另见：Bristol Myers Squibb 收购 Nvidia AI 系统用于药物发现：https://www.artificialintelligence-news.com/news/bristol-myers-squibb-nvidia-ai-system-drug-discovery/
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Muhammad Zulhusni：https://www.artificialintelligence-news.com/news/author/muhammadzulhusni/
Insilico Medicine has reduced the time needed to produce some drug development candidates to about one year by combining artificial intelligence with laboratory research in China, according to CEO Alex Zhavoronkov.
The Hong Kong-listed company’s fastest programme reached candidate nomination in nine months, while its typical timeline is about 13 months, Zhavoronkov said. He said conventional approaches usually take about four-and-a-half years to reach the same stage.
The timeline covers early discovery and candidate selection, rather than the full process of bringing a drug to market. Clinical trials, manufacturing, and regulatory review remain separate stages.
Insilico uses generative AI to identify biological targets, design potential drug molecules, and assess which compounds should advance to laboratory testing.
The company said its programmes typically reach preclinical-candidate nomination within 12 to 18 months after researchers synthesise and test between 60 and 200 molecules. Its workflow combines AI-generated designs with researcher review and experimental validation.
Laboratory experiments remain necessary to confirm the biological activity and drug properties of compounds selected by the models. Insilico said its AI-supported process allows teams to reach candidate nomination after testing a smaller set of synthesised molecules, although it has not provided a direct comparison with equivalent programmes developed without AI.
Insilico said it has generated 31 preclinical candidates since 2021. Thirteen programmes have received investigational new drug clearances, allowing them to advance towards human studies, according to the company’s pipeline disclosures.
The company conducts AI research in Montreal and Abu Dhabi, while much of its experimental validation and laboratory scale-up work takes place in China. Its Shanghai facility has automated parts of biological sampling and compound screening.
Teams outside China develop and evaluate the company’s AI models, while researchers in Shanghai handle biological testing, screening, and scale-up.
Zhavoronkov attributed part of the shorter development cycle to China’s research infrastructure, operating costs, and regulatory environment. He said pharmaceutical companies with research laboratories in China can remove about two years from traditional candidate-development timelines.
China has expanded beyond manufacturing generic drug ingredients and now plays a larger role in developing new medicines. International drugmakers also work with Chinese laboratories, contract research organisations, clinical-trial centres, and biotechnology companies.
A Pfizer executive said clinical development in China could be conducted three times faster and at about half the cost of equivalent work in Europe. Drug candidates typically take five to seven years to reach the Chinese market, compared with at least eight to 10 years in Western markets, according to Reuters .
China introduced a 30-working-day review pathway in 2025 for eligible Class I innovative-drug clinical-trial applications. Applications requiring expert consultation or involving complex technical issues can be moved to a 60-working-day review period.
“We now compete with Chinese pharmaceutical companies on timelines, and with traditional biotechnology companies in the West on novelty,” Zhavoronkov said.
Insilico has entered research and development agreements with pharmaceutical companies including Eli Lilly and Japan’s Takeda.
The company and Taiwan-based Bora Pharmaceuticals also announced a proposed strategic alliance that could exceed $2.5 billion if definitive agreements are signed and the collaboration is fully implemented.
Although Insilico operates research facilities in China, Zhavoronkov said more than 90% of its revenue comes from Western pharmaceutical companies. He did not disclose how much revenue the company generates in China.
Western licensing agreements are more lucrative for Insilico because China’s national insurance system offers lower reimbursement rates for highly novel drugs, Zhavoronkov said.
The company also limits sales of most of its software within China because of geopolitical concerns, Zhavoronkov said. It plans to expand its research operations in Shanghai.
Insilico announced and registered a Phase III trial of Rentosertib in July 2026. The oral drug is being studied for idiopathic pulmonary fibrosis, a disease that causes progressive scarring of the lungs.
The company used AI to identify the drug’s biological target and generate and optimise its molecular structure.
The Phase III study is designed to enrol 320 participants across 47 centres in China. It will compare Rentosertib with a placebo over 52 weeks, with the primary endpoint measuring the annual rate of decline in forced vital capacity, a standard measure of lung function.
The trial was listed as not yet recruiting when its ClinicalTrials.gov record was updated on July 7. Enrolment was expected to begin in August 2026, with primary completion estimated for October 2029.
Rentosertib previously completed a smaller Phase IIa study. The Phase III trial will test the treatment in a larger patient group over a longer period.
Candidate nomination remains an early development milestone. Drugs must still complete preclinical testing, human trials, manufacturing validation, and regulatory review before they can be approved for sale.
Industry data have not established whether AI-designed drugs are more likely to succeed in later-stage trials.
A 2024 analysis of AI-native biotechnology pipelines reported Phase I success rates of between 80% and 90%. The same study found a Phase II success rate of about 40%, broadly in line with the historical industry comparison used by the researchers.
The researchers said the number of Phase II programmes was too small to determine whether AI improves later-stage clinical success. The analysis was based on publicly reported pipelines and did not compare otherwise identical AI-supported and conventional drug programmes.
Insilico said it has produced 31 preclinical candidates and secured 13 investigational new drug clearances. Rentosertib is its first programme to reach the Phase III stage, while none of the company’s experimental medicines has received commercial approval.
AI and laboratory robotics are also changing staffing requirements within Insilico.
Zhavoronkov estimated that the company could automate or displace about 40% of its software-side workforce. He did not describe the figure as an announced staff reduction or apply it to the biotechnology industry as a whole.
Insilico employs about 400 people. Laboratory scientists and software engineers are being retrained to manage AI evaluation systems, automated equipment, and robotics, Zhavoronkov said.
The retraining is focused on AI benchmarks and robotic systems as the company automates more research and software functions, he said.
(Photo by Julia Koblitz：https://unsplash.com/@jkoblitz?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText)
See also: Bristol Myers Squibb buys Nvidia AI system for drug discovery：https://www.artificialintelligence-news.com/news/bristol-myers-squibb-nvidia-ai-system-drug-discovery/
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Muhammad Zulhusni：https://www.artificialintelligence-news.com/news/author/muhammadzulhusni/
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