计算生物学市场机会、成长驱动因素、产业趋势分析及预测（2025-2034年）

2024 年全球计算生物学市场价值为 71 亿美元，预计到 2034 年将以 12.3% 的复合年增长率增长至 227 亿美元。

计算模型在临床研究中的日益普及、药物研发成本和复杂性的不断攀升，以及生物资讯学和人工智慧的持续进步，共同推动了这一领域的成长。组学资料量的激增、政府政策的支持以及人工智慧驱动分析应用的不断扩展，都在加速计算生物学解决方案的普及。传统的药物发现仍然耗时且耗力，往往需要十年以上的时间，这促使製药公司采用计算工具来简化研发流程、减少实验失败，并在早期阶段识别有前景的候选药物。这些技术支援生物模拟、药物-标靶交互作用建模以及基于组学研究的数据驱动型洞察，从而显着缩短实验室时间并改善临床试验结果。製药业面临越来越大的压力，需要更快、更低成本地开发出有效的疗法，这持续推动计算生物学的发展。此外，计算生物学在临床试验设计、患者分层和生物标记发现方面日益增长的影响力，正在改变疗法的开发和验证方式。

预计到2024年，分析软体和服务领域将占据41.7%的市场。由于组学资料的快速增长、对复杂建模平台日益增长的需求，以及药物发现和精准医疗领域对人工智慧洞察的依赖性不断增强，对这些解决方案的需求正在激增。随着基于组学的研究不断兴起，先进分析和建模工具的应用也在加速，从而能够更快、更精确地进行生物学解读，这对于药物研发、临床试验和个人化治疗方案的开发至关重要。

2024年，临床前药物研发领域的市场规模预计将达到11亿美元。该领域正持续利用计算生物学技术模拟候选药物在人体试验前的药物动力学、药效学和毒性特性。这些工具能够预测药物在生物系统中的行为，从而最大限度地减少临床前研究中动物模型的使用，并提高药物成功进入临床试验的可能性。

预计到2024年，美国计算生物学市场规模将达32亿美元。美国大力推动药物研发，并积极采用尖端运算方法，这项措施持续推动市场扩张。凭藉其强大的生物技术生态系统、先进的研究能力以及政府、学术界和私营部门之间的紧密合作，美国仍保持着市场主导地位。各大科技和製药公司正大力投资人工智慧驱动的药物发现、基因组学和精准医疗领域。

全球计算生物学市场的主要企业包括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）。为了巩固市场地位，计算生物学领域的企业正专注于产品创新、人工智慧整合和策略合作。许多企业加大研发投入，以提高模拟精度、扩展组学资料分析能力并增强生物资讯平台的互通性。生物技术公司、学术机构和软体开发商之间的合作正在推动开发适用于药物发现和个人化医疗的强大计算模型。此外，各公司也积极寻求併购，以拓展其技术组合和地理覆盖范围。

目录

第一章：方法论与范围

第二章：执行概要

第三章：行业洞察

• 产业生态系分析
• 产业影响因素
  • 成长驱动因素
    • 生物资讯学和资料科学的持续进步
    • 利用电脑设计增加临床试验活动
    • 药物研发成本上升与时间压力
    • 有利的政府政策
    • 组学资料和生物资讯学研究的日益增长
  • 产业陷阱与挑战
    • 资料的瓦解与管理不善
    • 资料隐私和安全合规性
    • 缺乏熟练的专业人员
  • 机会
    • 符合监管要求的AI验证解决方案
    • 即时可穿戴资料整合平台
• 成长潜力分析
• 监管环境
  • 北美洲
  • 欧洲
• 技术与创新格局
  • 当前技术趋势
  • 新兴技术
• 投资环境
• 颠覆性技术影响评估
• 部署模式展望
• 劳动力发展要求
• 风险评估与缓解策略
• 波特的分析
• PESTEL 分析
• 差距分析
• 未来市场趋势

第四章：竞争格局

• 介绍
• 公司矩阵分析
• 公司市占率分析
  • 全球的
  • 北美洲
  • 欧洲
• 主要市场参与者的竞争分析
• 竞争定位矩阵
• 战略仪錶板
• 关键进展
  • 併购
  • 合作伙伴关係与合作
  • 新产品发布
  • 扩张计划

第五章：市场估算与预测：依工具划分，2021-2034年

• 主要趋势
• 分析软体和服务
• 资料库
• 硬体

第六章：市场估算与预测：依应用领域划分，2021-2034年

• 主要趋势
• 细胞与生物模拟
  • 计算基因组学
  • 计算蛋白质体学
  • 药物基因组学
  • 其他模拟
• 药物发现与疾病建模
  • 目标识别
  • 目标验证
  • 线索发现
  • 潜在客户优化
• 临床前药物开发
  • 药物动力学
  • 药效学
• 临床试验
  • 第一阶段
  • 第二阶段
  • 第三阶段
  • 第四阶段
• 人体模拟软体

第七章：市场估计与预测：依服务业划分，2021-2034年

• 主要趋势
• 合约
• 内部

第八章：市场估算与预测：依最终用途划分，2021-2034年

• 主要趋势
• 商业的
• 学术与研究

第九章：市场估计与预测：依地区划分，2021-2034年

• 主要趋势
• 北美洲
  • 我们
  • 加拿大
• 欧洲
  • 德国
  • 英国
  • 法国
  • 西班牙
  • 义大利
  • 荷兰
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 澳洲
  • 韩国
• 拉丁美洲
  • 巴西
  • 墨西哥
  • 阿根廷
• MEA
  • 南非
  • 沙乌地阿拉伯
  • 阿联酋

第十章：公司简介

• 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