Revenue surged 272%, the "AI pharmaceutical first stock" on the Hong Kong stock market successfully turned losses into profits

The BD boom in the innovative drug industry has reached a phased end.

Driven by the continuous capital siphon effect of the AI sector, the entire innovative drug sector is under pressure, with leading listed enterprises experiencing varying degrees of pullback. Even the "AI-powered pharmaceutical" track, which previously had the highest correlation with AI, failed to deliver an independent market performance.

On July 9, the Hong Kong-listed "first AI pharmaceutical stock" Insilico Medicine released its 2026 semi-annual performance forecast. The announcement shows that the company expects to record revenue of approximately $102.5 million to $106.5 million in the first half of the year, representing a substantial year-on-year increase of 272.7% to 287.3%; net profit is projected to range from $33.5 million to $39.5 million, successfully turning profitable year-on-year; adjusted net profit is expected to stand between $45.5 million and $51.5 million.

Regarding this profitable performance, Insilico Medicine stated that it mainly benefits from the company's continuous efforts to drive revenue growth while achieving systematic optimization of overall operational efficiency, with revenues from out-licensing, co-development, and research collaboration agreements all seeing steady growth.

Public information shows that in the first half of 2026, Insilico Medicine secured four large-scale BD collaborations, with a total contracted value approaching $7 billion. These include an $888 million collaboration with Servier in January, a $2.75 billion global R&D collaboration agreement with Eli Lilly in March, a $2.5 billion partnership with SK Biopharmaceuticals in June, and a $600 million global strategic collaboration agreement with Takeda Pharmaceutical on July 2.

This AI pharmaceutical enterprise, which listed on the Hong Kong Stock Exchange at the end of last year, took only half a year to secure heavyweight collaboration orders from four top global pharmaceutical companies. Its core competitiveness does not lie in mere hype over the AI pharmaceutical concept, but in a complete, implementable, and verifiable R&D system.

On July 8, Insilico Medicine officially announced that Rentosertib, the world's first AI-originated drug, has formally entered Phase III clinical trials. The relevant information has been published on the platform of the Center for Drug Evaluation (CDE) of the National Medical Products Administration of China, and registration has been completed on the ClinicalTrials.gov website.

It is understood that this drug is a core candidate drug whose entire R&D process was empowered by Insilico Medicine's self-developed generative AI platform Pharma.AI. Its innovative target and brand-new drug structure were both discovered with AI assistance, making it the world's first AI-developed drug with first-in-class potential for treating idiopathic pulmonary fibrosis (IPF).

Judging from the secondary market performance, even with large BD orders and significant clinical progress in hand, Insilico Medicine still failed to resist the downward trend against the market. Statistics show that since late February, the maximum decline in Insilico Medicine's share price has exceeded 50%, with the latest closing market capitalization at HK$24.7 billion.

From "Concept" to "Implementation"

Data from Deloitte shows that for an innovative drug, from target discovery to final approval for marketing, the average R&D cost has exceeded $2 billion, the overall R&D cycle generally exceeds 10 years, and the clinical success rate has always remained below 10%. Against this industry backdrop, leveraging AI technology to enhance new drug R&D efficiency and improve clinical success rates has become the core logic behind the emergence of the AI pharmaceutical track.

In 2014, Alex Zhavoronkov founded Insilico Medicine in the United States.

In the early days of entrepreneurship, Alex was very optimistic about the development potential of AI pharmaceuticals. However, constrained by the immature development of the industry and the overly forward-looking concept of AI pharmaceuticals, its business model did not gain recognition from the capital market. When the company fell into operational difficulties, Alex even had to sell his personal property to maintain the basic operations of the enterprise.

In 2018, Insilico Medicine reached a turning point in its development, when Alex got acquainted with Li Ge, the founder of WuXi AppTec, a leading enterprise in the CXO industry. Initially, Li Ge did not fully endorse the AI pharmaceutical model, but was willing to give the company a chance to try. Eventually, Insilico Medicine successfully passed the verification of its technology and model, and obtained investment from WuXi AppTec.

In 2019, Alex moved the company's headquarters to Hong Kong, China, and set up an R&D center in Shanghai, while welcoming core partner Feng Ren. Under Feng Ren's leadership and promotion, in just over two years, Insilico Medicine's Shanghai R&D center built a professional R&D team of nearly 150 people. The company established a clear division of labor: Alex is responsible for the iterative upgrading and technical optimization of the AI platform, while Feng Ren takes full charge of the overall drug R&D business.

The joint efforts of the two core founders put Insilico Medicine on a fast track of development. According to public media reports, Insilico Medicine ranks among the top in the world in terms of efficiency in the fields of novel drug target discovery and innovative drug R&D, capable of completing the screening and identification of a candidate drug within 9 to 18 months. In contrast, the pre-discovery cycle of traditional drug R&D averages as long as 4.5 years. By comparison, AI technology can increase the pre-R&D efficiency of new drugs by 3 to 6 times.

In 2021, with the release of the AlphaFold2 technology and the world's first AI-designed drug entering the clinical stage, AI pharmaceuticals were regarded by the industry as the optimal solution for new drug R&D, and a large number of pharmaceutical companies and capital flocked into the track.

However, with the rapid influx of capital and the swift rise in industry popularity, hidden problems in the track have continued to emerge. As various R&D failure cases surfaced one after another, the core logic of AI pharmaceuticals in reducing costs and increasing efficiency began to be questioned by the market. The ability to establish a sustainable business model has become the key to the survival and development of enterprises in the industry.

In response to the industry chaos, Alex, founder of Insilico Medicine, said: "AI technology completes an iteration every six months or even less. Currently, many enterprises blindly invest in developing basic large models, but such models are updated and iterated extremely quickly, making them easy to be phased out rapidly. This leads to the need for enterprises to continuously raise funds to sustain operations; once the cash flow breaks, the business model cannot be maintained. We have always adhered to a sustainable development path and refused to expand blindly following trends."

Based on considerations of steady development, Insilico Medicine listed on the Hong Kong Stock Exchange at the end of 2025, raising a total of HK$2.277 billion, making it the biotech IPO project with the largest fundraising scale on the Hong Kong stock market in 2025.

Feng Ren, Co-CEO of Insilico Medicine, said: "Pure AI pharmaceutical targets listed on the Hong Kong Stock Exchange are relatively scarce and highly representative of the industry. The company's successful listing means that the capital market has formally accepted the brand-new R&D model of AI-empowered innovative drugs. We also hope that our own development practice can provide a referable and replicable development sample for enterprises in the track."

The Test Continues

For the AI pharmaceutical track, even though it is in line with long-term industrial trends and easy to obtain high valuation premiums, the ultimate criterion for testing an enterprise's value is whether the drug can be successfully developed and commercialized for marketing.

Up to now, there has not been a single drug fully designed and developed under AI leadership approved for marketing in the world, and only a few projects have smoothly advanced to the Phase III clinical stage.

Senior industry insiders stated bluntly that the capital market has long stopped continuously supporting biopharmaceutical enterprises that cannot generate operating cash flow for a long time.

The insider further explained that the core bottom line for institutional investment is very clear at present: if an AI pharmaceutical enterprise cannot achieve cash flow realization within two or three years, it will basically be eliminated by capital. Essentially, AI pharmaceuticals have not broken away from the industry attribute of innovative drugs that requires long-term continuous investment and constant capital injection. The so-called advantage of shortening the R&D cycle still lacks verification from large-scale implementation cases.

On July 8, Rentosertib, the core pipeline drug of Insilico Medicine, formally entered Phase III clinical trials. Calculated based on a 52-week administration cycle, the administration trial is expected to end at the end of June 2027. Coupled with the subsequent data sorting and statistical analysis processes, the key clinical results will be announced as early as the end of 2027.

This also means that the next year and a half will still be a critical window period for testing the business model and technical value of AI pharmaceuticals. At the same time, Insilico Medicine's high valuation is highly dependent on the current high prosperity of the AI industry. Once the AI sector undergoes a deep correction, the company's valuation and share price will most likely come under pressure simultaneously.

Judging from past performance, from 2024 to 2025, Insilico Medicine's revenue declined from $85.834 million to $56.239 million, while its net loss expanded sharply from $17.096 million to $352 million. The continuous pressure on performance is directly reflected in the share price trend, with the company's share price falling by more than 50% at its maximum since the end of February.

In the first half of 2026, the company's revenue skyrocketed by 272.7% year-on-year, with maximum revenue reaching $106.5 million and maximum net profit hitting $39.5 million, officially announcing that the company's operations have entered a new stage of development.

Currently, there are three mainstream business models in the AI pharmaceutical industry: the SaaS model of selling software platforms to pharmaceutical companies, the AI+CRO model of providing R&D services, and the AI+Biotech model of self-developing drug pipelines and realizing value through licensing collaborations, which is the optimal choice. The first two models are only suitable for the phased survival transition of enterprises. If an enterprise wants to achieve long-term and steady development, realizing value monetization through self-developed pipelines is an inevitable path, which can refer to the development path of BeiGene.

Feng Ren also publicly stated that the company will long adhere to the core positioning of AI+Biotech, and BD collaboration revenue will remain the company's core source of revenue in the next three to five years. At the same time, he emphasized: "We do not want to be a service provider that only sells water and shovels during the gold rush. Our ultimate goal is to dig for gold ourselves and achieve the independent commercialization of our self-developed drugs."

As of June 30, 2026, Insilico Medicine has screened and identified 31 preclinical candidate compounds, covering multiple core disease areas such as oncology, immunology, metabolism, and the central nervous system, of which 13 have obtained IND clinical approvals. Currently, the company has a total of 10 projects in the clinical trial stage, 4 of which are independently advanced in clinical development by the company, and 6 are carried out with the support of partner pharmaceutical companies.

Within 2026 alone, the total value of BD collaboration transactions secured by Insilico Medicine has approached $7 billion. This means that the company has successfully crossed the "valley of death" of concept verification for AI pharmaceutical enterprises and officially entered a new cycle of commercial realization.

Kankan Finance believes that Insilico Medicine's successful turnaround to profitability in its semi-annual report is a clear signal of a fundamental reversal in the company's operations. If the core drug Rentosertib delivers high-quality Phase III clinical data smoothly next year, the company's development will achieve leapfrog upgrading, and its commercialization process will continue to accelerate.