計算生物學市場機會、成長促進因素、產業趨勢分析及預測（2025-2034年）

2024 年全球計算生物學市場價值為 71 億美元，預計到 2034 年將以 12.3% 的複合年成長率成長至 227 億美元。

計算模型在臨床研究中的日益普及、藥物研發成本和複雜性的不斷攀升，以及生物資訊學和人工智慧的持續進步，共同推動了這一領域的成長。組學資料量的激增、政府政策的支持以及人工智慧驅動分析應用的不斷擴展，都在加速計算生物學解決方案的普及。傳統的藥物發現仍然耗時且耗力，往往需要十年以上的時間，這促使製藥公司採用計算工具來簡化研發流程、減少實驗失敗，並在早期階段識別有前景的候選藥物。這些技術支援生物模擬、藥物-標靶交互作用建模以及基於組學研究的數據驅動型洞察，從而顯著縮短實驗室時間並改善臨床試驗結果。製藥業面臨越來越大的壓力，需要更快、更低成本地開發出有效的療法，這持續推動計算生物學的發展。此外，計算生物學在臨床試驗設計、患者分層和生物標記發現方面日益成長的影響力，正在改變療法的開發和驗證方式。

預計到2024年，分析軟體和服務領域將佔據41.7%的市場。由於組學資料的快速成長、對複雜建模平台日益成長的需求，以及藥物發現和精準醫療領域對人工智慧洞察的依賴性不斷增強，對這些解決方案的需求正在激增。隨著基於組學的研究不斷興起，先進分析和建模工具的應用也在加速，從而能夠更快、更精確地進行生物學解讀，這對於藥物研發、臨床試驗和個人化治療方案的開發至關重要。

2024年，臨床前藥物研發領域的市場規模預計將達到11億美元。該領域正持續利用計算生物學技術模擬候選藥物在人體試驗前的藥物動力學、藥效學和毒性特性。這些工具能夠預測藥物在生物系統中的行為，從而最大限度地減少臨床前研究中動物模型的使用，並提高藥物成功進入臨床試驗的可能性。

預計到2024年，美國計算生物學市場規模將達32億美元。美國大力推動藥物研發，並積極採用尖端運算方法，這項措施持續推動市場擴張。憑藉其強大的生物技術生態系統、先進的研究能力以及政府、學術界和私營部門之間的緊密合作，美國仍保持著市場主導地位。各大科技和製藥公司正大力投資人工智慧驅動的藥物發現、基因組學和精準醫療領域。

全球計算生物學市場的主要企業包括BIO-RAD、Schrodinger、Thermo Fisher Scientific、DNAnexus、Illumina、Dassault SYSTEMES、Compugen、QIAGEN、GINKGO、Instem、FIos GENOMICS、Strand、Aganitha、BenevolentAI、Deep Genomics、Certarai、CGakm、Sjash、Deep Genomics、DeeparaC）。為了鞏固市場地位，計算生物學領域的企業正專注於產品創新、人工智慧整合和策略合作。許多企業加大研發投入，以提高模擬精度、擴展組學資料分析能力並增強生物資訊平台的互通性。生物技術公司、學術機構和軟體開發商之間的合作正在推動開發適用於藥物發現和個人化醫療的強大計算模型。此外，各公司也積極尋求併購，以拓展其技術組合和地理覆蓋範圍。

目錄

第1章：方法論與範圍

第2章：執行概要

第3章：行業洞察

• 產業生態系分析
• 產業影響因素
  • 成長促進因素
    • 生物資訊學和資料科學的持續進步
    • 利用電腦設計增加臨床試驗活動
    • 藥物研發成本上升與時間壓力
    • 有利的政府政策
    • 組學資料和生物資訊學研究的日益成長
  • 產業陷阱與挑戰
    • 資料的瓦解與管理不善
    • 資料隱私和安全合規性
    • 缺乏熟練的專業人員
  • 機會
    • 符合監管要求的AI驗證解決方案
    • 即時穿戴式資料整合平台
• 成長潛力分析
• 監管環境
  • 北美洲
  • 歐洲
• 技術與創新格局
  • 當前技術趨勢
  • 新興技術
• 投資環境
• 顛覆性技術影響評估
• 部署模式展望
• 勞動力發展要求
• 風險評估與緩解策略
• 波特的分析
• PESTEL 分析
• 差距分析
• 未來市場趨勢

第4章：競爭格局

• 介紹
• 公司矩陣分析
• 公司市佔率分析
  • 全球的
  • 北美洲
  • 歐洲
• 主要市場參與者的競爭分析
• 競爭定位矩陣
• 戰略儀錶板
• 關鍵進展
  • 併購
  • 合作夥伴關係與合作
  • 新產品發布
  • 擴張計劃

第5章：市場估算與預測：依工具分類，2021-2034年

• 主要趨勢
• 分析軟體和服務
• 資料庫
• 硬體

第6章：市場估算與預測：依應用領域分類，2021-2034年

• 主要趨勢
• 細胞與生物模擬
  • 計算基因組學
  • 計算蛋白質體學
  • 藥物基因組學
  • 其他模擬
• 藥物發現與疾病建模
  • 目標識別
  • 目標驗證
  • 線索發現
  • 潛在客戶最佳化
• 臨床前藥物開發
  • 藥物動力學
  • 藥效學
• 臨床試驗
  • 第一階段
  • 第二階段
  • 第三階段
  • 第四階段
• 人體模擬軟體

第7章：市場估計與預測：依服務業分類，2021-2034年

• 主要趨勢
• 合約
• 內部

第8章：市場估算與預測：依最終用途分類，2021-2034年

• 主要趨勢
• 商業的
• 學術與研究

第9章：市場估計與預測：依地區分類，2021-2034年

• 主要趨勢
• 北美洲
  • 美國
  • 加拿大
• 歐洲
  • 德國
  • 英國
  • 法國
  • 西班牙
  • 義大利
  • 荷蘭
• 亞太地區
  • 中國
  • 日本
  • 印度
  • 澳洲
  • 韓國
• 拉丁美洲
  • 巴西
  • 墨西哥
  • 阿根廷
• MEA
  • 南非
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國

第10章：公司簡介

• aganitha
• Atomwise
• Benevolent AI
• BIODIGITAL
• BIO-RAD
• cadence
• CERTARA
• compugen
• DASSAULT SYSTEMES
• deep genomics
• DNAnexus
• fios GENOMICS
• Genedata (Danaher)
• GINKGO
• Illumina
• instem
• QIAGEN
• Schrodinger
• strand
• Thermo Fisher SCIENTIFIC

The Global Computational Biology Market was valued at USD 7.1 Billion in 2024 and is estimated to grow at a CAGR of 12.3% to reach USD 22.7 Billion by 2034.

The growing integration of computational models in clinical research, the rising cost and complexity of drug development, and ongoing advancements in bioinformatics and artificial intelligence are fueling this growth. Increasing omics data volume, supportive government policies, and expanding applications of AI-driven analytics are accelerating the adoption of computational biology solutions. Traditional drug discovery remains time-intensive and costly, often taking over a decade, which has pushed pharmaceutical companies to embrace computational tools that streamline R&D, reduce experimental failures, and identify promising therapeutic candidates early in the process. These technologies support biological simulations, drug-target interaction modeling, and data-driven insights from omics research, significantly cutting down laboratory time and improving clinical trial outcomes. The mounting pressure on the pharmaceutical industry to develop effective therapies faster and at a lower cost continues to propel the computational biology landscape forward. Moreover, its growing influence on clinical trial design, patient stratification, and biomarker discovery is transforming the way therapies are developed and validated.

The analysis software and services segment held a 41.7% share in 2024. The demand for these solutions is surging due to the rapid expansion of omics data, the growing necessity for complex modeling platforms, and the increasing dependence on AI-enabled insights across drug discovery and precision medicine. With the continuous rise in omics-based research, the adoption of advanced analytical and modeling tools is accelerating, enabling faster and more precise biological interpretations that are vital for pharmaceutical R&D, clinical testing, and tailored treatment development.

The preclinical drug development segment was valued at USD 1.1 Billion in 2024 and is witnessing consistent utilization of computational biology to simulate pharmacokinetic, pharmacodynamic, and toxicity characteristics of drug candidates before human testing. These tools can anticipate a drug's behavior in biological systems, helping minimize the use of animal models in preclinical studies and improving the likelihood of progressing to clinical trials successfully.

United States Computational Biology Market reached USD 3.2 Billion in 2024. The country's strong focus on accelerating drug development through the adoption of cutting-edge computational methods continues to drive market expansion. The U.S. remains a dominant force due to its robust biotechnology ecosystem, advanced research capabilities, and strong collaboration between government, academia, and the private sector. Major technology and pharmaceutical players are heavily investing in AI-led drug discovery, genomics, and precision medicine.

Leading companies operating within the Global Computational Biology Market include BIO-RAD, Schrodinger, Thermo Fisher SCIENTIFIC, DNAnexus, Illumina, Dassault SYSTEMES, Compugen, QIAGEN, GINKGO, Instem, FIos GENOMICS, Strand, Aganitha, BenevolentAI, Deep Genomics, Certara, Cadence, BIODIGITAL, Atomwise, and Genedata (Danaher). To strengthen their foothold, companies in the Computational Biology Market are focusing on product innovation, AI integration, and strategic partnerships. Many are investing in R&D to enhance simulation accuracy, expand omics data analytics capabilities, and improve the interoperability of bioinformatics platforms. Collaborations between biotech firms, academic institutions, and software developers are fostering the development of robust computational models tailored for drug discovery and personalized medicine. Firms are also pursuing mergers and acquisitions to broaden their technology portfolios and geographic presence.

Table of Contents

Chapter 1 Methodology and Scope

• 1.1 Market scope and definition
• 1.2 Research design
  • 1.2.1 Research approach
  • 1.2.2 Data collection methods
• 1.3 Data mining sources
  • 1.3.1 Global
  • 1.3.2 Regional/Country
• 1.4 Base estimates and calculations
  • 1.4.1 Base year calculation
  • 1.4.2 Key trends for market estimation
• 1.5 Primary research and validation
  • 1.5.1 Primary sources
• 1.6 Forecast model
• 1.7 Research assumptions and limitations

Chapter 2 Executive Summary

• 2.1 Industry 360° synopsis
• 2.2 Key market trends
  • 2.2.1 Regional trends
  • 2.2.2 Tool trends
  • 2.2.3 Application trends
  • 2.2.4 Services trends
  • 2.2.5 End use trends
• 2.3 CXO perspectives: Strategic imperatives
  • 2.3.1 Key decision points for industry executives
  • 2.3.2 Critical success factors for market players
• 2.4 Future outlook and strategic recommendations

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Industry impact forces
  • 3.2.1 Growth drivers
    • 3.2.1.1 Ongoing advancements in bioinformatics and data science
    • 3.2.1.2 Increasing clinical trial activities using computational designs
    • 3.2.1.3 Rising drug development costs & timeline pressures
    • 3.2.1.4 Favorable government policies
    • 3.2.1.5 Rising volume of omics data & bioinformatics research
  • 3.2.2 Industry pitfalls and challenges
    • 3.2.2.1 Disintegration and mismanagement of data
    • 3.2.2.2 Data privacy & security compliance
    • 3.2.2.3 Lack of skilled professional
  • 3.2.3 Opportunities
    • 3.2.3.1 Regulatory-ready AI validation solutions
    • 3.2.3.2 Real-time wearable data integration platforms
• 3.3 Growth potential analysis
• 3.4 Regulatory landscape
  • 3.4.1 North America
  • 3.4.2 Europe
• 3.5 Technology and innovation landscape
  • 3.5.1 Current technological trends
  • 3.5.2 Emerging technologies
• 3.6 Investment landscape
• 3.7 Disruptive technology impact assessment
• 3.8 Deployment model outlook
• 3.9 Workforce development requirements
• 3.10 Risk assessment & mitigation strategies
• 3.11 Porter's analysis
• 3.12 PESTEL analysis
• 3.13 Gap analysis
• 3.14 Future market trends

Chapter 4 Competitive Landscape, 2024

• 4.1 Introduction
• 4.2 Company matrix analysis
• 4.3 Company market share analysis
  • 4.3.1 Global
  • 4.3.2 North America
  • 4.3.3 Europe
• 4.4 Competitive analysis of major market players
• 4.5 Competitive positioning matrix
• 4.6 Strategy dashboard
• 4.7 Key developments
  • 4.7.1 Mergers & acquisitions
  • 4.7.2 Partnerships & collaborations
  • 4.7.3 New product launches
  • 4.7.4 Expansion plans

Chapter 5 Market Estimates and Forecast, By Tool, 2021 - 2034 ($ Mn)

• 5.1 Key trends
• 5.2 Analysis software and services
• 5.3 Databases
• 5.4 Hardware

Chapter 6 Market Estimates and Forecast, By Application, 2021 - 2034 ($ Mn)

• 6.1 Key trends
• 6.2 Cellular & biological simulation
  • 6.2.1 Computational genomics
  • 6.2.2 Computational proteomics
  • 6.2.3 Pharmacogenomics
  • 6.2.4 Other simulations
• 6.3 Drug discovery & disease modelling
  • 6.3.1 Target identification
  • 6.3.2 Target validation
  • 6.3.3 Lead discovery
  • 6.3.4 Lead optimization
• 6.4 Preclinical drug development
  • 6.4.1 Pharmacokinetics
  • 6.4.2 Pharmacodynamics
• 6.5 Clinical trials
  • 6.5.1 Phase I
  • 6.5.2 Phase II
  • 6.5.3 Phase III
  • 6.5.4 Phase IV
• 6.6 Human body simulation software

Chapter 7 Market Estimates and Forecast, By Services, 2021 - 2034 ($ Mn)

• 7.1 Key trends
• 7.2 Contract
• 7.3 In-house

Chapter 8 Market Estimates and Forecast, By End Use, 2021 - 2034 ($ Mn)

• 8.1 Key trends
• 8.2 Commercial
• 8.3 Academics & research

Chapter 9 Market Estimates and Forecast, By Region, 2021 - 2034 ($ Mn)

• 9.1 Key trends
• 9.2 North America
  • 9.2.1 U.S.
  • 9.2.2 Canada
• 9.3 Europe
  • 9.3.1 Germany
  • 9.3.2 UK
  • 9.3.3 France
  • 9.3.4 Spain
  • 9.3.5 Italy
  • 9.3.6 Netherlands
• 9.4 Asia Pacific
  • 9.4.1 China
  • 9.4.2 Japan
  • 9.4.3 India
  • 9.4.4 Australia
  • 9.4.5 South Korea
• 9.5 Latin America
  • 9.5.1 Brazil
  • 9.5.2 Mexico
  • 9.5.3 Argentina
• 9.6 MEA
  • 9.6.1 South Africa
  • 9.6.2 Saudi Arabia
  • 9.6.3 UAE

Chapter 10 Company Profiles

• 10.1 aganitha
• 10.2 Atomwise
• 10.3 Benevolent AI
• 10.4 BIODIGITAL
• 10.5 BIO-RAD
• 10.6 cadence
• 10.7 CERTARA
• 10.8 compugen
• 10.9 DASSAULT SYSTEMES
• 10.10 deep genomics
• 10.11 DNAnexus
• 10.12 fios GENOMICS
• 10.13 Genedata (Danaher)
• 10.14 GINKGO
• 10.15 Illumina
• 10.16 instem
• 10.17 QIAGEN
• 10.18 Schrodinger
• 10.19 strand
• 10.20 Thermo Fisher SCIENTIFIC