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市场调查报告书
商品编码
1802968
2032 年人工智慧老年保护剂市场预测:按治疗领域、技术、应用、最终用户和地区分類的全球分析AI Geroprotector Discovery Market Forecasts to 2032 - Global Analysis By Therapeutic Area, Technology, Application, End User and By Geography |
根据 Stratistics MRC 的数据,全球人工智慧老年保护器市场规模预计在 2025 年将达到 3.16 亿美元,到 2032 年将达到 16.28 亿美元,预测期内的复合年增长率为 26.4%。
AI 抗衰老药物研发是指应用人工智慧和机器学习来识别、筛检和优化能够减缓、预防或逆转老化相关过程的化合物和干预措施。透过分析海量生物资料集,AI 可以快速预测潜在的抗衰老化合物,减少药物开发中的试验,并加速老化机制的精准标靶化。
全球老龄人口正在增加
全球老年人口的成长是人工智慧老年保护剂研发市场的主要驱动力。老年人口中与老龄化相关的疾病的盛行率不断上升,从而扩大了对针对老龄化生物学机制的创新治疗性介入的需求。此外,这种人口结构的变化给医疗保健系统带来了巨大压力,迫切需要有效且具预防性的抗衰老解决方案。因此,老龄化人口的成长直接推动了对人工智慧主导的老年保护剂研发的投资和研究,这些产品有望延长健康寿命,并减轻与老龄化相关疾病相关的经济负担。
技术基础设施的初始资本投入高
开发和应用用于药物研发的人工智慧演算法需要高效能运算 (HPC) 系统、海量资料储存解决方案以及专用软体,而所有这些成本都高得令人望而却步。招募一批由资料科学家、计算生物学家和人工智慧专家组成的高技能人才队伍,将进一步增加营运成本。如此高的经济障碍可能会扼杀创新,有效强化资金雄厚的现有企业的市场准入,并限制小型企业的参与。
个性化抗衰老方案的开发
利用人工智慧演算法,我们可以分析多组体学数据、生活方式因素和临床病史,从而识别患者特异性的衰老生物标记物,并预测个体对潜在抗衰老药物的反应。这项技术有助于开发高度客製化的治疗方法,以最大限度地提高疗效并最大限度地减少副作用。此外,这种个人化方法还可以在临床试验中对患者群体进行分层,从而优化研究设计并加快新型靶向抗衰老化合物的核准进程。
黑箱问题与人工智慧预测的可解释性
如果人工智慧系统产生潜在的抗衰老候选药物,却无法提供清晰、可解释的生物学基础见解,就会造成重大障碍。 FDA 和 EMA 等监管机构要求全面了解药物的作用机制才能批准。这种不透明性可能会削弱临床医生和研究人员的信心,延迟临床应用,并限制人工智慧衍生的发现广泛融入主流治疗开发平臺。
新冠疫情对人工智慧抗衰老药物研发市场产生了双重影响。最初,它扰乱了研究活动和供应链,导致与新冠疫情无关的计划暂时延迟。然而,它随后又成为重要的催化剂,凸显了先进计算方法在快速药物研发和再利用中的关键作用。疫情凸显了老龄化人口对新型病原体的脆弱性,并强调了延长健康寿命研究的重要性。这导致投资者对人工智慧驱动的生物技术平台的兴趣和资金投入增加,最终对市场成长产生了长期的正面影响。
机器学习 (ML) 将成为预测期内最大的细分市场
机器学习 (ML) 领域预计将在预测期内占据最大的市场占有率,这得益于其在海量生物数据集中识别复杂非线性模式方面无与伦比的能力。机器学习演算法,尤其是深度学习网络,非常擅长处理高通量筛检资料、基因组序列和蛋白质体学谱,从而预测新分子的生殖保护作用和毒性。它们能够不断从新数据中学习和改进,这对于目标识别、先导药物最适化和生物标记发现至关重要。这种多功能性及其在其他药物发现领域已证实的有效性,巩固了机器学习作为最大细分市场的地位。
预计肿瘤学在预测期内将以最高的复合年增长率成长
由于老化与致癌作用密切相关,肿瘤学领域预计将在预测期内呈现最高成长率。老龄化是癌症的主要风险因素,因为细胞损伤和老化的累积为肿瘤的形成创造了有利环境。许多抗衰老药物透过选择性清除癌前衰老细胞而展现出强大的抗癌活性。老化社会中癌症的高发性为能够同时针对基本老化过程和癌症发展的人工智慧发现疗法提供了清晰的临床路径和巨大的潜在市场,从而推动了该领域的成长。
预计北美将在预测期内占据最大的市场占有率,这得益于其领先的製药和生物技术公司、世界一流的学术研究机构以及强大的创业投资生态系统的协同效应。此外,支持性的法规结构,尤其是美国药物管理局(FDA),对人工智慧驱动的药物开发工具日益开放,正在促进市场发展。该地区先进的医疗基础设施和高昂的医疗成本进一步促进了尖端人工智慧技术的采用,巩固了其在人工智慧老年保护剂研发领域的领先地位。
预计亚太地区在预测期内将呈现最高的复合年增长率。这得益于生物技术和製药产业的显着扩张、政府推动医疗保健领域人工智慧创新的倡议增多,以及日本和中国等国家人口老化的快速发展。此外,老龄化疾病的盛行率不断上升,迫切需要有效的治疗性介入。增加对人工智慧新兴企业,以及在本地和全球参与者之间建立策略伙伴关係关係,是推动该地区市场加速扩张的关键因素。
According to Stratistics MRC, the Global AI Geroprotector Discovery Market is accounted for $316 million in 2025 and is expected to reach $1628 million by 2032 growing at a CAGR of 26.4% during the forecast period. AI Geroprotector Discovery refers to the application of artificial intelligence and machine learning to identify, screen, and optimize compounds or interventions that can slow, prevent, or reverse aging-related processes. By analyzing vast biological datasets, AI enables faster prediction of geroprotective potential, reduces trial-and-error in drug development, and accelerates precision targeting of aging mechanisms.
Rising global aging population
The escalating global geriatric demographic is a primary driver for the AI geroprotector discovery market. This population cohort exhibits a heightened prevalence of age-related disorders, thereby amplifying the demand for innovative therapeutic interventions that target the biological mechanisms of aging. Additionally, this demographic shift imposes a significant strain on healthcare systems, creating an urgent need for efficacious and preventative anti-aging solutions. Consequently, the rising aging population directly fuels investment and research into AI-driven discovery of geroprotectors, which promise to extend healthspan and mitigate the economic burden associated with age-related morbidity.
High initial capital investment for technology infrastructure
The development and application of AI algorithms for drug discovery necessitate access to high-performance computing (HPC) systems, vast data storage solutions, and specialized software, all of which entail exorbitant costs. The recruitment of a highly skilled workforce comprising data scientists, computational biologists, and AI specialists further escalates operational expenditures. This high financial barrier effectively consolidates market presence among well-funded established players and constrains the participation of small and medium-sized enterprises (SMEs), potentially stifling innovation.
Development of personalized geroprotective regimens
AI algorithms can be leveraged to analyze multi-omics data, lifestyle factors, and clinical histories to identify patient-specific aging biomarkers and predict individual responses to potential geroprotectors. This capability facilitates the development of highly tailored therapeutic regimens that maximize efficacy and minimize adverse effects. Furthermore, this personalized approach allows for the stratification of patient populations in clinical trials, enhancing trial design and accelerating the path to regulatory approval for novel, targeted anti-aging compounds.
The "Black Box" problem and interpretability of AI predictions
When AI systems generate a potential geroprotector candidate without providing clear, interpretable insights into the underlying biological rationale, it creates significant hurdles. Regulatory bodies like the FDA and EMA require a comprehensive understanding of a drug's mechanism of action for approval. This opacity can erode trust among clinicians and researchers, potentially delaying clinical translation and limiting the widespread integration of AI-derived discoveries into mainstream therapeutic development pipelines.
The COVID-19 pandemic had a dual impact on the AI geroprotector discovery market. Initially, it disrupted research activities and supply chains, causing temporary delays in non-COVID-related projects. However, it subsequently acted as a significant accelerator by underscoring the critical role of advanced computational approaches in rapid drug discovery and repurposing. The pandemic highlighted the vulnerabilities of the elderly population to novel pathogens, thereby reinforcing the importance of research into healthspan extension. This led to increased investor interest and funding directed towards AI-powered biotechnology platforms, ultimately netting a positive long-term effect on market growth.
The machine learning (ML) segment is expected to be the largest during the forecast period
The machine learning (ML) segment is expected to account for the largest market share during the forecast period due to its unparalleled proficiency in identifying complex, non-linear patterns within vast biological datasets. ML algorithms, particularly deep learning networks, are exceptionally adept at processing high-throughput screening data, genomic sequences, and proteomic profiles to predict the geroprotective efficacy and toxicity of novel molecules. Their ability to continuously learn and improve from new data makes them indispensable for target identification, lead optimization, and biomarker discovery. This versatility and proven effectiveness in other drug discovery domains solidify ML's position as the largest segment.
The oncology segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the oncology segment is predicted to witness the highest growth rate, driven by the profound intersection between aging and carcinogenesis. Aging is a primary risk factor for cancer, as the accumulation of cellular damage and senescence creates a permissive environment for tumorigenesis. Many geroprotectors, such as senolytics, exhibit strong anti-cancer potential by selectively eliminating premalignant senescent cells. The high incidence of cancer within the aging population presents a clear clinical pathway and a substantial addressable market for AI-discovered therapies that can simultaneously target fundamental aging processes and oncogenesis, which is fueling the segment growth.
During the forecast period, the North America region is expected to hold the largest market share, attributed to its synergistic confluence of leading pharmaceutical and biotechnology companies, world-class academic research institutions, and a robust venture capital ecosystem. Moreover, the presence of a supportive regulatory framework, particularly from the U.S. FDA, which is increasingly open to AI-derived drug development tools, facilitates market growth. The region's advanced healthcare infrastructure and high healthcare expenditure further enable the adoption of cutting-edge AI technologies, consolidating its position as the frontrunner in the AI geroprotector discovery landscape.
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, fueled by a significant expansion in its biotechnology and pharmaceutical sectors, increasing government initiatives aimed at fostering AI innovation in healthcare, and a rapidly aging population in countries like Japan and China. Additionally, the rising prevalence of age-related diseases is creating an urgent need for effective gerotherapeutic interventions. The growing investment in AI startups and the establishment of strategic partnerships between regional and global players are key factors catalyzing the market's accelerated expansion in this region.
Key players in the market
Some of the key players in AI Geroprotector Discovery Market include Insilico Medicine, Deep Longevity, Juvenescence, BioAge Labs, Calico, Recursion Pharmaceuticals, BenevolentAI, Xaira Therapeutics, Arda Therapeutics, InVivo Biosystems, Gero, Helix, Valo Health, Exscientia, Atomwise and BERG.
In June 2025, BioAge has launched an initiative to analyze over 17,000 samples from the HUNT Biobank in Norway to accelerate discovery of drug targets targeting the biology of aging. This molecular profiling is expected to expand insights and identify novel therapeutic targets for aging-related diseases.
In April 2024, AI-based drug developer Xaira Therapeutics has been launched with more than $1 billion in capital and a self-described ambitious commitment to transform drug discovery and development by creating new and more effective treatments faster.
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.