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个人化医疗市场中的生成人工智慧 - 2018-2028 年全球产业规模、份额、趋势、机会和预测，按个人化医疗治疗、部署模型、最终用户区域和竞争细分

Generative AI in Personalized Medicine Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028 Segmented By Personalized Medicine Therapeutics, By Deployment Model, By End-User Region and Competition
出版日期: | 出版商: TechSci Research | 英文 181 Pages | 商品交期: 2-3个工作天内

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简介目录

2022 年，全球个人化医疗市场中的生成人工智慧价值为 1.5212 亿美元，预计在预测期内将强劲成长，到 2028 年CAGR为25.62%。全球个人化医疗市场中的生成人工智慧是一个充满活力且快速发展的领域处于人工智慧 (AI) 和医疗保健的交叉点。随着个人化医疗日益受到重视，利用生成式人工智慧已成为为个别患者量身定制医疗方案的变革力量。该市场的特点是应用先进演算法和机器学习技术来分析大量资料集，包括基因组学、蛋白质组学和患者记录。主要目标是破解复杂的模式和相关性，以指导临床医生设计个人化的治疗计划。

生成式人工智慧透过模拟和产生新的分子结构并预测其生物效应，在药物发现、治疗优化和疾病预测中发挥关键作用。由于复杂疾病的日益普及以及人们日益认识到传统一刀切的医疗保健方法的局限性，市场需求激增。该领域的公司正在积极开发创新的人工智慧解决方案，以提高诊断准确性、预测患者对特定疗法的反应，并最终改善临床结果。

将生成式人工智慧整合到医疗保健系统中也促进了科技公司、製药公司和医疗保健提供者之间的合作。监管机构正在密切关注与在个人化医疗中使用人工智慧相关的伦理影响和资料隐私问题，有助于在市场内建立指导方针和标准。随着全球个人化医疗市场中的生成人工智慧不断扩大，主要趋势包括多组学资料的整合、可解释人工智慧的兴起以增强信任和透明度，以及去中心化临床试验的出现。

市场概况
预测期 2024-2028
2022 年市场规模 1.5212亿美元
2028 年市场规模 5.9190亿美元
2023-2028 年CAGR 25.62%
成长最快的细分市场 医院和诊所
最大的市场 北美洲

随着利害关係人认识到生成人工智慧彻底改变医疗保健服务的潜力，并迎来一个真正个人化医疗的时代，即根据每个患者独特的基因组成和特征量身定制治疗方法，该市场有望实现显着增长。儘管互通性、监管合规性和道德考量等挑战仍然存在，但人工智慧技术的不断进步和整个行业的协作努力正在推动市场走向未来，精准医疗将成为全球医疗保健实践的基石。

目录

第 1 章：产品概述

  • 市场定义
  • 市场范围
    • 涵盖的市场
    • 考虑学习的年份
    • 主要市场区隔

第 2 章：研究方法

  • 研究目的
  • 基线方法
  • 主要产业伙伴
  • 主要协会和二手资料来源
  • 预测方法
  • 数据三角测量与验证
  • 假设和限制

第 3 章：执行摘要

  • 市场概况
  • 主要市场细分概述
  • 主要市场参与者概述
  • 重点地区/国家概况
  • 市场驱动因素、挑战、趋势概述

第 4 章：全球个人化医疗中的生成人工智慧市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 个人化医学治疗（药物、基因组医学、设备）
    • 按部署模型（本地、基于云端）
    • 按最终使用者（医院和诊所、门诊手术中心、其他）
    • 按地区
    • 按公司划分 (2022)
  • 市场地图
    • 透过个人化医学治疗
    • 按部署模型
    • 按最终用户
    • 按地区

第 5 章：亚太地区个人化医疗中的生成人工智慧市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过个人化医学治疗
    • 按部署模型
    • 按最终用户
    • 按国家/地区
  • 亚太地区：国家分析
    • 中国个人化医疗中的生成人工智慧
    • 印度个人化医疗中的生成人工智慧
    • 澳洲个人化医疗中的生成人工智慧
    • 日本个人化医疗中的生成人工智慧
    • 韩国个人化医疗中的生成人工智慧

第 6 章：欧洲个人化医疗中的生成人工智慧市场前景

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过个人化医学治疗
    • 按部署模型
    • 按最终用户
    • 按国家/地区
  • 欧洲：国家分析
    • 法国
    • 德国
    • 西班牙
    • 义大利
    • 英国

第 7 章：北美个人化医疗中的生成人工智慧市场前景

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过个人化医学治疗
    • 按部署模型
    • 按最终用户
    • 按国家/地区
  • 北美：国家分析
    • 美国
    • 墨西哥
    • 加拿大

第 8 章：南美洲个人化医疗市场展望中的生成人工智慧

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过个人化医学治疗
    • 按部署模型
    • 按最终用户
    • 按国家/地区
  • 南美洲：国家分析
    • 巴西
    • 阿根廷
    • 哥伦比亚

第 9 章：中东和非洲个人化医疗市场展望中的生成人工智慧

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过个人化医学治疗
    • 按部署模型
    • 按最终用户
    • 按国家/地区
  • MEA：国家分析
    • 南非个人化医疗中的生成人工智慧
    • 沙乌地阿拉伯个人化医疗中的生成人工智慧
    • 阿联酋个人化医疗中的生成人工智慧
    • 埃及个人化医疗中的生成人工智慧

第 10 章：市场动态

  • 司机
  • 挑战

第 11 章：市场趋势与发展

  • 最近的发展
  • 产品发布
  • 併购

第 12 章：个人化医疗市场中的全球生成人工智慧：SWOT 分析

第 13 章：波特的五力分析

  • 产业竞争
  • 新进入者的潜力
  • 供应商的力量
  • 客户的力量
  • 替代产品的威胁

第14章：竞争格局

  • 强生公司
    • Business Overview
    • Company Snapshot
    • Products & Services
    • Current Capacity Analysis
    • Financials (In case of listed)
    • Recent Developments
    • SWOT Analysis
  • 蝴蝶网
  • 深度基因体学
  • 谷歌有限责任公司
  • IBM 沃森健康
  • 微软公司
  • 艾多克
  • 英科医疗
  • 路径AI
  • 腾讯控股有限公司

第 15 章：策略建议

第 16 章：关于我们与免责声明

简介目录
Product Code: 20049

Global Generative AI in Personalized Medicine Market has valued at USD 152.12 million in 2022 and is anticipated to project robust growth in the forecast period with a CAGR of 25.62% through 2028. The Global Generative AI in Personalized Medicine Market is a dynamic and rapidly evolving sector at the intersection of artificial intelligence (AI) and healthcare. As personalized medicine gains prominence, leveraging generative AI has become a transformative force in tailoring medical treatments to individual patients. This market is characterized by the application of advanced algorithms and machine learning techniques to analyze vast datasets, including genomics, proteomics, and patient records. The primary goal is to decipher intricate patterns and correlations that can guide clinicians in designing personalized treatment plans.

Generative AI plays a pivotal role in drug discovery, treatment optimization, and disease prediction by simulating and generating new molecular structures and predicting their biological effects. The market witnesses a surge in demand due to the increasing prevalence of complex diseases and the growing recognition of the limitations of traditional one-size-fits-all approaches to healthcare. Companies in this space are actively developing innovative AI solutions to enhance diagnostic accuracy, predict patient responses to specific therapies, and ultimately improve clinical outcomes.

The integration of generative AI into healthcare systems is also fostering collaborations between technology firms, pharmaceutical companies, and healthcare providers. Regulatory bodies are closely monitoring the ethical implications and data privacy concerns associated with the use of AI in personalized medicine, contributing to the establishment of guidelines and standards within the market. As the Global Generative AI in Personalized Medicine Market continues to expand, key trends include the incorporation of multi-omics data, the rise of explainable AI to enhance trust and transparency, and the emergence of decentralized clinical trials.

Market Overview
Forecast Period2024-2028
Market Size 2022USD 152.12 Million
Market Size 2028USD 591.90 Million
CAGR 2023-202825.62%
Fastest Growing SegmentHospitals & Clinics
Largest MarketNorth America

The market is poised for significant growth as stakeholders recognize the potential of generative AI to revolutionize healthcare delivery and usher in an era of truly personalized medicine, where treatments are tailored to the unique genetic makeup and characteristics of each patient. While challenges such as interoperability, regulatory compliance, and ethical considerations persist, the ongoing advancements in AI technologies and collaborative efforts across the industry are driving the market towards a future where precision medicine becomes the cornerstone of healthcare practices worldwide.

Key Market Drivers

Rising Prevalence of Complex Diseases

The escalating prevalence of complex diseases has become a catalyst for the burgeoning growth of the global generative AI in personalized medicine market. The 21st century has witnessed a paradigm shift in healthcare, with an increasing focus on tailoring treatments to the unique genetic makeup of individuals. Complex diseases, characterized by multifaceted etiologies and intricate molecular mechanisms, present formidable challenges for traditional therapeutic approaches. As the incidence of conditions such as cancer, cardiovascular diseases, and neurological disorders continues to rise worldwide, there is a pressing need for innovative solutions that can decipher the intricate interplay of genetic, environmental, and lifestyle factors influencing disease progression.

generative artificial intelligence (AI) has emerged as a transformative force, offering unprecedented capabilities in data analysis, pattern recognition, and prediction. The ability of generative AI algorithms to sift through vast datasets, including genomic information, clinical records, and patient outcomes, enables the identification of subtle patterns and correlations that elude traditional analytical methods. This, in turn, empowers healthcare professionals with valuable insights into the underlying mechanisms of diseases, paving the way for more precise and personalized therapeutic interventions.

The demand for personalized medicine is intricately linked to the rising prevalence of complex diseases, as conventional one-size-fits-all approaches often prove insufficient in addressing the unique genetic variations and molecular profiles of individual patients. Generative AI plays a pivotal role in this shift towards personalized medicine by aiding in the identification of biomarkers, predicting patient responses to specific treatments, and optimizing therapeutic regimens based on individualized data. The integration of AI-driven technologies into the realm of healthcare not only enhances diagnostic accuracy but also streamlines the drug discovery and development process, ultimately leading to more effective and targeted therapies.

The global generative AI in personalized medicine market is witnessing a surge in investment and innovation, with pharmaceutical companies, research institutions, and technology firms actively contributing to its growth. As the healthcare industry embraces the potential of generative AI to unlock the complexities of diseases and deliver personalized treatment strategies, the market is poised for substantial expansion.

Advancements in Genomic Research

Advancements in genomic research stand as a driving force behind the flourishing Global Generative AI in Personalized Medicine Market. The completion of the Human Genome Project marked a watershed moment, providing an exhaustive blueprint of human DNA. Since then, ongoing breakthroughs in genomic technologies have exponentially increased the volume and complexity of genetic data available. Generative AI, equipped with sophisticated algorithms, has emerged as an indispensable tool to navigate and extract meaningful insights from this vast genomic landscape.

By rapidly analyzing and interpreting individual genetic variations, generative AI contributes to the identification of specific biomarkers, disease susceptibilities, and therapeutic targets. This capability is pivotal in tailoring medical treatments to the unique genetic makeup of each patient. As the field of genomics continues to evolve, with initiatives like precision medicine becoming mainstream, the demand for generative AI solutions in personalized medicine intensifies. The ability of generative AI to decipher the intricacies of genetic information positions it as a linchpin in the development and implementation of personalized treatment plans.

The synergy between advancements in genomic research and the computational power of generative AI not only expedites the understanding of genetic complexities but also catalyzes innovations in drug discovery, disease prediction, and treatment optimization. As the Generative AI in Personalized Medicine Market capitalizes on these advancements, it propels healthcare into an era where genomic insights, powered by AI, pave the way for a more targeted and effective approach to patient care. The seamless integration of generative AI and genomic research not only enhances diagnostic precision but also accelerates the realization of truly personalized medicine, where healthcare interventions are tailored to the distinct genetic profile of each individual. In essence, the symbiotic relationship between the relentless progress in genomic research and the transformative capabilities of generative AI underscores the pivotal role this dynamic duo plays in reshaping the landscape of personalized medicine and steering the healthcare industry towards a more individualized and effective future.

Drug Discovery and Development

Traditional drug discovery has long been a laborious and resource-intensive process, marked by high failure rates and protracted timelines. However, the integration of generative AI into this domain has ushered in a new era of efficiency and precision. AI-driven algorithms excel in the analysis of vast datasets, including molecular structures, biological pathways, and clinical trial outcomes. This analytical prowess enables researchers to identify potential drug candidates more rapidly and accurately than conventional methods, significantly reducing the time and costs associated with drug development.

In the realm of personalized medicine, where the focus is on tailoring treatments to the unique genetic and molecular profiles of individual patients, generative AI plays a pivotal role. The ability of AI algorithms to analyze genomic data and discern intricate patterns allows for the identification of specific biomarkers associated with diseases. This information is instrumental in the development of targeted therapies, ensuring that interventions are not only more efficacious but also tailored to the genetic nuances of each patient. The precision offered by generative AI in predicting patient responses to different drugs facilitates the selection of the most appropriate and effective treatment strategies, thereby enhancing overall therapeutic outcomes.

Pharmaceutical companies and research institutions are increasingly leveraging generative AI technologies to expedite the drug discovery and development process. Virtual screening of compounds, predictive modeling of drug interactions, and the identification of novel targets are among the many applications where AI proves invaluable. This synergy between generative AI and drug development aligns with the paradigm shift towards personalized medicine, where the goal is to move beyond a one-size-fits-all approach and deliver treatments that are finely tuned to the genetic makeup of each patient.

As the global demand for personalized medicine continues to rise, driven by an increasing prevalence of complex diseases and a growing emphasis on precision healthcare, the market for generative AI in this sector is experiencing a robust upswing. The convergence of cutting-edge technologies, such as machine learning, big data analytics, and genomics, positions generative AI as a transformative tool in the pursuit of more effective, personalized, and targeted therapies.

Key Market Challenges

Interoperability Challenges

Interoperability challenges stand as a significant hurdle in the path of the Global Generative AI in Personalized Medicine Market. As this innovative sector seeks to leverage the power of generative AI in tailoring medical treatments to individual patients, the seamless exchange of healthcare information becomes imperative. However, the healthcare ecosystem is characterized by a multitude of systems, platforms, and data formats, resulting in a fragmented landscape that inhibits effective interoperability.

One of the primary issues hindering interoperability in the Generative AI in Personalized Medicine Market is the lack of standardized formats and protocols for sharing healthcare data. Electronic health records (EHRs), laboratory results, and genomic information often reside in siloed systems that operate on different standards. This fragmentation makes it challenging to integrate these diverse datasets, hindering the efficient flow of information required for generative AI applications. The absence of standardized data formats creates a barrier to the seamless collaboration between healthcare providers, research institutions, and technology developer.

Additionally, interoperability challenges extend to the diverse range of devices and technologies used in healthcare settings. From diagnostic equipment to wearable devices that collect patient-generated data, the integration of these technologies with generative AI platforms becomes complex due to differing communication protocols and data structures. The lack of a standardized framework to enable interoperability between these devices impedes the comprehensive data exchange necessary for generative AI to reach its full potential in personalized medicine.

Data Privacy and Security Concerns

The burgeoning Global Generative AI in Personalized Medicine Market is encountering a formidable obstacle in the form of data privacy and security concerns. As the integration of generative AI technologies in healthcare becomes more widespread, the reliance on vast and sensitive datasets, including patient records and genomic information, raises ethical questions and challenges regarding the protection of personal health information.

One of the primary concerns in the Generative AI in Personalized Medicine Market revolves around the delicate nature of healthcare data. Patient information, often containing highly sensitive details about medical conditions, genetic predispositions, and treatment histories, is a prime target for cyber threats. Unauthorized access to such information not only jeopardizes individual privacy but also poses ethical challenges regarding the responsible use of patient data in the development of generative AI applications.

Ensuring patient consent and maintaining data ownership become critical aspects of navigating the intricate landscape of data privacy in the context of generative AI. As generative AI relies on extensive health-related datasets for training and analysis, establishing transparent and ethical frameworks for obtaining patient consent and clearly defining data ownership rights becomes paramount. Striking a balance between facilitating data accessibility for research purposes and safeguarding patient privacy is an ongoing challenge that the Generative AI in Personalized Medicine Market must address.

Key Market Trends

Integration of Multi-Omics Data

The integration of multi-omics data is proving to be a pivotal factor in propelling the global generative AI in personalized medicine market to new heights. As the field of genomics expands and evolves, the need to comprehensively understand the intricate interplay of various biological layers-genomics, transcriptomics, proteomics, metabolomics, and beyond-has become increasingly apparent. Multi-omics data integration involves the amalgamation of information from diverse molecular levels, providing a holistic view of the molecular landscape within an individual. This integration is particularly crucial in the context of personalized medicine, where the goal is to tailor healthcare interventions based on the unique genetic and molecular makeup of each patient.

Generative AI, with its capacity for advanced pattern recognition and complex data analysis, is ideally suited to tackle the challenges posed by multi-omics data. The sheer volume and complexity of information generated by different omics technologies require sophisticated computational approaches to extract meaningful insights. Generative AI algorithms excel in deciphering patterns and relationships within these multi-dimensional datasets, uncovering hidden correlations that can be pivotal in understanding disease mechanisms and predicting individual responses to treatments.

The synergy between multi-omics data integration and generative AI is reshaping the landscape of personalized medicine by enabling a more precise and comprehensive understanding of diseases. The identification of biomarkers across multiple omics layers allows for a nuanced characterization of diseases, facilitating the development of targeted therapies. By leveraging generative AI, researchers can discern complex molecular signatures indicative of disease subtypes, progression trajectories, and potential therapeutic targets.

The global market for generative AI in personalized medicine is witnessing a substantial upswing as the integration of multi-omics data becomes a cornerstone in advancing precision healthcare. Pharmaceutical companies, research institutions, and healthcare providers are increasingly recognizing the value of combining genomic, proteomic, and metabolomic information to tailor treatments to individual patients. This integration not only enhances diagnostic accuracy but also fuels innovation in drug discovery and development, paving the way for more effective and personalized therapeutic interventions.

Decentralized Clinical Trials

The adoption of decentralized clinical trials (DCTs) is emerging as a driving force behind the surging global market for generative AI in personalized medicine. Traditional clinical trial models often face challenges such as participant recruitment hurdles, geographical limitations, and the burden of in-person visits. Decentralized clinical trials leverage digital technologies, wearables, and remote monitoring to overcome these obstacles, allowing for greater participant diversity and inclusion while enhancing the efficiency of data collection. Generative AI, with its capacity for advanced analytics and pattern recognition, complements the decentralized approach by processing the wealth of data generated in these trials.

Generative AI facilitates the analysis of real-time, patient-generated data from wearables and other remote monitoring devices, providing continuous insights into individual health parameters. The ability to process and interpret this data in near real-time allows for a more dynamic and personalized understanding of patient responses to treatments. Machine learning algorithms can identify subtle patterns and correlations within the vast datasets, aiding in the identification of biomarkers, predicting individual responses to interventions, and optimizing personalized treatment regimens.

The decentralization of clinical trials aligns with the broader shift toward personalized medicine, as it enables the inclusion of a more diverse and representative participant pool. This diversity is crucial for capturing the variability in treatment responses based on genetic, environmental, and lifestyle factors. Generative AI serves as a linchpin in this decentralized paradigm by transforming the copious amounts of patient-generated data into actionable insights. The integration of AI-driven analytics into decentralized clinical trials not only accelerates the pace of data analysis but also enhances the overall quality and depth of information gleaned from participants.

Pharmaceutical companies, contract research organizations (CROs), and other stakeholders are increasingly recognizing the value of combining decentralized clinical trials with generative AI to streamline the drug development process and deliver more personalized healthcare solutions. The global market for generative AI in personalized medicine is witnessing a notable upswing as a result of this convergence, with innovative applications ranging from remote patient monitoring to predictive modeling of treatment outcomes.

Segmental Insights

Personalized Medicine Therapeutics Insights

Based on the Personalized Medicine Therapeutics, Pharmaceuticals emerged as the dominant segment in the global market for Global Generative AI in Personalized Medicine in 2022. Generative AI, with its ability to analyze vast and complex datasets, becomes an invaluable tool in the development and optimization of personalized pharmaceuticals. The intricate nature of biological systems, coupled with the vast variability among individuals, requires advanced computational approaches to decipher patterns and identify optimal treatment strategies. Generative AI excels in simulating molecular interactions, predicting drug responses, and optimizing treatment regimens based on individual patient data.

Deployment Model Insights

Based on the Deployment Model, Cloud Based emerged as the dominant segment in the global market for Global Generative AI in Personalized Medicine Market in 2022. The nature of generative AI applications involves the processing and analysis of vast datasets, including genomics, clinical records, and other healthcare-related information. Cloud-based deployment provides the scalability and computational power required to handle these extensive datasets efficiently. The ability to scale resources dynamically allows organizations to manage the computational demands of generative AI applications, ensuring optimal performance and responsiveness. Secondly, cloud-based deployment models offer accessibility and flexibility, crucial factors in the rapidly evolving field of personalized medicine.

Regional Insights

North America emerged as the dominant player in the Global Generative AI in Personalized Medicine Market in 2022, holding the largest market share. North America houses several prominent technology companies that play a pivotal role in shaping the landscape of artificial intelligence, including generative AI. The collaboration between healthcare institutions and tech companies in the region fosters the development and implementation of advanced AI solutions tailored for personalized medicine applications. North America consistently allocates a significant portion of its GDP to healthcare. The high healthcare expenditure indicates a willingness to invest in state-of-the-art technologies that can improve patient outcomes, enhance diagnostic accuracy, and advance personalized medicine. Generative AI, with its potential to revolutionize healthcare practices, aligns with the region's commitment to delivering high-quality patient care...

Key Market Players

Syntegra

NioyaTech

Saxon

IBM Watson

Microsoft Corporation

Google LLC

Tencent Holdings Ltd.

Neuralink Corporation

Johnson & Johnson

OpenAI

Oracle

Report Scope:

In this report, the Global Generative AI in Personalized Medicine Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Global Generative AI in Personalized Medicine Market, By Personalized Medicine Therapeutics:

  • Pharmaceutical
  • Genomic Medicine
  • Devices

Global Generative AI in Personalized Medicine Market, By Deployment Model:

  • On-premises
  • Cloud Based

Global Generative AI in Personalized Medicine Market, By End-User:

  • Hospitals and Clinics
  • Ambulatory Surgical Centers
  • Others

Global Generative AI in Personalized Medicine Market, By Region:

  • North America
  • United States
  • Canada
  • Mexico
  • Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
  • Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • South America
  • Brazil
  • Argentina
  • Colombia
  • Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE
  • Kuwait
  • Turkey
  • Egypt

Competitive Landscape

  • Company Profiles: Detailed analysis of the major companies present in the Global Generative AI in Personalized Medicine Market.

Available Customizations:

  • Global Generative AI in Personalized Medicine Market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, Trends

4. Global Generative AI in Personalized Medicine Market Outlook

  • 4.1. Market Size & Forecast
    • 4.1.1. By Value
  • 4.2. Market Share & Forecast
    • 4.2.1. By Personalized Medicine Therapeutics (Pharmaceutical, Genomic Medicine, Devices)
    • 4.2.2. By Deployment Model (On-premises, Cloud Based)
    • 4.2.3. By End-User (Hospitals and Clinics, Ambulatory Surgical Centers, Others)
    • 4.2.4. By Region
    • 4.2.5. By Company (2022)
  • 4.3. Market Map
    • 4.3.1. By Personalized Medicine Therapeutics
    • 4.3.2. By Deployment Model
    • 4.3.3. By End-User
    • 4.3.4. By Region

5. Asia Pacific Generative AI in Personalized Medicine Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Personalized Medicine Therapeutics
    • 5.2.2. By Deployment Model
    • 5.2.3. By End-User
    • 5.2.4. By Country
  • 5.3. Asia Pacific: Country Analysis
    • 5.3.1. China Generative AI in Personalized Medicine Market Outlook
      • 5.3.1.1. Market Size & Forecast
        • 5.3.1.1.1. By Value
      • 5.3.1.2. Market Share & Forecast
        • 5.3.1.2.1. By Personalized Medicine Therapeutics
        • 5.3.1.2.2. By Deployment Model
        • 5.3.1.2.3. By End-User
    • 5.3.2. India Generative AI in Personalized Medicine Market Outlook
      • 5.3.2.1. Market Size & Forecast
        • 5.3.2.1.1. By Value
      • 5.3.2.2. Market Share & Forecast
        • 5.3.2.2.1. By Personalized Medicine Therapeutics
        • 5.3.2.2.2. By Deployment Model
        • 5.3.2.2.3. By End-User
    • 5.3.3. Australia Generative AI in Personalized Medicine Market Outlook
      • 5.3.3.1. Market Size & Forecast
        • 5.3.3.1.1. By Value
      • 5.3.3.2. Market Share & Forecast
        • 5.3.3.2.1. By Personalized Medicine Therapeutics
        • 5.3.3.2.2. By Deployment Model
        • 5.3.3.2.3. By End-User
    • 5.3.4. Japan Generative AI in Personalized Medicine Market Outlook
      • 5.3.4.1. Market Size & Forecast
        • 5.3.4.1.1. By Value
      • 5.3.4.2. Market Share & Forecast
        • 5.3.4.2.1. By Personalized Medicine Therapeutics
        • 5.3.4.2.2. By Deployment Model
        • 5.3.4.2.3. By End-User
    • 5.3.5. South Korea Generative AI in Personalized Medicine Market Outlook
      • 5.3.5.1. Market Size & Forecast
        • 5.3.5.1.1. By Value
      • 5.3.5.2. Market Share & Forecast
        • 5.3.5.2.1. By Personalized Medicine Therapeutics
        • 5.3.5.2.2. By Deployment Model
        • 5.3.5.2.3. By End-User

6. Europe Generative AI in Personalized Medicine Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Personalized Medicine Therapeutics
    • 6.2.2. By Deployment Model
    • 6.2.3. By End-User
    • 6.2.4. By Country
  • 6.3. Europe: Country Analysis
    • 6.3.1. France Generative AI in Personalized Medicine Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Personalized Medicine Therapeutics
        • 6.3.1.2.2. By Deployment Model
        • 6.3.1.2.3. By End-User
    • 6.3.2. Germany Generative AI in Personalized Medicine Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Personalized Medicine Therapeutics
        • 6.3.2.2.2. By Deployment Model
        • 6.3.2.2.3. By End-User
    • 6.3.3. Spain Generative AI in Personalized Medicine Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Personalized Medicine Therapeutics
        • 6.3.3.2.2. By Deployment Model
        • 6.3.3.2.3. By End-User
    • 6.3.4. Italy Generative AI in Personalized Medicine Market Outlook
      • 6.3.4.1. Market Size & Forecast
        • 6.3.4.1.1. By Value
      • 6.3.4.2. Market Share & Forecast
        • 6.3.4.2.1. By Personalized Medicine Therapeutics
        • 6.3.4.2.2. By Deployment Model
        • 6.3.4.2.3. By End-User
    • 6.3.5. United Kingdom Generative AI in Personalized Medicine Market Outlook
      • 6.3.5.1. Market Size & Forecast
        • 6.3.5.1.1. By Value
      • 6.3.5.2. Market Share & Forecast
        • 6.3.5.2.1. By Personalized Medicine Therapeutics
        • 6.3.5.2.2. By Deployment Model
        • 6.3.5.2.3. By End-User

7. North America Generative AI in Personalized Medicine Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Personalized Medicine Therapeutics
    • 7.2.2. By Deployment Model
    • 7.2.3. By End-User
    • 7.2.4. By Country
  • 7.3. North America: Country Analysis
    • 7.3.1. United States Generative AI in Personalized Medicine Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Personalized Medicine Therapeutics
        • 7.3.1.2.2. By Deployment Model
        • 7.3.1.2.3. By End-User
    • 7.3.2. Mexico Generative AI in Personalized Medicine Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Personalized Medicine Therapeutics
        • 7.3.2.2.2. By Deployment Model
        • 7.3.2.2.3. By End-User
    • 7.3.3. Canada Generative AI in Personalized Medicine Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Personalized Medicine Therapeutics
        • 7.3.3.2.2. By Deployment Model
        • 7.3.3.2.3. By End-User

8. South America Generative AI in Personalized Medicine Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Personalized Medicine Therapeutics
    • 8.2.2. By Deployment Model
    • 8.2.3. By End-User
    • 8.2.4. By Country
  • 8.3. South America: Country Analysis
    • 8.3.1. Brazil Generative AI in Personalized Medicine Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Personalized Medicine Therapeutics
        • 8.3.1.2.2. By Deployment Model
        • 8.3.1.2.3. By End-User
    • 8.3.2. Argentina Generative AI in Personalized Medicine Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Personalized Medicine Therapeutics
        • 8.3.2.2.2. By Deployment Model
        • 8.3.2.2.3. By End-User
    • 8.3.3. Colombia Generative AI in Personalized Medicine Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Personalized Medicine Therapeutics
        • 8.3.3.2.2. By Deployment Model
        • 8.3.3.2.3. By End-User

9. Middle East and Africa Generative AI in Personalized Medicine Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Personalized Medicine Therapeutics
    • 9.2.2. By Deployment Model
    • 9.2.3. By End-User
    • 9.2.4. By Country
  • 9.3. MEA: Country Analysis
    • 9.3.1. South Africa Generative AI in Personalized Medicine Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Personalized Medicine Therapeutics
        • 9.3.1.2.2. By Deployment Model
        • 9.3.1.2.3. By End-User
    • 9.3.2. Saudi Arabia Generative AI in Personalized Medicine Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Personalized Medicine Therapeutics
        • 9.3.2.2.2. By Deployment Model
        • 9.3.2.2.3. By End-User
    • 9.3.3. UAE Generative AI in Personalized Medicine Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Personalized Medicine Therapeutics
        • 9.3.3.2.2. By Deployment Model
        • 9.3.3.2.3. By End-User
    • 9.3.4. Egypt Generative AI in Personalized Medicine Market Outlook
      • 9.3.4.1. Market Size & Forecast
        • 9.3.4.1.1. By Value
      • 9.3.4.2. Market Share & Forecast
        • 9.3.4.2.1. By Personalized Medicine Therapeutics
        • 9.3.4.2.2. By Deployment Model
        • 9.3.4.2.3. By End-User

10. Market Dynamics

  • 10.1. Drivers
  • 10.2. Challenges

11. Market Trends & Developments

  • 11.1. Recent Developments
  • 11.2. Product Launches
  • 11.3. Mergers & Acquisitions

12. Global Generative AI in Personalized Medicine Market: SWOT Analysis

13. Porter's Five Forces Analysis

  • 13.1. Competition in the Industry
  • 13.2. Potential of New Entrants
  • 13.3. Power of Suppliers
  • 13.4. Power of Customers
  • 13.5. Threat of Substitute Product
  • 13.6.

14. Competitive Landscape

  • 14.1. Johnson & Johnson
    • 14.1.1. Business Overview
    • 14.1.2. Company Snapshot
    • 14.1.3. Products & Services
    • 14.1.4. Current Capacity Analysis
    • 14.1.5. Financials (In case of listed)
    • 14.1.6. Recent Developments
    • 14.1.7. SWOT Analysis
  • 14.2. Butterfly Network
  • 14.3. Deep Genomics
  • 14.4. Google LLC
  • 14.5. IBM Watson Health
  • 14.6. Microsoft Corporation
  • 14.7. Aidoc
  • 14.8. Insilico Medicine
  • 14.9. PathAI
  • 14.10. Tencent Holdings Ltd.

15. Strategic Recommendations

16. About Us & Disclaimer