High-performance Computing for Life Sciences Market Size is predicted to expand at a 11.6% CAGR during the forecast period for 2024-2031.
Numerous factors are driving the growth of global high-performance computing (HPC) for the life sciences market. The exponential proliferation of biological data, including genomics, proteomics, and other omics data, necessitates the utilization of high-performance computing for efficient management, analysis, and interpretation of these vast datasets. Traditional computer systems are inadequate to handle the complexity and volume of data generated by contemporary life sciences research, underscoring the indispensable role of HPC in bioinformatics and biological computation.
The drug discovery and development process is renowned for its high cost, lengthy duration, and significant likelihood of failure. HPC emerges as a crucial tool in alleviating both the time and financial burdens associated with this process. By enabling more precise simulations and modeling of molecular interactions, HPC accelerates the identification of viable drug candidates and enhances the optimization of their compositions, thereby streamlining drug development workflows.
Moreover, the rapid advancement of HPC technologies, encompassing improvements in computational capacity, storage solutions, and the availability of HPC resources via cloud platforms, has democratized access to HPC within the life sciences sector. These technological advancements have facilitated the broader adoption of HPC across various research and development initiatives within the life sciences domain, empowering entities to leverage its capabilities more effectively.
The high-performance computing for life sciences market is segmented by end users, application type, and component type. Based on end users, the market is segmented into pharmaceutical and biotechnology companies, academic and research institutions, contract research organizations (CROs), hospitals and clinics, and others. The market is segmented by application into drug discovery and development, genomic analysis, proteomics, bioinformatics, and others. The market is segmented by component type into hardware, software, and services.
The academic and research institutions segment is projected to witness the most rapid growth within the global high-performance computing for life sciences market. This growth is fueled by heightened funding allocated to academic research endeavors in areas such as genomics, proteomics, and personalized medicine. Additionally, advancements in accessibility, particularly through cloud computing and national supercomputing centers, are making high-performance computing resources more readily available to academic and research institutions. Collaborative efforts between academia and industry frequently harness high-performance computing capabilities to tackle complex computational challenges, thereby facilitating the widespread adoption of HPC solutions in the field.
The genomic analysis segment is anticipated to dominate the market. The growing emphasis on personalized medicine, initiatives to understand genetic disorders, and decreasing costs associated with genomic sequencing are propelling the demand for significant computational resources required for processing, analyzing, and storing the vast datasets generated by genomic sequencing. These factors converge to establish the genomic analysis segment as a major player in the market. With its established foundation and continuous expansion, this segment maintains a significant presence in the HPC for the life sciences market.
During the forecast period, North America is projected to lead the global high-performance computing for life sciences market. This region boasts some of the world's most prestigious research institutions, universities, and biotechnology companies. These entities possess cutting-edge laboratory and high-performance computing facilities, empowering them to spearhead groundbreaking studies in proteomics, genomics, personalized healthcare, and drug discovery.
In contrast, Asia Pacific (APAC) is anticipated to experience the swiftest growth in the global high-performance computing for life sciences market. APAC countries have witnessed a rising trend of collaboration among academic institutions, research organizations, and industry stakeholders. This collaborative approach fosters the exchange of knowledge and resources, fueling the demand for advanced computational capabilities offered by HPC systems. Moreover, the increasing focus on healthcare and biotechnology in the APAC region has prompted investments in the modernization of healthcare infrastructure.
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Report Attribute |
Specifications |
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Growth Rate CAGR |
CAGR of 11.6% from 2024 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Component Type, By Application, By End-user and By Region |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; Southeast Asia; South Korea |
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Competitive Landscape |
HP Enterprise, AWS Inc., Advanced Clustering Technologies, Rescale, IBM Corp., Alibaba Cloud, Dell, NVIDIA Corp., BIO-HPC, and Microsoft Azure, among others |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global High-performance Computing for Life Sciences Market Snapshot
Chapter 4. Global High-performance Computing for Life Sciences Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Component Type Estimates & Trend Analysis
5.1. by Component Type & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Component Type:
5.2.1. Hardware
5.2.2. Software
5.2.3. Services
Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis
6.1. by Application & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:
6.2.1. Drug Discovery and Development
6.2.2. Genomic Analysis
6.2.3. Proteomics
6.2.4. Bioinformatics
6.2.5. and Others
Chapter 7. Market Segmentation 3: by End-User Estimates & Trend Analysis
7.1. by End-User & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by End-User:
7.2.1. Pharmaceutical and Biotechnology Companies
7.2.2. Academic and Research Institutions
7.2.3. Contract Research Organizations (CROs)
7.2.4. Hospitals and Clinics
7.2.5. Others
Chapter 8. High-performance Computing for Life Sciences Market Segmentation 4: Regional Estimates & Trend Analysis
8.1. North America
8.1.1. North America High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Component Type, 2019-2031
8.1.2. North America High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.1.3. North America High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.1.4. North America High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
8.2. Europe
8.2.1. Europe High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Component Type, 2019-2031
8.2.2. Europe High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.2.3. Europe High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.2.4. Europe High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
8.3. Asia Pacific
8.3.1. Asia Pacific High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Component Type, 2019-2031
8.3.2. Asia-Pacific High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.3.3. Asia Pacific High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.3.4. Asia Pacific High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
8.4. Latin America
8.4.1. Latin America High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Component Type, 2019-2031
8.4.2. Latin America High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.4.3. Latin America High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.4.4. Latin America High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
8.5. Middle East & Africa
8.5.1. Middle East & Africa High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Component Type, 2019-2031
8.5.2. Middle East & Africa High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.5.3. Middle East & Africa High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.5.4. Middle East & Africa High-performance Computing for Life Sciences Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles
9.2.1. HP Enterprise
9.2.2. AWS Inc.
9.2.3. Advanced Clustering Technologies
9.2.4. Rescale
9.2.5. IBM Corp.
9.2.6. Alibaba Cloud
9.2.7. Dell
9.2.8. NVIDIA Corp.
9.2.9. BIO-HPC
9.2.10. Microsoft Azure
9.2.11. among others
High-performance Computing for Life Sciences Market- By Component Type
High-performance Computing for Life Sciences Market- By Application
High-performance Computing for Life Sciences Market- By End User
High-performance Computing for Life Sciences Market- By Region
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
