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1410106

精準醫療中的人工智慧 (AI) 市場：2023-2028 年預測

AI in Precision Medicine Market - Forecasts from 2023 to 2028

出版日期: 2023年12月14日 | 出版商:

Knowledge Sourcing Intelligence | 英文 149 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

2021年精準醫療市場人工智慧（AI）的市場規模為13.22億美元，預計在預測期內複合年成長率為27.63%。

在精準醫療領域，人工智慧正成為一股變革力量，將人工智慧的潛力與醫療保健結合，徹底改變患者照護。利用人工智慧演算法和機器學習技術，可以研究海量的患者資料，如基因圖譜、病歷、生活方式訊息，使我們能夠提供個人化、有針對性的治療方案。隨著醫療保健提供者和製藥公司看到了改善患者治療結果、提高診斷準確性和加快藥物研發過程的潛力，精準醫療領域的人工智慧 (AI) 市場正在迅速擴大。Masu。人工智慧驅動的平台可以檢測大資料集的模式和相關性，從而實現疾病風險預測和個人化治療的創建。隨著人工智慧的進步，它有望改變精準醫療的格局，提供新的技術來提供個人化的醫療干預，並徹底改變患者照護的未來。

資料分析和機器學習演算法的進步正在推動精準醫療領域人工智慧 (AI) 市場的成長。

資料分析和機器學習演算法的進步在人工智慧在精準醫療業務中的擴展中發揮關鍵作用。這些發展使醫療保健專業人員能夠分析大型且複雜的資料集，提取有用的見解，並更有效地設計個人化治療方法。機器學習演算法檢測患者資料中的模式和聯繫，以幫助疾病診斷、預後和治療效果評估。這些演算法準確性和效率的提高將加速人工智慧 (AI) 在精準醫療中的應用，為醫護人員提供強大的工具來提供有針對性的有效治療，並改善患者的治療效果。

精準醫療領域的人工智慧 (AI) 市場對個人化和標靶化治療方法的需求不斷成長。

對個人化和標靶治療方案的日益成長的需求正在推動人工智慧在精準醫療行業的興起。傳統的醫療方法通常依賴籠統的治療計劃，可能沒有考慮個別差異和特殊需求。但由於人工智慧的突破，醫療保健專業人員現在可以利用患者特定的資料來建立個人化治療。為了提案個人化治療方法，人工智慧系統可以分析遺傳資訊、病歷、生活方式和環境資料等各種因素。這種方法有可能提高治療效果、減少副作用並改善患者的治療結果。隨著個人化醫療對於提供更準確、更有效的醫療保健治療的重要性的認知，精準醫療領域對人工智慧的需求不斷增加。

精準醫療市場中的人工智慧 (AI) 可改善患者的治療效果和治療效果。

改善患者治療效果和治療效果是精準醫療市場中人工智慧應用的關鍵驅動力。根據發表在 JAMA Network Open 上的一項研究，精準醫療中採用的人工智慧演算法已證明能夠可靠地預測患者的結果和治療效果。在臨床決策流程中使用人工智慧可以將某些疾病的治療效果提高30-50%。《醫學網路研究期刊》上發表的另一項研究發現，使用人工智慧的精準醫療可減少 14%的不利事件和 25% 的再入院率。這些結果證明了人工智慧在改善治療方法、發現成功藥物和節省醫療成本方面的潛力。透過利用人工智慧的分析能力和資料主導的洞察力，醫療保健專業人員可以做出更明智的決策，從而改善患者的治療效果和治療效果，並最終提高護理品質。

北美是精準醫療領域人工智慧 (AI) 的市場領導者。

北美已成為精準醫療市場人工智慧的市場領導者。該地區的主導地位有幾個原因。首先，北美擁有強大的醫療基礎設施和先進的技術創新，支援人工智慧（AI）在精準醫療中的應用。此外，北美擁有頂尖的製藥和生物技術公司、研究機構和學術中心，有助於該公司的市場領導地位。該地區正大力投資人工智慧研發，推動精準醫療創新。此外，北美擁有有利的法律規範和支援政策，可以刺激人工智慧在醫療保健領域的應用。然而，有關精準醫療市場人工智慧（AI）關鍵領域的最新資訊，請參閱最新的市場報告。

人工智慧與基因定序和精準醫療的結合擴大了精準醫療領域人工智慧（AI）的市場規模

在醫療健康領域，基因定序、精準醫療和人工智慧的整合已成為重要的成長因素。基因定序產生大量遺傳資料，當使用人工智慧演算法進行分析時，可以發現與疾病相關的基因突變並提供個人化的治療方案。使用人工智慧進行基因組分析已顯示出可喜的結果，一些研究顯示罕見疾病的診斷率為 30%。人工智慧系統還可以根據基因圖譜預測藥物反應，從而實現更量身定做和有效的治療。人工智慧和基因定序的結合有可能改變精準醫療，根據個人的基因組成提供個人化治療，改善患者的治療結果和治療效果。

主要進展

2023 年7 月，人工智慧和精準醫療領域的先驅Tempos 與TScan Therapeutics 合作，TScan Therapeutics 是一家臨床階段的生物製藥公司，專注於為癌症患者開發TCR 工程T 細胞療法（TCR-T）。今天我們宣布了一項新的合作合作開發伴同性診斷 (CDx) 測試。該合作夥伴關係將支持 TScan 的 1 期固體癌臨床試驗篩檢程序，使患者能夠接受基於腫瘤抗原陽性和完整 HLA 表達的客製化 TCR-T 組合。
2021 年 9 月魁北克人工智慧研究所 (Mila) 今天宣布與人工智慧治療領域的領導者 Deep Genomics 建立合作夥伴關係。該協議允許該公司加入 Mila 的網路並從該研究所的研究業務中受益。深度基因組學利用人工智慧和機器學習來編程和選擇針對醫療需求未滿足的遺傳性疾病的突破性治療方法。
2023 年 6 月 Apptio Inc. 是財務和業務IT 管理及最佳化軟體領域的先驅，今天被 IBM 在與 Vista Equity Partners 的最終交易中以 46 億美元的價格收購。收購 Apptio 將加速 IBM 的 IT 自動化能力，並使管理人員能夠從其技術投資中獲得更大的商業價值。

公司產品

基因組序列測定： Tempus 提供完整的基因序列測定服務，創建高品質的遺傳資料，與臨床資料結合，可以揭示疾病發展和治療反應的見解。
研究合作計畫： 23andMe 與學術機構和製藥公司合作，收集資料遺傳和表現型資料用於研究。透過使用人工智慧分析這個龐大的資料集，研究人員可以發現遺傳見解並確定新的治療標靶。
SOPHiA DDM 平台： SOPHiA GENETICS 提供了一個全面的人工智慧平台，該平台使用機器學習和複雜的演算法來分析和解釋遺傳資料。該平台有助於識別致病突變、預測治療反應並指導個人化治療決策。

In the field of precision medicine, AI has emerged as a transformational force, merging the potential of artificial intelligence with healthcare to revolutionize patient care. The use of AI algorithms and machine learning techniques has allowed for the study of massive volumes of patient data, such as genetic profiles, medical records, and lifestyle information, to provide personalized and targeted treatment solutions. Artificial intelligence (AI) in precision medicine market is expanding rapidly as healthcare providers and pharmaceutical firms see its potential to improve patient outcomes, increase diagnosis accuracy, and expedite drug discovery processes. AI-powered platforms can detect patterns and correlations in large datasets, allowing for illness risk prediction and the creation of personalized therapies. As AI advances, it has enormous promise for changing the landscape of precision medicine, providing fresh techniques to deliver personalized healthcare interventions, and revolutionizing the future of patient care.

Advancements in Data Analytics and Machine Learning Algorithms bolsters AI in Precision Medicine Market Growth.

Data analytics and machine learning algorithms advancements have played a critical part in the expansion of AI in the precision medicine business. These developments have enabled healthcare practitioners to analyze massive and complicated datasets, extract useful insights, and design personalized treatment methods more efficiently. Machine learning algorithms detect patterns and connections in patient data, assisting in illness diagnosis, prognosis, and therapy response evaluation. These algorithms' enhanced accuracy and efficiency have accelerated the use of AI in precision medicine, providing healthcare practitioners with strong tools to perform targeted and effective therapies, thereby improving patient outcomes.

Rising Demand for Personalized and Targeted Treatment Approaches in AI in Precision Medicine Market.

The growing desire for personalized and targeted treatment options has aided AI's rise in the precision medicine business. Traditional healthcare approaches frequently rely on generalized treatment plans that may fail to account for individual differences and special demands. However, thanks to breakthroughs in artificial intelligence, healthcare professionals may now use patient-specific data to build personalized therapies. To develop personalized treatment recommendations, AI systems may analyze a variety of elements such as genetic information, medical history, lifestyle, and environmental data. This method has the potential to improve therapeutic efficacy, reduce side effects, and improve patient outcomes. The growing appreciation for the significance of personalized medicine in providing more precise and effective healthcare treatments has increased the demand for AI in the field of precision medicine.

Improving Patient Outcomes and Treatment Efficacy in AI in Precision Medicine Market.

Improving patient outcomes and treatment efficacy is a key driver in the precision medicine market's use of AI. AI algorithms employed in precision medicine have shown the capacity to reliably predict patient outcomes and treatment responses, according to a study published in JAMA Network Open. The use of AI in clinical decision-making processes has resulted in 30-50% better treatment results for specific disorders. Another study published in the Journal of Medical Internet Research discovered that AI-based precision medicine treatments reduced adverse events by 14% and hospital readmissions by 25%. These findings show AI's potential to improve treatment regimens, uncover successful medications, and save healthcare costs. Healthcare professionals may make more informed decisions by harnessing AI's analytical capacity and data-driven insights, resulting in better patient outcomes, increased treatment efficacy, and, ultimately, improved quality of care.

North America is the Market Leader in the AI in Precision Medicine Market.

North America has emerged as the market leader in AI in the precision medicine market. Several reasons contribute to the region's prominence. For starters, North America has a strong healthcare infrastructure and a high degree of technology innovation, which encourages the use of AI in precision medicine. Furthermore, the presence of top pharmaceutical and biotechnology businesses, research institutes, and academic centres in North America helps to the company's market leadership. Significant investments in AI research and development have occurred in the region, encouraging precision medical innovation. Furthermore, North America has a favourable regulatory framework and supporting policies that stimulate the use of artificial intelligence in healthcare. However, for the most up-to-date information on the leading region in the AI in precision medicine market, see the most recent market reports.

Integration of AI with Genomic Sequencing and Precision Medicine Enhances the AI in Precision Medicine Market Size.

In the healthcare business, the integration of AI with genome sequencing and precision medicine has become a crucial growth element. Genomic sequencing creates massive volumes of genetic data, which may then be analysed with AI algorithms to uncover disease-associated genetic variants and inform personalised treatment options. AI-powered genome analysis has yielded encouraging results, with studies claiming a 30% diagnosis yield in uncommon disorders. AI systems may also anticipate medication reactions based on genetic profiles, allowing for more tailored and effective therapy. The combination of AI with genomic sequencing has the potential to transform precision medicine by providing personalized treatments based on an individual's genetic composition, resulting in improved patient outcomes and treatment efficacy.

Key Developments:

In July 2023, Tempus, a pioneer in artificial intelligence and precision medicine, announced today a new collaboration to develop a companion diagnostic (CDx) test with TScan Therapeutics, a clinical-stage biopharmaceutical company focused on the development of TCR-engineered T cell therapies (TCR-T) for cancer patients. The partnership supports TScan's screening procedure for its Phase 1 solid tumour clinical trial, which is meant to allow patients to receive customised TCR-T mixes based on tumour antigen positivity and intact HLA expression.
In September 2021, Mila, the Quebec Artificial Intelligence Institute, announced today the beginning of a collaboration with Deep Genomics, a leader in therapeutic artificial intelligence therapies. This agreement will enable the firm to join Mila's network and take benefit of the research institute's recruitment operations. Deep Genomics employs artificial intelligence and machine learning to programme and choose revolutionary therapies for genetic illnesses with unmet medical needs.
In June 2023, Apptio Inc., a pioneer in financial and operational IT management and optimisation software, was purchased by IBM for $4.6 billion today in a formal deal with Vista Equity Partners. Apptio's purchase will accelerate IBM's IT automation capabilities and empower company executives to achieve greater business value from technology investments.

Company Products:

Genomic Sequencing: Tempus offers complete genome sequencing services, producing high-quality genetic data that may be combined with clinical data to reveal insights into disease development and therapy response.
Research Collaboration Program: 23andMe has worked with academic institutions and pharmaceutical businesses to collect vast amounts of genetic and phenotypic data for study. This massive dataset is analysed using AI, allowing researchers to unearth genetic insights and identify new treatment targets.
SOPHiA DDM Platform: SOPHiA GENETICS offers a comprehensive AI platform that analyses and interprets genetic data using machine learning and sophisticated algorithms. The platform aids in the identification of disease-causing variations, the prediction of therapy response, and the guidance of personalised treatment decisions.

Segmentation:

By Technology

Machine Learning
Natural Language Processing (Nlp)
Deep Learning
Big Data Analytics
Others

By Application

Drug Discovery And Development
Oncology
Genetic Testing
Rare Diseases
Infectious Diseases
Others

By End-User

Pharmaceutical And Biotechnology Companies
Research Institutes And Academic Centers
Healthcare Providers
Others

By Geography

North America
United States
Canada
Mexico
South America
Brazil
Argentina
Others
Europe
United Kingdom
Germany
France
Italy
Spain
Others
Middle East and Africa
Saudi Arabia
UAE
Others
Asia Pacific
Japan
China
India
South Korea
Indonesia
Taiwan
Others

1. INTRODUCTION

1.1. Market Overview
1.2. Market Definition
1.3. Scope of the Study
1.4. Market Segmentation
1.5. Currency
1.6. Assumptions
1.7. Base, and Forecast Years Timeline

2. RESEARCH METHODOLOGY

2.1. Research Data
2.2. Sources
2.3. Research Design

3. EXECUTIVE SUMMARY

3.1. Research Highlights

4. MARKET DYNAMICS

4.1. Market Drivers
4.2. Market Restraints
4.3. Porters Five Forces Analysis
- 4.3.1. Bargaining Power of Suppliers
- 4.3.2. Bargaining Power of Buyers
- 4.3.3. Threat of New Entrants
- 4.3.4. Threat of Substitutes
- 4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis

5. AI IN PRECISION MEDICINE MARKET, BY TECHNOLOGY

5.1. Introduction
5.2. Machine Learning
5.3. Natural Language Processing (NLP)
5.4. Deep Learning
5.5. Big Data Analytics
5.6. Others

6. AI IN PRECISION MEDICINE MARKET, BY APPLICATION

6.1. Introduction
6.2. Drug Discovery and Development
6.3. Oncology
6.4. Genetic Testing
6.5. Rare Diseases
6.6. Infectious Diseases
6.7. Others

7. AI IN PRECISION MEDICINE MARKET, BY END-USER

7.1. Introduction
7.2. Pharmaceutical and Biotechnology Companies
7.3. Research Institutes and Academic Centers
7.4. Healthcare Providers
7.5. Others

8. AI IN PRECISION MEDICINE MARKET, BY GEOGRAPHY

8.1. Introduction
8.2. North America
- 8.2.1. United States
- 8.2.2. Canada
- 8.2.3. Mexico
8.3. South America
- 8.3.1. Brazil
- 8.3.2. Argentina
- 8.3.3. Others
8.4. Europe
- 8.4.1. United Kingdom
- 8.4.2. Germany
- 8.4.3. France
- 8.4.4. Italy
- 8.4.5. Spain
- 8.4.6. Others
8.5. Middle East and Africa
- 8.5.1. Saudi Arabia
- 8.5.2. UAE
- 8.5.3. Others
8.6. Asia Pacific
- 8.6.1. Japan
- 8.6.2. China
- 8.6.3. India
- 8.6.4. South Korea
- 8.6.5. Indonesia
- 8.6.6. Taiwan
- 8.6.7. Others