{"@context":"https://schema.org","@type":"NewsArticle","generatedAt":"2026-07-28T06:20:51.496Z","headline":"AI 如何缩短中国药物发现周期：Insilico Medicine 将候选药物开发时间压缩至约一年","description":"Insilico Medicine 通过将人工智能与实验室研究结合，已将部分候选药物的开发时间缩短至约一年。该公司 CEO Alex Zhavoronkov 表示，其最快项目在九个月内就完成了候选药物提名，典型周期约为 13 个月。","url":"https://www.aioga.com/news/cms33196c07iaro3f3qccae6e/","mainEntityOfPage":"https://www.aioga.com/news/cms33196c07iaro3f3qccae6e/","datePublished":"2026-07-27T10:00:00.000Z","dateModified":"2026-07-27T10:00:00.000Z","inLanguage":"zh-CN","publisher":{"@type":"NewsMediaOrganization","name":"Aioga","url":"https://www.aioga.com"},"citation":["https://www.artificialintelligence-news.com/news/ai-drug-discovery-china","https://aihot.virxact.com/items/cms33196c07iaro3f3qccae6e"],"canonicalUrl":"https://www.aioga.com/news/cms33196c07iaro3f3qccae6e/","directAnswer":{"@type":"Answer","text":"Aioga 编辑摘要：Insilico Medicine 通过将人工智能与实验室研究结合，已将部分候选药物的开发时间缩短至约一年。 Aioga 将其归入「行业动态」方向，重点关注它对真实使用和行业竞争的影响。","url":"https://www.aioga.com/news/cms33196c07iaro3f3qccae6e/","dateCreated":"2026-07-27T10:00:00.000Z","author":{"@type":"Organization","@id":"https://www.aioga.com/authors/aioga-editorial/#editorial-team","name":"Aioga Editorial Team","url":"https://www.aioga.com/authors/aioga-editorial/"}},"evidence":[{"@type":"CreativeWork","name":"artificialintelligence-news.com source article","url":"https://www.artificialintelligence-news.com/news/ai-drug-discovery-china","datePublished":"2026-07-27T10:00:00.000Z","provider":{"@type":"Organization","name":"artificialintelligence-news.com","url":"https://www.artificialintelligence-news.com/news/ai-drug-discovery-china"}},{"@type":"CreativeWork","name":"AIHot archive record","url":"https://aihot.virxact.com/items/cms33196c07iaro3f3qccae6e","datePublished":"2026-07-27T10:00:00.000Z","provider":{"@type":"Organization","name":"AIHot","url":"https://aihot.virxact.com/items/cms33196c07iaro3f3qccae6e"}}],"aggregationSource":"Artificial Intelligence News（RSS）","originalPublisher":{"name":"artificialintelligence-news.com","url":"https://www.artificialintelligence-news.com/news/ai-drug-discovery-china"},"article":{"id":"cms33196c07iaro3f3qccae6e","slug":"cms33196c07iaro3f3qccae6e","url":"https://www.aioga.com/news/cms33196c07iaro3f3qccae6e/","title":"AI 如何缩短中国药物发现周期：Insilico Medicine 将候选药物开发时间压缩至约一年","title_en":"How AI is shortening drug discovery timelines in China","summary":"Insilico Medicine 通过将人工智能与实验室研究结合，已将部分候选药物的开发时间缩短至约一年。该公司 CEO Alex Zhavoronkov 表示，其最快项目在九个月内就完成了候选药物提名，典型周期约为 13 个月。","source":"Artificial Intelligence News（RSS）","sourceUrl":"https://www.artificialintelligence-news.com/news/ai-drug-discovery-china","aiHotUrl":"https://aihot.virxact.com/items/cms33196c07iaro3f3qccae6e","publishedAt":"2026-07-27T10:00:00.000Z","category":"行业动态","score":45,"selected":false,"articleBody":["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/","Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo：https://www.ai-expo.net/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx：https://techexevent.com/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series and is co-located with other leading technology events including the Cyber Security & Cloud Expo：https://cybersecuritycloudexpo.com/?utm_source=CloudTech-News&utm_medium=Footer-banner&utm_campaign=world-series. Click here：https://techexevent.com/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series for more information.","AI News is powered by TechForge Media：https://techforge.pub/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series. Explore other upcoming enterprise technology events and webinars here：https://techforge.pub/events/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series.","Muhammad Zulhusni：https://www.artificialintelligence-news.com/news/author/muhammadzulhusni/","Physical AI：https://www.artificialintelligence-news.com/categories/ai-and-us/physical-ai/","AI Business Strategy：https://www.artificialintelligence-news.com/categories/inside-ai/ai-business-strategy/, Artificial Intelligence：https://www.artificialintelligence-news.com/categories/artificial-intelligence/, Features：https://www.artificialintelligence-news.com/categories/features/, Finance AI：https://www.artificialintelligence-news.com/categories/ai-in-action/finance-ai/, World of Work：https://www.artificialintelligence-news.com/categories/ai-and-us/world-of-work/","Sponsored Content：https://www.artificialintelligence-news.com/categories/sponsored-content/","Healthcare & Wellness AI：https://www.artificialintelligence-news.com/categories/ai-in-action/healthcare-wellness-ai/","Artificial Intelligence：https://www.artificialintelligence-news.com/categories/artificial-intelligence/","All our premium content and latest tech news delivered straight to your inbox","AI News is part of TechForge：https://techforge.pub/"],"articleImages":[{"sourceUrl":"https://www.artificialintelligence-news.com/wp-content/uploads/2026/06/image-300x37.png","alt":"Banner for AI & Big Data Expo by TechEx 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logo in the background as OpenAI is deploying a Health feature inside ChatGPT, giving users the option to connect Apple Health data and medical records to the chatbot.","afterParagraph":40,"url":"/media/articles/cms33196c07iaro3f3qccae6e/ae1ffe324bf79d4c.jpg"}],"mediaStatus":"ok","articleBodyZh":["Insilico Medicine 的首席执行官 Alex Zhavoronkov 表示，通过将人工智能与中国的实验室研究相结合，该公司已将某些药物开发候选物的生产时间缩短到大约一年。","这家在香港上市的公司最快的项目在九个月内就达到了候选物提名阶段，而其典型时间表约为 13 个月，Zhavoronkov 说。他表示，传统方法通常需要大约四年半才能达到同一阶段。","该时间表涵盖早期发现和候选物选择阶段，而不是将药物推向市场的整个过程。临床试验、生产和监管审查仍然是独立的阶段。","Insilico 使用生成式人工智能来识别生物靶点、设计潜在药物分子，并评估哪些化合物应进入实验室测试。","公司表示，其项目通常在研究人员合成和测试 60 到 200 个分子后，在 12 到 18 个月内达到临床前候选物提名阶段。其工作流程将 AI 生成的设计与研究人员的审查和实验验证相结合。","实验室实验仍然是确认模型选择的化合物的生物活性和药物特性的必要步骤。Insilico 表示，其 AI 支持的流程使团队在测试较少一组合成分子后就能达到候选物提名阶段，尽管公司未提供与未使用 AI 开发的同类项目的直接比较。","Insilico 表示，自 2021 年以来已生成 31 个临床前候选物。根据公司的管线披露，其中 13 个项目已获得临床试验新药 (IND) 批准，使其能够向人体研究推进。","公司在蒙特利尔和阿布扎比进行 AI 研究，而大部分实验验证和实验室放大工作在中国进行。其上海设施已实现部分生物取样和化合物筛选的自动化。","中国以外的团队负责开发和评估公司的 AI 模型，而上海的研究人员负责生物测试、筛选和放大。","Zhavoronkov 将部分较短的开发周期归因于中国的科研基础设施、运营成本和监管环境。他表示，在中国设有研究实验室的制药公司可以比传统候选药物开发周期提前约两年。","中国的业务已经超越了仿制药成分的生产，现在在新药开发中也扮演更重要的角色。国际制药公司也与中国的实验室、合同研究机构、临床试验中心和生物技术公司合作。","一位辉瑞高管表示，在中国进行临床开发的速度可能是欧洲同类工作的三倍，而且成本约为欧洲的一半。路透社称，药物候选产品通常需要五到七年才能进入中国市场，而在西方市场至少需要八到十年。","中国在2025年为符合条件的I类创新药临床试验申请推出了30个工作日审评通道。需要专家咨询或涉及复杂技术问题的申请可以转入60个工作日审评周期。","“我们现在在时间上与中国制药公司竞争，在创新性上与西方的传统生物技术公司竞争，”Zhavoronkov说。","Insilico 已与包括礼来和日本武田在内的制药公司签订了研发协议。","该公司还与总部位于台湾的Bora Pharmaceuticals宣布了一项拟议战略联盟，如果签署最终协议并全面实施合作，其价值可能超过25亿美元。","尽管Insilico在中国设有研究设施，Zhavoronkov 表示，其超过90%的收入来自西方制药公司。他没有披露公司在中国的收入额。","Zhavoronkov表示，西方的许可协议对Insilico更有利，因为中国的国家保险系统对高度创新药物的报销率较低。","Zhavoronkov说，由于地缘政治原因，公司也限制了在中国的大部分软件销售。公司计划在上海扩大研究业务。","Insilico于2026年7月宣布并注册了Rentosertib的III期临床试验。这种口服药物正在研究用于特发性肺纤维化，这是一种导致肺部逐渐瘢痕化的疾病。","公司使用人工智能识别了该药物的生物学靶点，并生成和优化了其分子结构。","III期研究计划在中国47个中心招募320名参与者。该研究将比较Rentosertib与安慰剂在52周内的疗效，主要终点为测量受试者用力肺活量年下降率，这是肺功能的标准衡量指标。","在ClinicalTrials.gov记录于7月7日更新时，该试验显示尚未开始招募。预计招募将于2026年8月开始，主要完成时间预计为2029年10月。","Rentosertib此前完成了较小规模的IIa期研究。III期试验将对更大患者群体进行更长期的治疗测试。","候选药物提名仍属于早期开发里程碑。药物仍需完成临床前测试、人类试验、生产验证以及监管审查，才能获准销售。","行业数据尚未确定AI设计的药物在后期试验中是否更可能成功。","2024年对AI原生生物技术管线的分析报告显示I期成功率在80%到90%之间。同一研究发现II期成功率约为40%，大致与研究人员用于行业历史比较的情况一致。","研究人员表示，II期项目数量过少，无法确定AI是否提高了后期临床成功率。该分析基于公开报告的管线，并未比较其他条件相同的AI支持药物项目与传统药物项目。","Insilico表示已产生31个临床前候选药物，并获得了13项新药临床试验申请批准。Rentosertib是其首个达到III期阶段的项目，而公司尚未有任何实验性药物获得商业批准。","人工智能和实验室机器人也在改变Insilico内部的人员配置需求。","Zhavoronkov 估计，该公司可能会自动化或替代大约 40% 的软件相关员工。他没有将这一数字描述为已宣布的裁员，也没有将其应用于整个生物技术行业。","Insilico 雇佣了大约 400 名员工。Zhavoronkov 表示，实验室科学家和软件工程师正在接受再培训，以管理 AI 评估系统、自动化设备和机器人技术。","他说，再培训的重点是 AI 基准测试和机器人系统，因为公司正在自动化更多的研究和软件功能。","（照片：Julia Koblitz：https://unsplash.com/@jkoblitz?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText）","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/","想要向行业领导者学习更多关于 AI 和大数据的知识吗？请查看 AI & 大数据博览会：https://www.ai-expo.net/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series，该博览会将在阿姆斯特丹、加利福尼亚和伦敦举办。此综合性活动是 TechEx 的一部分：https://techexevent.com/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series，并与其他领先的技术活动共同举办，包括网络安全与云博览会：https://cybersecuritycloudexpo.com/?utm_source=CloudTech-News&utm_medium=Footer-banner&utm_campaign=world-series。点击这里：https://techexevent.com/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series 了解更多信息。","AI 新闻由 TechForge Media 提供支持：https://techforge.pub/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series。在此探索其他即将举行的企业技术活动和网络研讨会：https://techforge.pub/events/?utm_source=AI-News&utm_medium=Footer-banner&utm_campaign=world-series。","Muhammad Zulhusni：https://www.artificialintelligence-news.com/news/author/muhammadzulhusni/","物理 AI：https://www.artificialintelligence-news.com/categories/ai-and-us/physical-ai/","AI商业策略：https://www.artificialintelligence-news.com/categories/inside-ai/ai-business-strategy/，人工智能：https://www.artificialintelligence-news.com/categories/artificial-intelligence/，专题报道：https://www.artificialintelligence-news.com/categories/features/，金融AI：https://www.artificialintelligence-news.com/categories/ai-in-action/finance-ai/，职场世界：https://www.artificialintelligence-news.com/categories/ai-and-us/world-of-work/","赞助内容：https://www.artificialintelligence-news.com/categories/sponsored-content/","医疗与健康AI：https://www.artificialintelligence-news.com/categories/ai-in-action/healthcare-wellness-ai/","人工智能：https://www.artificialintelligence-news.com/categories/artificial-intelligence/","我们所有的高级内容和最新科技新闻将直接发送到您的邮箱","AI新闻是TechForge的一部分：https://techforge.pub/"],"translationStatus":"translated","bodyOrigin":"source-page","editorial":{"summary":"Aioga 编辑摘要：Insilico Medicine 通过将人工智能与实验室研究结合，已将部分候选药物的开发时间缩短至约一年。 Aioga 将其归入「行业动态」方向，重点关注它对真实使用和行业竞争的影响。","background":"背景分析：公司与行业类动态需要放在竞争格局、商业化路径、资本信号和监管环境中观察，单条公告不能代表最终结果。","viewpoint":"Aioga 判断：这条动态更适合作为行业观察信号，当前信息足以建立线索，但不足以推导长期结论。","implications":"影响分析：对相关团队而言，短期应先核对来源、可用范围和实际成本，再判断是否值得接入或跟进。","nextStep":"后续观察：继续观察官方文件、合作落地、收入或用户信号、竞品动作和监管后续。","evidenceRefs":["title","summary","articleBody"],"confidence":"medium","status":"published","aiGenerated":false,"autoApproved":true,"generatedBy":"rule-safe-fallback","generatedAt":"2026-07-28T06:29:10.471Z","sourceHash":"23d0a78f85a45004","validation":{"passed":true,"mode":"rule-safe-fallback","checks":["schema","length","source-attribution","no-html"]}},"tags":["行业动态","Artificial Intelligence News（RSS）"],"translations":{"zh-CN":{"title":"AI 如何缩短中国药物发现周期：Insilico Medicine 将候选药物开发时间压缩至约一年","summary":"Insilico Medicine 通过将人工智能与实验室研究结合，已将部分候选药物的开发时间缩短至约一年。该公司 CEO Alex Zhavoronkov 表示，其最快项目在九个月内就完成了候选药物提名，典型周期约为 13 个月。","category":"行业动态","source":"artificialintelligence-news.com","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"AI 如何缩短中国药物发现周期：Insilico Medicine 将候选药物开发时间压缩至约一年 - Aioga AI资讯","description":"Insilico Medicine 通过将人工智能与实验室研究结合，已将部分候选药物的开发时间缩短至约一年。该公司 CEO Alex Zhavoronkov 表示，其最快项目在九个月内就完成了候选药物提名，典型周期约为 13 个月。","url":"https://www.aioga.com/news/cms33196c07iaro3f3qccae6e/"},"en":{"title":"How AI Shortens the Drug Discovery Cycle in China: Insilico Medicine Reduces Candidate Drug Development Time to About One Year","summary":"Insilico Medicine, by combining artificial intelligence with laboratory research, has shortened the development time of some drug candidates to about one year. The company's CEO, Alex Zhavoronkov, stated that its fastest project completed the drug candidate nomination in nine months, with a typical cycle of about 13 months.","category":"Industry","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"How AI Shortens the Drug Discovery Cycle in China: Insilico Medicine Reduces Candidate Drug Development Time to About One Year - Aioga AI News","description":"Insilico Medicine, by combining artificial intelligence with laboratory research, has shortened the development time of some drug candidates to about one year. The company's CEO, A...","url":"https://www.aioga.com/en/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:43:11.821Z"},"ja":{"title":"AIは中国の薬物探索周期をどのように短縮するか：Insilico Medicineは候補薬の開発時間を約1年に圧縮","summary":"Insilico Medicineは、人工知能と実験室研究を組み合わせることで、一部の候補薬の開発時間を約1年に短縮しました。同社のCEOアレックス・ジャボロンコフ氏によれば、最も早いプロジェクトでは9か月で候補薬の指名を完了し、典型的なサイクルは約13か月です。","category":"業界動向","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"AIは中国の薬物探索周期をどのように短縮するか：Insilico Medicineは候補薬の開発時間を約1年に圧縮 - Aioga AIニュース","description":"Insilico Medicineは、人工知能と実験室研究を組み合わせることで、一部の候補薬の開発時間を約1年に短縮しました。同社のCEOアレックス・ジャボロンコフ氏によれば、最も早いプロジェクトでは9か月で候補薬の指名を完了し、典型的なサイクルは約13か月です。","url":"https://www.aioga.com/ja/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:43:17.146Z"},"ko":{"title":"AI가 중국 약물 발견 주기를 단축하는 방법: Insilico Medicine이 후보 약물 개발 시간을 약 1년으로 단축","summary":"Insilico Medicine는 인공지능과 실험실 연구를 결합하여 일부 후보 약물의 개발 시간을 약 1년으로 단축했습니다. 이 회사의 CEO Alex Zhavoronkov은 가장 빠른 프로젝트가 9개월 만에 후보 약물 지명을 완료했으며, 일반적인 주기는 약 13개월이라고 밝혔습니다.","category":"업계 동향","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"AI가 중국 약물 발견 주기를 단축하는 방법: Insilico Medicine이 후보 약물 개발 시간을 약 1년으로 단축 - Aioga AI 뉴스","description":"Insilico Medicine는 인공지능과 실험실 연구를 결합하여 일부 후보 약물의 개발 시간을 약 1년으로 단축했습니다. 이 회사의 CEO Alex Zhavoronkov은 가장 빠른 프로젝트가 9개월 만에 후보 약물 지명을 완료했으며, 일반적인 주기는 약 13개월이라고 밝혔습니다.","url":"https://www.aioga.com/ko/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:44:08.147Z"},"es":{"title":"Cómo la IA acorta el ciclo de descubrimiento de medicamentos en China: Insilico Medicine reduce el tiempo de desarrollo de medicamentos candidatos a aproximadamente un año","summary":"Insilico Medicine, al combinar la inteligencia artificial con la investigación de laboratorio, ha reducido el tiempo de desarrollo de algunos medicamentos candidatos a aproximadamente un año. El CEO de la compañía, Alex Zhavoronkov, señaló que su proyecto más rápido completó la nominación de medicamento candidato en nueve meses, mientras que el ciclo típico es de aproximadamente 13 meses.","category":"Industria","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Cómo la IA acorta el ciclo de descubrimiento de medicamentos en China: Insilico Medicine reduce el tiempo de desarrollo de medicamentos candidatos a aproximadamente un año - Aioga Noticias de IA","description":"Insilico Medicine, al combinar la inteligencia artificial con la investigación de laboratorio, ha reducido el tiempo de desarrollo de algunos medicamentos candidatos a aproximadame...","url":"https://www.aioga.com/es/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:43:56.631Z"},"fr":{"title":"Comment l'IA raccourcit le cycle de découverte des médicaments en Chine : Insilico Medicine réduit le temps de développement des candidats médicaments à environ un an","summary":"Insilico Medicine, en combinant intelligence artificielle et recherche en laboratoire, a réduit le temps de développement de certains médicaments candidats à environ un an. Le PDG de l'entreprise, Alex Zhavoronkov, a déclaré que son projet le plus rapide avait abouti à la nomination d'un médicament candidat en neuf mois, le cycle typique étant d'environ 13 mois.","category":"Industrie","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Comment l'IA raccourcit le cycle de découverte des médicaments en Chine : Insilico Medicine réduit le temps de développement des candidats médicaments à environ un an - Aioga Actualités IA","description":"Insilico Medicine, en combinant intelligence artificielle et recherche en laboratoire, a réduit le temps de développement de certains médicaments candidats à environ un an. Le PDG...","url":"https://www.aioga.com/fr/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:44:50.894Z"},"de":{"title":"Wie KI den Arzneimittelentdeckungszyklus in China verkürzt: Insilico Medicine reduziert die Entwicklungszeit für Kandidatenmedikamente auf etwa ein Jahr","summary":"Insilico Medicine hat durch die Kombination von künstlicher Intelligenz mit Laborforschung die Entwicklungszeit einiger präklinischer Medikamentenkandidaten auf etwa ein Jahr verkürzt. Der CEO des Unternehmens, Alex Zhavoronkov, gab an, dass sein schnellstes Projekt die Nominierung eines Medikamentenkandidaten innerhalb von neun Monaten abgeschlossen hat, während der typische Zyklus etwa 13 Monate beträgt.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Wie KI den Arzneimittelentdeckungszyklus in China verkürzt: Insilico Medicine reduziert die Entwicklungszeit für Kandidatenmedikamente auf etwa ein Jahr - Aioga KI-News","description":"Insilico Medicine hat durch die Kombination von künstlicher Intelligenz mit Laborforschung die Entwicklungszeit einiger präklinischer Medikamentenkandidaten auf etwa ein Jahr verkü...","url":"https://www.aioga.com/de/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:44:45.183Z"},"pt-BR":{"title":"Como a IA está encurtando o ciclo de descoberta de medicamentos na China: a Insilico Medicine reduz o tempo de desenvolvimento de candidatos a medicamentos para cerca de um ano","summary":"A Insilico Medicine, ao combinar inteligência artificial com pesquisa laboratorial, conseguiu reduzir o tempo de desenvolvimento de alguns candidatos a medicamentos para cerca de um ano. O CEO da empresa, Alex Zhavoronkov, afirmou que seu projeto mais rápido concluiu a nomeação de candidatos a medicamentos em nove meses, sendo o ciclo típico de cerca de 13 meses.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Como a IA está encurtando o ciclo de descoberta de medicamentos na China: a Insilico Medicine reduz o tempo de desenvolvimento de candidatos a medicamentos para cerca de um ano - Aioga Notícias de IA","description":"A Insilico Medicine, ao combinar inteligência artificial com pesquisa laboratorial, conseguiu reduzir o tempo de desenvolvimento de alguns candidatos a medicamentos para cerca de u...","url":"https://www.aioga.com/pt-BR/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:45:31.366Z"},"ru":{"title":"Как ИИ сокращает цикл открытия лекарств в Китае: Insilico Medicine сокращает время разработки кандидатов в лекарства примерно до одного года","summary":"Компания Insilico Medicine, сочетая искусственный интеллект с лабораторными исследованиями, сократила время разработки некоторых кандидатов на лекарства примерно до одного года. Генеральный директор компании Алекс Жаворонков заявил, что самый быстрый проект завершил выдвижение кандидата на лекарство за девять месяцев, а типичный цикл занимает около 13 месяцев.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Как ИИ сокращает цикл открытия лекарств в Китае: Insilico Medicine сокращает время разработки кандидатов в лекарства примерно до одного года - Aioga Новости ИИ","description":"Компания Insilico Medicine, сочетая искусственный интеллект с лабораторными исследованиями, сократила время разработки некоторых кандидатов на лекарства примерно до одного года. Ге...","url":"https://www.aioga.com/ru/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:45:34.297Z"},"ar":{"title":"كيف تُقصِّر الذكاء الاصطناعي دورة اكتشاف الأدوية في الصين: شركة Insilico Medicine تقلص فترة تطوير الأدوية المرشحة إلى حوالي سنة واحدة","summary":"شركة Insilico Medicine من خلال دمج الذكاء الاصطناعي مع البحث المخبري، قامت بتقليص وقت تطوير بعض الأدوية المرشحة إلى حوالي عام واحد. وصرح الرئيس التنفيذي للشركة أليكس زهافورونكوف أن أسرع مشاريعها أكملت ترشيح الأدوية المرشحة خلال تسعة أشهر، بينما تستغرق الدورة النموذجية حوالي 13 شهراً.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"كيف تُقصِّر الذكاء الاصطناعي دورة اكتشاف الأدوية في الصين: شركة Insilico Medicine تقلص فترة تطوير الأدوية المرشحة إلى حوالي سنة واحدة - Aioga أخبار الذكاء الاصطناعي","description":"شركة Insilico Medicine من خلال دمج الذكاء الاصطناعي مع البحث المخبري، قامت بتقليص وقت تطوير بعض الأدوية المرشحة إلى حوالي عام واحد. وصرح الرئيس التنفيذي للشركة أليكس زهافورونكوف أن...","url":"https://www.aioga.com/ar/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:46:24.694Z"},"hi":{"title":"एआई चीन की दवा खोज चक्र को कैसे छोटा कर सकता है: Insilico Medicine ने उम्मीदवार दवा विकास समय को लगभग एक साल तक कम किया","summary":"इंसिलिको मेडिसिन ने कृत्रिम बुद्धिमत्ता और प्रयोगशाला अनुसंधान को मिलाकर कुछ उम्मीदवार दवाओं के विकास समय को लगभग एक वर्ष तक कम कर दिया है। कंपनी के सीईओ एलेक्स ज़ेवॉरोनकोव ने कहा कि उनकी सबसे तेज परियोजना ने नौ महीनों के भीतर उम्मीदवार दवा नामांकन पूरा कर लिया, जबकि सामान्य समय लगभग 13 महीने का है।","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"एआई चीन की दवा खोज चक्र को कैसे छोटा कर सकता है: Insilico Medicine ने उम्मीदवार दवा विकास समय को लगभग एक साल तक कम किया - Aioga AI समाचार","description":"इंसिलिको मेडिसिन ने कृत्रिम बुद्धिमत्ता और प्रयोगशाला अनुसंधान को मिलाकर कुछ उम्मीदवार दवाओं के विकास समय को लगभग एक वर्ष तक कम कर दिया है। कंपनी के सीईओ एलेक्स ज़ेवॉरोनकोव ने कहा...","url":"https://www.aioga.com/hi/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:46:23.625Z"},"it":{"title":"Come l'IA può abbreviare il ciclo di scoperta dei farmaci in Cina: Insilico Medicine riduce il tempo di sviluppo dei farmaci candidati a circa un anno","summary":"Insilico Medicine, combinando l'intelligenza artificiale con la ricerca di laboratorio, ha ridotto il tempo di sviluppo di alcuni farmaci candidati a circa un anno. Il CEO dell'azienda, Alex Zhavoronkov, ha dichiarato che il loro progetto più rapido ha completato la nomina del farmaco candidato in nove mesi, con un ciclo tipico di circa 13 mesi.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Come l'IA può abbreviare il ciclo di scoperta dei farmaci in Cina: Insilico Medicine riduce il tempo di sviluppo dei farmaci candidati a circa un anno - Aioga Notizie IA","description":"Insilico Medicine, combinando l'intelligenza artificiale con la ricerca di laboratorio, ha ridotto il tempo di sviluppo di alcuni farmaci candidati a circa un anno. Il CEO dell'azi...","url":"https://www.aioga.com/it/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:47:14.292Z"},"nl":{"title":"Hoe AI de cyclus van geneesmiddelontdekking in China verkort: Insilico Medicine verkort de ontwikkelingsduur van kandidaat-geneesmiddelen tot ongeveer één jaar","summary":"Insilico Medicine heeft door kunstmatige intelligentie te combineren met laboratoriumonderzoek de ontwikkelingstijd van sommige kandidaat-geneesmiddelen verkort tot ongeveer een jaar. De CEO van het bedrijf, Alex Zhavoronkov, verklaarde dat hun snelste project de kandidaat-geneesmiddelindicatie binnen negen maanden had voltooid, terwijl de typische cyclus ongeveer 13 maanden bedraagt.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Hoe AI de cyclus van geneesmiddelontdekking in China verkort: Insilico Medicine verkort de ontwikkelingsduur van kandidaat-geneesmiddelen tot ongeveer één jaar - Aioga AI-nieuws","description":"Insilico Medicine heeft door kunstmatige intelligentie te combineren met laboratoriumonderzoek de ontwikkelingstijd van sommige kandidaat-geneesmiddelen verkort tot ongeveer een ja...","url":"https://www.aioga.com/nl/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:47:18.993Z"},"tr":{"title":"Yapay Zeka Çin'de İlaç Keşif Döngüsünü Nasıl Kısaltıyor: Insilico Medicine Aday İlaç Geliştirme Süresini Yaklaşık Bir Yıla Sıkıştırıyor","summary":"Insilico Medicine, yapay zekayı laboratuvar araştırmalarıyla birleştirerek bazı aday ilaçların geliştirme süresini yaklaşık bir yıla kadar kısalttı. Şirketin CEO'su Alex Zhavoronkov, en hızlı projelerinin dokuz ay içinde aday ilaç adaylığını tamamladığını ve tipik sürenin yaklaşık 13 ay olduğunu belirtti.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Yapay Zeka Çin'de İlaç Keşif Döngüsünü Nasıl Kısaltıyor: Insilico Medicine Aday İlaç Geliştirme Süresini Yaklaşık Bir Yıla Sıkıştırıyor - Aioga AI Haberleri","description":"Insilico Medicine, yapay zekayı laboratuvar araştırmalarıyla birleştirerek bazı aday ilaçların geliştirme süresini yaklaşık bir yıla kadar kısalttı. Şirketin CEO'su Alex Zhavoronko...","url":"https://www.aioga.com/tr/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:48:07.819Z"},"vi":{"title":"AI làm thế nào để rút ngắn chu kỳ phát hiện thuốc ở Trung Quốc: Insilico Medicine rút ngắn thời gian phát triển thuốc ứng viên xuống khoảng một năm","summary":"Insilico Medicine thông qua việc kết hợp trí tuệ nhân tạo với nghiên cứu trong phòng thí nghiệm, đã rút ngắn thời gian phát triển một số ứng cử viên thuốc xuống còn khoảng một năm. Giám đốc điều hành công ty Alex Zhavoronkov cho biết, dự án nhanh nhất của họ đã hoàn thành việc đề cử ứng cử viên thuốc trong vòng chín tháng, chu kỳ điển hình khoảng 13 tháng.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"AI làm thế nào để rút ngắn chu kỳ phát hiện thuốc ở Trung Quốc: Insilico Medicine rút ngắn thời gian phát triển thuốc ứng viên xuống khoảng một năm - Tin tức AI Aioga","description":"Insilico Medicine thông qua việc kết hợp trí tuệ nhân tạo với nghiên cứu trong phòng thí nghiệm, đã rút ngắn thời gian phát triển một số ứng cử viên thuốc xuống còn khoảng một năm....","url":"https://www.aioga.com/vi/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:47:57.743Z"},"id":{"title":"Bagaimana AI Memperpendek Siklus Penemuan Obat di China: Insilico Medicine Mempercepat Waktu Pengembangan Obat Kandidat Hingga Sekitar Satu Tahun","summary":"Insilico Medicine telah mempersingkat waktu pengembangan beberapa kandidat obat menjadi sekitar satu tahun dengan menggabungkan kecerdasan buatan dan penelitian laboratorium. CEO perusahaan, Alex Zhavoronkov, menyatakan bahwa proyek tercepat mereka menyelesaikan penunjukan kandidat obat dalam sembilan bulan, dengan siklus khas sekitar 13 bulan.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Bagaimana AI Memperpendek Siklus Penemuan Obat di China: Insilico Medicine Mempercepat Waktu Pengembangan Obat Kandidat Hingga Sekitar Satu Tahun - Berita AI Aioga","description":"Insilico Medicine telah mempersingkat waktu pengembangan beberapa kandidat obat menjadi sekitar satu tahun dengan menggabungkan kecerdasan buatan dan penelitian laboratorium. CEO p...","url":"https://www.aioga.com/id/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:48:49.865Z"},"th":{"title":"AI ช่วยลดระยะเวลาการค้นพบยาในจีนอย่างไร: Insilico Medicine ลดเวลาการพัฒนายาตัวเลือกเหลือประมาณหนึ่งปี","summary":"Insilico Medicine โดยการรวมปัญญาประดิษฐ์กับการวิจัยในห้องปฏิบัติการ ได้ลดระยะเวลาในการพัฒนายาบางตัวลงเหลือประมาณหนึ่งปี CEO ของบริษัท Alex Zhavoronkov กล่าวว่ามีโครงการที่เร็วที่สุดสามารถทำการเสนอชื่อยาตัวอย่างภายในเก้าเดือน โดยรอบเวลาปกติประมาณ 13 เดือน","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"AI ช่วยลดระยะเวลาการค้นพบยาในจีนอย่างไร: Insilico Medicine ลดเวลาการพัฒนายาตัวเลือกเหลือประมาณหนึ่งปี - ข่าว AI Aioga","description":"Insilico Medicine โดยการรวมปัญญาประดิษฐ์กับการวิจัยในห้องปฏิบัติการ ได้ลดระยะเวลาในการพัฒนายาบางตัวลงเหลือประมาณหนึ่งปี CEO ของบริษัท Alex Zhavoronkov กล่าวว่ามีโครงการที่เร็วที่สุ...","url":"https://www.aioga.com/th/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:48:53.864Z"},"pl":{"title":"Jak AI skraca cykl odkrywania leków w Chinach: Insilico Medicine skraca czas opracowywania kandydujących leków do około roku","summary":"Insilico Medicine, poprzez połączenie sztucznej inteligencji z badaniami laboratoryjnymi, skróciło czas opracowywania niektórych leków-kandydatów do około roku. Dyrektor generalny firmy, Alex Zhavoronkov, stwierdził, że ich najszybszy projekt zakończył nominację leku-kandydata w dziewięć miesięcy, a typowy cykl wynosi około 13 miesięcy.","category":"行业动态","source":"Artificial Intelligence News（RSS）","aggregationSource":"Artificial Intelligence News（RSS）","pageTitle":"Jak AI skraca cykl odkrywania leków w Chinach: Insilico Medicine skraca czas opracowywania kandydujących leków do około roku - Aioga Wiadomości AI","description":"Insilico Medicine, poprzez połączenie sztucznej inteligencji z badaniami laboratoryjnymi, skróciło czas opracowywania niektórych leków-kandydatów do około roku. Dyrektor generalny...","url":"https://www.aioga.com/pl/news/cms33196c07iaro3f3qccae6e/","contentTranslated":true,"sourceHash":"32c7730d42a84d91","translatedAt":"2026-07-27T10:49:40.456Z"}}}}