市场调查报告书
商品编码
1466509
计算生物学市场:按服务、应用和最终用途分类 - 全球预测 2024-2030Computational Biology Market by Services (Contract, In-house), Application (Cellular Biological Simulation, Clinical Trials, Drug Discovery & Disease Modelling), End-Use - Global Forecast 2024-2030 |
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计算生物学市场规模预估2023年为62.5亿美元,2024年达74.2亿美元,预计2030年将达210.1亿美元,复合年增长率为18.91%。
计算生物学是一个跨学科领域,它应用电脑科学、应用数学、统计学和生物资讯学的技术来解决生物学中的复杂问题、理解生物资料和模拟生物系统。它涵盖了理论方法、资料分析、计算模拟技术和数学建模在生物学、行为和社会系统研究中的发展和应用。该技术的主要目的是深入了解生物系统的原理和动力学,并预测它们的行为和相互作用。计算生物学与生物资讯学领域密切相关,但倾向于关注理论方法和计算模型的发展。计算生物学市场是由药物发现和个人化医疗需求不断增长、生物资讯学领域的进步以及复杂生物资料量不断增加所推动的。用于基因组学和蛋白质组学研究和开发的政府和私人资金也支持市场扩张。儘管存在成长潜力,但对专门计算基础设施的需求、与计算工具相关的高成本以及缺乏分析生物资料的熟练专业人员正在阻碍计算生物学的发展。此外,资料安全和隐私问题以及医疗保健相关资料监管合规的复杂性也为市场普及带来了障碍。然而,人工智慧和机器学习演算法的整合透过增强预测建模和资料分析能力,进一步为市场成长提供了利润丰厚的机会。此外,人们对生物标誌物发现及其在精准医学中的作用的日益关注为市场扩张带来了新的机会。
主要市场统计 | |
---|---|
基准年[2023] | 62.5亿美元 |
预测年份 [2024] | 74.2亿美元 |
预测年份 [2030] | 210.1亿美元 |
复合年增长率(%) | 18.91% |
内部计算生物学处理敏感服务资料和独特研究的优势
在计算生物学的动态领域,基于合约的服务作为一种灵活的解决方案脱颖而出,适合寻求专业知识且无需全职工作的组织。这些服务由外部提供者和个人顾问提供,根据特定的计划需求和时间表量身定制,因此您可以临时或逐个计划地依赖先进的分析技能、尖端演算法开发和自订生物资讯软体解决方案。有需要的公司来说,这是宝贵的资源。相较之下,内部计算生物学服务被整合到组织的永久营运结构中。这种方法可以对计算生物学专业知识进行一致的长期投资,并促进对公司特定研究领域和方法的深入了解。内部团队熟悉组织的资料、目标和流程,从而使产出与业务的策略目标紧密结合。我们提供稳定且不断发展的资源,可以适应您公司不断变化的需求。
应用计算生物学在简化药物开发平臺方面的重要应用
细胞生物学模拟使用计算模型来模拟生物细胞的行为和交互作用。这些模拟有助于理解和预测细胞功能、生物行为以及对各种刺激的反应,对于基础研究和应用生物医学应用至关重要。该技术特别适合研究复杂的生化途径以及在体外或体内进行成本高昂或技术上困难的电脑实验。临床试验是为确定新药、医疗设备或治疗通讯协定在人体中的有效性而进行的实验研究。计算生物学在临床试验设计和分析中发挥着至关重要的作用,提高了试验设计、患者分层和资料分析的效率。药物发现和疾病建模是计算生物学的重要应用,化合物的电脑辅助设计 (CAD) 和疾病途径建模加速了新疗法的发现。这些技术中的每一种都能够探索广泛的化学空间和复杂疾病的建模,识别新药的潜在目标和分子。人体模拟软体包含多种计算工具,旨在模拟人体的解剖和生理方面。这些模拟可用于多种应用,包括医疗设备设计、手术规划和教育目的。临床前药物开发是药物开发过程中临床试验领先的研究阶段。使用In Silico模型和模拟工具来预测候选药物的药物动力学、动态和毒性。
扩大商业公司对计算生物学的采用,解决最终用途应用研究的挑战
在学术领域,计算生物学工具主要用于研究和教育目的。重点是最尖端科技的可及性、学生和研究人员的易用性以及成本效益。学术机构通常需要广泛的资料库和计算能力来进行从进化生物学到系统生物学等多种研究。製药和生物技术公司等商业组织正在优先考虑将计算生物学应用于药物发现和开发、个人化医疗和农业基因组学。这些领域需要强大、扩充性的解决方案,重点是资料安全和智慧财产权保护。
区域洞察
美洲,尤其是北美的计算生物学市场正在呈现强劲成长。知名製药公司的存在、先进的医疗基础设施和严格的研发活动正在支持该地区的市场扩张。对基因组学和蛋白质组学的大规模投资进一步推动了对计算生物学解决方案的需求。美国仍然处于领先地位,这得益于政府的支持政策、产业与学术界合作的加强以及越来越多的生物资讯学课程,这些课程为该领域的熟练专业人员提供了支持。在私人和公共资金增加的推动下,特别是在欧洲,EMEA(欧洲、中东和非洲)地区的计算生物学市场正在大幅成长。有效的药物开发法律规范和卓越的科学传统正在推动该地区的市场进步。德国、英国和法国是主要贡献者,重点关註生物技术和计算科学。中东正稳步迎头赶上,这主要得益于政府对生技领域的战略投资,而非洲正处于发展的早期阶段。亚太地区正在成为计算生物学市场的动态成长中心。经济的快速发展、医疗保健支出的增加以及生物技术产业的蓬勃发展是市场格局的特征。由于政府的支持、对生命科学教育和研究的重视以及对个人化医疗日益增长的兴趣,该地区国家为市场参与者提供了有利的机会。跨国合作和外国投资的涌入进一步凸显了这个市场的特征,使亚太地区成为一个充满竞争和未来性的地区。
FPNV定位矩阵
FPNV定位矩阵对于评估计算生物学市场至关重要。我们检视与业务策略和产品满意度相关的关键指标,以对供应商进行全面评估。这种深入的分析使用户能够根据自己的要求做出明智的决策。根据评估,供应商被分为四个成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市场占有率分析
市场占有率分析是一种综合工具,可以对计算生物学市场中供应商的现状进行深入而深入的研究。全面比较和分析供应商在整体收益、基本客群和其他关键指标方面的贡献,以便更好地了解公司的绩效及其在争夺市场占有率时面临的挑战。此外,该分析还提供了对该行业竞争特征的宝贵见解,包括在研究基准年观察到的累积、分散主导地位和合併特征等因素。这种详细程度的提高使供应商能够做出更明智的决策并制定有效的策略,从而在市场上获得竞争优势。
1. 市场渗透率:提供有关主要企业所服务的市场的全面资讯。
2. 市场开拓:我们深入研究利润丰厚的新兴市场,并分析其在成熟细分市场的渗透率。
3. 市场多元化:提供有关新产品发布、开拓地区、最新发展和投资的详细资讯。
4.竞争评估与资讯:对主要企业的市场占有率、策略、产品、认证、监管状况、专利状况、製造能力等进行全面评估。
5. 产品开发与创新:提供对未来技术、研发活动和突破性产品开发的见解。
1.计算生物学市场的市场规模和预测是多少?
2.计算生物学市场预测期内需要考虑投资的产品、细分市场、应用和领域有哪些?
3.计算生物学市场的技术趋势和法规结构是什么?
4.计算生物学市场主要厂商的市场占有率是多少?
5. 进入计算生物学市场的适当型态和策略手段是什么?
[193 Pages Report] The Computational Biology Market size was estimated at USD 6.25 billion in 2023 and expected to reach USD 7.42 billion in 2024, at a CAGR 18.91% to reach USD 21.01 billion by 2030.
Computational biology is an interdisciplinary domain that applies techniques from computer science, applied mathematics, statistics, and bioinformatics to solve complex problems in biology, understand biological data, and model biological systems. It encompasses the development and application of theoretical methods and data-analytical, computational simulation techniques, and mathematical modeling to the study of biological, behavioral, and social systems. The primary aim of this technology is to generate insights into the principles and dynamics of biological systems, as well as to predict their behaviors and interactions. Computational biology is closely related to the field of bioinformatics but tends to focus more on the development of theoretical approaches and computational models. The computational biology market is driven by the increasing need for drug discovery and personalized medicine, advancements in the field of bioinformatics, and the rise in the volume of complex biological data. Government and private funding for research and development in genomics and proteomics also support the market expansion. Despite growth prospects, the need for specialized computational infrastructure, high costs associated with computational tools, and a shortage of skilled professionals to analyze biological data hinder the scope of computational biology. Moreover, concerns regarding data security and privacy and the complexity of regulatory compliances for healthcare-related data create hurdles in market proliferation. However, an integration of artificial intelligence and machine learning algorithms is further presenting lucrative opportunities for market growth by enhancing predictive modeling and data analysis capabilities. Moreover, the rising focus on biomarker discovery and its role in precision medicine opens up new opportunities for the market's expansion.
KEY MARKET STATISTICS | |
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Base Year [2023] | USD 6.25 billion |
Estimated Year [2024] | USD 7.42 billion |
Forecast Year [2030] | USD 21.01 billion |
CAGR (%) | 18.91% |
Services: Benefits of in-house computational biology capabilities to handle sensitive data or proprietary research
In the dynamic field of computational biology, contract based services stand out as a flexible solution for organizations seeking specialized expertise without the overhead of full-time employment. These services, offered by external providers or individual consultants, are tailored to meet the specific project demands and timelines, making them an invaluable resource for companies that require advanced analytical skills, state-of-the-art algorithm development, or custom bioinformatics software solutions on a temporary or per-project basis. In contrast, in-house computational biology services are integrated within an organization's permanent operational structure. This approach allows for a consistent and long-term investment in computational biology expertise, fostering a deep understanding of the company's specific research areas and methodologies. In-house teams are intimately familiar with the data, objectives, and processes of their organization, enabling them to align their output closely with the strategic goals of the business. They provide a stable and continually evolving resource capable of adapting to the company's changing needs over time.
Application: Significant applications of computational biology to streamline the drug development pipeline
Cellular biological simulation involves the use of computational models to simulate the behaviors and interactions of biological cells. These simulations help to understand and predict cellular functions, biological behaviors, and responses to various stimuli, which is critical for both basic research and applied biomedical applications. The technology is especially relevant for investigating complex biochemical pathways and in silico experimentation, which can be cost-prohibitive or technically challenging to perform in vitro or in vivo. Clinical trials are experimental research studies conducted to determine the efficacy of new drugs, medical devices, or treatment protocols on human subjects. Computational biology plays a pivotal role in the design and analysis of clinical trials, improving the efficiency of trial designs, patient stratification, and data analysis. Drug discovery & disease modeling are crucial applications of computational biology where computer-aided design (CAD) for drug compounds and modeling of disease pathways accelerate the discovery of new therapeutics. These methods enable the exploration of vast chemical spaces and the modeling of complex diseases, respectively, to identify potential targets and molecules for new drugs. Human body simulation software encompasses a broad set of computational tools designed to model anatomical and physiological aspects of the human body. These simulations are employed for a variety of applications, including medical device design, surgical planning, and educational purposes. Preclinical drug development is the phase of research that precedes clinical trials in the drug development process. It involves the use of in silico models and simulation tools to predict the pharmacokinetics, pharmacodynamics, and toxicity of candidate drugs.
End-Use: Growing adoption of computational biology in commercial entities to tackle applied research challenges
In academic settings, computational biology tools are primarily used for research and educational purposes. The emphasis is on accessibility to cutting-edge technology, ease of use for students and researchers, and cost-effectiveness. Academic institutions often require extensive databases and computational power for diverse research ranging from evolutionary biology to systems biology. Commercial entities, including pharmaceutical and biotech companies, prioritize the application of computational biology for drug discovery and development, personalized medicine, and agrigenomics. These sectors seek robust, scalable solutions with a strong emphasis on data security and intellectual property protection.
Regional Insights
The computational biology market in the Americas, particularly in North America, is exhibiting robust growth. The presence of established pharmaceutical companies, sophisticated healthcare infrastructure, and rigorous research and development activities are propelling the region's market expansion. Large-scale investments in genomics and proteomics are further spurring demand for computational biology solutions. The United States remains at the forefront, backed by supportive government policies, substantial academic-industry collaborations, and an increase in bioinformatics-related courses that supply skilled professionals to the field. The EMEA region has been experiencing a significant surge in the computational biology market owing to increased funding by private and public entities, particularly in Europe. Efficient regulatory frameworks for drug development and a tradition of excellence in scientific research are driving the market's progress in this region. Germany, the UK, and France are major contributors with their strong focus on biotechnology and computational sciences. The Middle East is steadily catching up, largely due to strategic government investments in the biotech sector, while Africa is in the early stages of development. Asia-Pacific is emerging as a dynamic growth hub for the computational biology market. Rapid economic development, increasing healthcare expenditure, and a burgeoning biotechnology industry characterize the market landscape. Countries in the region are providing lucrative opportunities for market players owing to governmental backing, a focus on education and research in the life sciences, and a rising emphasis on personalized medicine. Cross-border collaborations and the inflow of foreign investments are further defining this market, positioning APAC as a competitive and high-potential region.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Computational Biology Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Computational Biology Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the Computational Biology Market, highlighting leading vendors and their innovative profiles. These include Agilent Technologies, Inc., BGI Group, Biomax Informatics AG, Chemical Computing Group Inc., Compugen Ltd., Dassault Systemes SE, DNAnexus, Inc., DNASTAR, Inc., Eurofins Scientific SE, Genedata AG, Illumina, Inc., Insilico Medicine, Instem Group, Nimbus Discovery Llc, Ocean Genomics, PerkinElmer, Inc., Pluto Bioinformatics, ProFound Therapeutics, QIAGEN N.V., Rosa & Co. Llc, Schrodinger, Inc., Simulation Plus Inc., SOPHiA GENETICS, Thermo Fisher Scientific Inc., Waters Corporation, and WuXi NextCODE.
Market Segmentation & Coverage
1. Market Penetration: It presents comprehensive information on the market provided by key players.
2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
1. What is the market size and forecast of the Computational Biology Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Computational Biology Market?
3. What are the technology trends and regulatory frameworks in the Computational Biology Market?
4. What is the market share of the leading vendors in the Computational Biology Market?
5. Which modes and strategic moves are suitable for entering the Computational Biology Market?