership with NVIDIA to deploy over 3,500 NVIDIA Blackwell G in hybrid cloud and on-premises environments across the U.S. and Europe.PU, building up to nowThe Largest GPU Cluster Publicly Disclosed in the Pharmaceutical Industry. According to publicly available information, this superThe computing platform spans the entire value chain: In the R&D field, the "Lab-in-the-Loop" model is enhanced through Nvidia's BioNeMo platform, bridging biological experiments with AI models.Type; In the manufacturing field, the Omniverse library is used to drive digital twin optimization processes; In the fields of diagnostics and digital pathology, accelerated computing is leveraged to gain insights from massive amounts of data.

PfizerSuccessively reached cooperation with AI pharmaceutical companies such as Adapsyn, XtalPi, Atomwise, and CytoReason, covering multiple fields including target discovery, small molecule drug discovery, immune disease model construction, and antibody drug development. By introducing different AI technical capabilities through cooperation, the drug research and development process is accelerated.

Breaking the "Double Ten Law," Ecological Synergy Boosts Industrial Development

In the field of new drug development, there is the famous "Double Ten Rule" — 10 years and an investment of 1 billion US dollars. However, Deloitte's long-term tracking of the world’s TOP20 pharmaceutical companies shows that the average cost for a single new drug from discovery to market has risen to 2.23 billion US dollars, with a research and development cycle exceeding 100 months. Meanwhile, the return on investment for global new drug development has remained at only around 5.9% in the long term.

AI is completely颠覆ing this model. With the application of AI throughout the entire drug research and development process, such as the identification of disease targets, drug discovery, preclinical and clinical research, the overall time and cost associated with drug development are being reduced.

However, AI-driven drug development still faces certain challenges. As of now, there is no drug completely designed by AI that has been approved for marketing globally, with only a few projects advancing to Phase III clinical trials.

(Image Source: Wen Wei Po)

Insilico Medicine's core pipeline ISM001-055 — the world's first AI-driven drug candidate to enter clinical trials — is scheduled to commence Phase IIb/III studies in the first half of 2026. If progress goes smoothly, it is expected to rank among the first group in the global AI pharmaceutical field to enter the pivotal clinical stage or achieve market launch.

During the critical period when AI pharmaceuticals are moving from concept to implementation, the support of the industrial ecosystem is crucial.After long-term development, Zhangjiang Pharm Valley has become an industrial highland with the most complete industry chain, the best ecosystem, the most concentrated talent pool, the most active innovation, and the most efficient R&D., and is exploring a systematic path of support.

✔ At the policy level:Pudong New Area emphasized "promoting the openness of application scenarios" in the "15th Five-Year Plan," proposing to explore public service and market-oriented application scenarios such as intelligent transportation, smart healthcare, and intelligent manufacturing. It aims to drive the implementation of strategically high-value AI scenarios through methods like "open competition for the best solutions," while creating benchmark application scenarios to promote the practical application and popularization of AI technology.

✔ At the ecological construction level, By building a full-chain collaborative ecosystem, to help all parties achieve low-cost, high-quality cooperation. For example, establishZhangjiang AI Drug Discovery Alliance`, Gather`Insilico Medicine, XtalPi, Fosun Pharma, Shanghai Institute of Materia Medica, Chinese Academy of SciencesThe 40-plus member units, includingShanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai Advanced Research Institute, Zhejiang University, Zhangjiang Group, MedChemExpress (MCE), XtalPi, Insilico Medicine, Hengrui Pharma, Hansoh Pharma, covering an ecosystem from source innovation to industrial application, further promoting technology sharing, project cooperation, and talent exchange.

Nowadays, AI-empowered drug research and development has hit the "fast-forward button." In Zhangjiang Pharm Valley, a group of cutting-edge companies are further leveraging the advantages of AI technology to accelerate the integration and development of the future health industry on the track where biomedicine intersects with artificial intelligence.

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