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藥物開發以基因為基之藥物開發人工智能人工智能藥物研發

市場調查報告書

商品編碼

1995877

基因組學市場中的人工智慧 (AI)：策略洞察與預測 (2026–2031)

Artificial Intelligence (AI) in Genomics Market - Strategic Insights and Forecasts (2026-2031)

出版日期: 2026年03月02日 | 出版商:

Knowledge Sourcing Intelligence | 英文 144 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

全球基因組學領域的人工智慧 (AI) 市場預計將從 2026 年的 34 億美元成長到 2031 年的 143 億美元，複合年成長率為 33.3%。

基因組學領域的人工智慧（AI）市場處於先進數據分析與生命科學創新的交匯點。隨著醫療保健系統向精準醫療、個人化療法和數據驅動診斷轉型，該領域正迅速擴張。定序技術產生的基因組數據量日益成長，對能夠提取有意義的生物學見解的計算工具的需求也隨之強勁成長。人工智慧技術正日益融入研究、藥物發現和臨床決策，進一步提升了該市場在整個醫療保健和生物技術生態系統中的戰略重要性。

宏觀經濟促進因素包括全球疾病負擔（尤其是癌症）的加重、基因組學研究投資的增加以及藥物研發管線的擴展。人工智慧能夠高效分析複雜的基因數據，從而支持標靶治療的開發並改善患者預後。運算能力、數位醫療基礎設施和不斷擴展的基因組資料庫的整合正在加速人工智慧在研發和臨床領域的應用。

市場促進因素

精準醫療需求的日益成長是推動成長的主要動力。醫療服務提供者正擴大利用基因訊息，根據患者的個別特徵最佳化治療方案。人工智慧工具能夠分析大規模基因組數據，幫助識別疾病風險、治療路徑和治療結果。這項能力在腫瘤學領域尤其重要，因為早期檢測和標靶治療至關重要。

製藥和生物技術產業也在推動人工智慧的應用。人工智慧透過識別疾病相關的遺傳標記、預測治療反應和縮短研究週期，加速了藥物研發進程。分析大規模基因組資料集的能力提高了識別治療標靶的準確性和效率。基因組研究投入的增加和定序成本的降低進一步推動了對人工智慧分析工具的需求。

全球癌症發生率不斷上升，以及對更廣泛疾病管理的需求日益成長，正在推動市場發展。人工智慧驅動的基因組學有助於早期檢測和個人化治療方案的製定，從而改善臨床療效，並最終在長期內降低醫療成本。

市場限制因素

儘管成長潛力巨大，但仍存在一些結構性挑戰。基因組數據的複雜性需要高效能運算基礎設施和先進的分析能力，這可能會增加營運成本。此外，不同資料來源的整合也為研究系統和臨床系統之間的互通性帶來了挑戰。

數據品質和標準化問題限制了人工智慧模型的可靠性，尤其是在臨床應用中。基因組資料集的差異性和隱私問題會限制資料共用和模型訓練。有關病患資料使用的法規和倫理考量也給參與企業帶來了合規負擔。

此外，在醫療保健環境中，人工智慧產生的見解的可解釋性對於臨床可靠性和決策至關重要，但採用人工智慧仍然面臨障礙。

對技術和細分市場的洞察

在市場區隔中，產品分為軟體工具和服務兩大類。軟體平台構成基因組數據解讀的分析基礎，而服務則支持實施、諮詢和研究整合。

就應用領域而言，精準醫療是主要應用場景，其次是診斷和預後、藥物發現和開發以及農業基因組學。藥物發現應用尤其重要，因為它們需要有效率地識別基因標靶和治療路徑。

終端用戶包括製藥和生物技術公司、學術和研究機構、醫院以及診斷中心。由於基因組治療方法研發需求旺盛且投資不斷增加，製藥公司仍是主要採用者。

從區域上看，北美佔據了較大的市場佔有率，這得益於其強大的研究基礎設施、先進的醫療保健系統以及對基因組學創新的巨額投資。

競爭格局與策略展望

競爭格局包括技術提供者、基因組學專家和醫療保健分析公司。主要企業致力於開發先進的人工智慧模型、擴展數據整合能力並加強研究合作。

生物技術公司與人工智慧技術公司之間的策略合作日益增加。對預測分析、疾病風險建模和個人化治療平台的投資正在推動創新。定序、計算生物學和知識圖譜分析等領域的持續技術進步可望提升市場競爭力。

市場競爭也受到研究經費、平台擴充性和監管合規框架的影響。

重點

基因組學領域的人工智慧市場正發展成為現代醫療創新不可或缺的一部分。對精準醫療的強勁需求、計算分析技術的快速發展以及不斷擴大的研究活動正在推動該領域的持續成長。儘管數據管理和監管方面的挑戰仍然存在，但持續的技術進步和策略合作有望支撐市場的長期擴張。

本報告的主要益處

深入分析：獲得跨地區、客戶群、政策、社會經濟因素、消費者偏好和產業領域的詳細市場洞察。
競爭格局：了解主要企業的策略趨勢，並確定最佳的市場進入方式。
市場促進因素和未來趨勢：我們將評估影響市場的主要成長要素和新興趨勢。
實用建議：我們支援制定策略決策以開發新的收入來源。
適合各類讀者：非常適合Start-Ups、研究機構、顧問公司、中小企業和大型企業。

我們的報告的使用範例

產業和市場洞察、機會評估、產品需求預測、打入市場策略、區域擴張、資本投資決策、監管分析、新產品開發和競爭情報。

報告範圍

2021年至2025年的歷史數據和2026年至2031年的預測數據
成長機會、挑戰、供應鏈前景、法律規範與趨勢分析
評估競爭對手的市場定位、策略和市場佔有率。
細分市場和區域銷售成長及預測評估
公司簡介，包括策略、產品、財務狀況和主要發展動態。

北美洲
- 報價
- 透過使用
- 最終用戶
- 國家
  - 美國
  - 加拿大
  - 墨西哥
南美洲
- 報價
- 透過使用
- 最終用戶
- 國家
  - 巴西
  - 阿根廷
  - 其他
歐洲
- 報價
- 透過使用
- 最終用戶
- 國家
  - 英國
  - 德國
  - 法國
  - 西班牙
  - 其他
中東和非洲
- 報價
- 透過使用
- 最終用戶
- 國家
  - 沙烏地阿拉伯
  - 以色列
  - UAE
  - 其他
亞太地區
- 報價
- 透過使用
- 最終用戶
- 國家
  - 中國
  - 日本
  - 印度
  - 韓國
  - 澳洲
  - 越南
  - 印尼
  - 其他

第9章：競爭環境與分析

主要企業及策略分析
市佔率分析
合併、收購、協議和合作關係
競爭環境儀錶板

第10章：公司簡介

IBM
Sophia Genetics SA
QIAGEN NV
Fabric Genomics, Inc.
Congenica Ltd.
Illumina, Inc.
Freenome Holdings, Inc.
Data4cure, Inc.
Tempus Labs, Inc.
NVIDIA Corporation

簡介目錄

Product Code: KSI061614431

The Global Artificial Intelligence (AI) in Genomics market is forecast to grow at a CAGR of 33.3%, reaching USD 14.3 billion in 2031 from USD 3.4 billion in 2026.

The artificial intelligence in genomics market is positioned at the intersection of advanced data analytics and life sciences innovation. The sector is expanding rapidly as healthcare systems shift toward precision medicine, personalized therapies, and data-driven diagnostics. Growing volumes of genomic data generated through sequencing technologies are creating strong demand for computational tools capable of extracting meaningful biological insights. AI technologies are increasingly embedded in research, drug discovery, and clinical decision-making, strengthening the strategic importance of this market across healthcare and biotechnology ecosystems.

Macroeconomic drivers include rising global disease burden, particularly cancer, increasing investments in genomics research, and expanding pharmaceutical research pipelines. AI is enabling efficient analysis of complex genetic data, supporting targeted treatment development and improved patient outcomes. The convergence of computing power, digital health infrastructure, and expanding genomic databases is accelerating adoption across both research and clinical environments.

Market Drivers

The growing demand for precision medicine is a primary growth catalyst. Healthcare providers are increasingly using genetic information to tailor treatments based on individual patient profiles. AI tools enable large-scale genomic data interpretation, helping identify disease risks, treatment pathways, and therapy effectiveness. This capability is particularly valuable in oncology, where early detection and targeted therapies are critical.

Pharmaceutical and biotechnology industries are also driving adoption. AI accelerates drug discovery by identifying genetic markers linked to disease, predicting treatment responses, and reducing research timelines. The ability to analyze large genomic datasets improves accuracy and efficiency in identifying therapeutic targets. Increasing investment in genomic research and declining sequencing costs are further supporting demand for AI-enabled analytical tools.

Rising global cancer incidence and broader disease management needs are strengthening market momentum. AI-based genomics supports early detection and personalized treatment planning, improving clinical outcomes and reducing healthcare costs over time.

Market Restraints

Despite strong growth potential, several structural challenges remain. Genomic data complexity requires high-performance computing infrastructure and advanced analytical capabilities, which can increase operational costs. Integration of diverse data sources also presents interoperability challenges across research and clinical systems.

Data quality and standardization issues limit the reliability of AI models, particularly in clinical applications. Variability in genomic datasets and privacy concerns can restrict data sharing and model training. Regulatory and ethical considerations around patient data usage also create compliance burdens for market participants.

Additionally, adoption barriers remain in healthcare environments where interpretability of AI-generated insights is critical for clinical trust and decision-making.

Technology and Segment Insights

The market is segmented by offering into software tools and services. Software platforms form the analytical backbone of genomic data interpretation, while services support implementation, consulting, and research integration.

By application, precision medicine represents a central use case, followed by diagnosis and prognosis, drug discovery and development, and agricultural genomics. Drug discovery applications are particularly significant due to the need for efficient identification of genetic targets and therapeutic pathways.

End-user segmentation includes pharmaceutical and biotechnology companies, academic and research institutions, and hospitals and diagnostic centers. Pharmaceutical companies remain major adopters due to intensive research requirements and growing investment in genomic-based therapies.

Geographically, North America holds a substantial market share, supported by strong research infrastructure, advanced healthcare systems, and significant investment in genomics innovation.

Competitive and Strategic Outlook

The competitive environment includes technology providers, genomics specialists, and healthcare analytics firms. Key players are focused on developing advanced AI models, expanding data integration capabilities, and strengthening research collaborations.

Strategic partnerships between biotech firms and AI technology companies are increasing. Investment in predictive analytics, disease risk modeling, and personalized treatment platforms is shaping innovation. Ongoing technological development in sequencing, computational biology, and knowledge graph analytics is expected to enhance market capabilities.

Market competition is also influenced by research funding, platform scalability, and regulatory compliance frameworks.

Key Takeaways

The artificial intelligence in genomics market is evolving into a critical component of modern healthcare innovation. Strong demand for precision medicine, rapid advances in computational analytics, and expanding research activity are driving sustained growth. While data management and regulatory challenges persist, continued technological progress and strategic collaborations are expected to support long-term market expansion.

Key Benefits of this Report

Insightful Analysis: Gain detailed market insights across regions, customer segments, policies, socio-economic factors, consumer preferences, and industry verticals.
Competitive Landscape: Understand strategic moves by key players to identify optimal market entry approaches.
Market Drivers and Future Trends: Assess major growth forces and emerging developments shaping the market.
Actionable Recommendations: Support strategic decisions to unlock new revenue streams.
Caters to a Wide Audience: Suitable for startups, research institutions, consultants, SMEs, and large enterprises.

What businesses use our reports for

Industry and market insights, opportunity assessment, product demand forecasting, market entry strategy, geographical expansion, capital investment decisions, regulatory analysis, new product development, and competitive intelligence.

Report Coverage

Historical data from 2021 to 2025 and forecast data from 2026 to 2031
Growth opportunities, challenges, supply chain outlook, regulatory framework, and trend analysis
Competitive positioning, strategies, and market share evaluation
Revenue growth and forecast assessment across segments and regions
Company profiling including strategies, products, financials, and key developments

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
1.8. Key Benefits for the Stakeholders

2. RESEARCH METHODOLOGY

2.1. Research Design
2.2. Research Process

3. EXECUTIVE SUMMARY

3.1. Key Findings

4. MARKET DYNAMICS

4.1. Market Drivers
4.2. Market Restraints
4.3. Porter's 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
4.5. Analyst View

5. AI IN GENOMICS MARKET BY OFFERING

5.1. Introduction
5.2. Software tools
5.3. Services

6. AI IN GENOMICS MARKET BY APPLICATION

6.1. Introduction
6.2. Precision medicine
6.3. Diagnosis and prognosis
6.4. Drug discovery and development
6.5. Agriculture and animal breeding
6.6. Others

7. AI IN GENOMICS MARKET BY END-USER

7.1. Introduction
7.2. Pharmaceutical and biotechnology companies
7.3. Academic and research institutes
7.4. Hospitals and diagnostic centers
7.5. Others

8. AI IN GENOMICS MARKET BY GEOGRAPHY

8.1. Introduction
8.2. North America
- 8.2.1. By Offering
- 8.2.2. By Application
- 8.2.3. By End-User
- 8.2.4. By Country
  - 8.2.4.1. USA
  - 8.2.4.2. Canada
  - 8.2.4.3. Mexico
8.3. South America
- 8.3.1. By Offering
- 8.3.2. By Application
- 8.3.3. By End-User
- 8.3.4. By Country
  - 8.3.4.1. Brazil
  - 8.3.4.2. Argentina
  - 8.3.4.3. Others
8.4. Europe
- 8.4.1. By Offering
- 8.4.2. By Application
- 8.4.3. By End-User
- 8.4.4. By Country
  - 8.4.4.1. United Kingdom
  - 8.4.4.2. Germany
  - 8.4.4.3. France
  - 8.4.4.4. Spain
  - 8.4.4.5. Others
8.5. Middle East and Africa
- 8.5.1. By Offering
- 8.5.2. By Application
- 8.5.3. By End-User
- 8.5.4. By Country
  - 8.5.4.1. Saudi Arabia
  - 8.5.4.2. Israel
  - 8.5.4.3. UAE
  - 8.5.4.4. Others
8.6. Asia Pacific
- 8.6.1. By Offering
- 8.6.2. By Application
- 8.6.3. By End-User
- 8.6.4. By Country
  - 8.6.4.1. China
  - 8.6.4.2. Japan
  - 8.6.4.3. India
  - 8.6.4.4. South Korea
  - 8.6.4.5. Australia
  - 8.6.4.6. Vietnam
  - 8.6.4.7. Indonesia
  - 8.6.4.8. Others