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High-performance Computing for Life Sciences Market

High-performance Computing for Life Sciences Market Size, Share & Trends Analysis Report, By Component Type (Hardware, Software, and Services), By Application (Drug Discovery and Development, Genomic Analysis, Proteomics, Bioinformatics, and Others), End User (Pharmaceutical and Biotechnology Companies, Academic and Research Institutions, Contract Research Organizations (CROs), Hospitals and Clinics, and Others), By Region, Forecasts, 2024-2031

Report ID : 2497 | Published : 2024-05-27 | Pages: 180 | Format: PDF/EXCEL

High-performance Computing for Life Sciences Market Size is predicted to expand at a 11.6% CAGR during the forecast period for 2024-2031.

High-performance Computing for Life Sciences Market info

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.

Competitive Landscape

Some of the Major Key Players in the High-performance Computing for Life Sciences Market are:

  • HP Enterprise
  • AWS Inc.
  • Advanced Clustering Technologies
  • Rescale
  • IBM Corp.
  • Alibaba Cloud
  • Dell, NVIDIA Corp.
  • BIO-HPC
  • Microsoft Azure
  • NVIDIA Corp.

Market Segmentation:

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.

Academic and Research Institutions Segment is Accounted as a Major Contributor in the Market

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.

Genomic Segment Witnessed Growth at a Rapid Rate

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.

In the region, the North American High-performance Computing for Life Sciences market holds a Significant Revenue Share

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.

Recent Developments:

  • In February 2024, Quantum Corporation finalized its acquisition of XENON Systems, a prominent provider of high-performance computing and data storage solutions. The acquisition was primarily driven by Quantum's interest in integrating XENON Systems' expertise into its Quantum Myriad software platform. This strategic move aims to offer comprehensive end-to-end data management solutions tailored for artificial intelligence models and multi-variant simulations across diverse industries, including life sciences.
  • In November 2023, Quantum software innovator Classiq announced a groundbreaking industry initiative known as the Quantum Computing for Life Sciences & Healthcare Center. Developed in partnership with NVIDIA and the Tel Aviv Sourasky Medical Center, this initiative is dedicated to advancing the development and application of quantum algorithms and technologies within the realms of life sciences and healthcare. The center aims to leverage quantum computing's transformative potential to address critical challenges in these fields.

High-performance Computing for Life Sciences Market Report Scope

Report Attribute

Specifications

Growth Rate CAGR

CAGR of 11.6% from 2024 to 2031

Quantitative Units

Representation of revenue in US$ Bn and CAGR from 2024 to 2031

Historic Year

2019 to 2023

Forecast Year

2024-2031

Report Coverage

The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends

Segments Covered

By Component Type, By Application, By End-user and By Region

Regional Scope

North America; Europe; Asia Pacific; Latin America; Middle East & Africa

Country Scope

U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; Southeast Asia; South Korea

Competitive Landscape

HP Enterprise, AWS Inc., Advanced Clustering Technologies, Rescale, IBM Corp., Alibaba Cloud, Dell, NVIDIA Corp., BIO-HPC, and Microsoft Azure, among others

Customization Scope

Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape.

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

Segmentation of High-performance Computing for Life Sciences Market-

High-performance Computing for Life Sciences Market- By Component Type

  • Hardware
  • Software
  • Services

High-performance Computing for Life Sciences Market Seg

High-performance Computing for Life Sciences Market- By Application

  • Drug Discovery and Development
  • Genomic Analysis
  • Proteomics
  • Bioinformatics
  • Others

High-performance Computing for Life Sciences Market- By End User

  • Pharmaceutical and Biotechnology Companies
  • Academic and Research Institution
  • Contract Research Organizations (CROs)
  • Hospitals and Clinics
  • Others

High-performance Computing for Life Sciences Market- By Region

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • Southeast Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and 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:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

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: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

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.

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AWS Inc., Advanced Clustering Technologies, Rescale, IBM Corp., Alibaba Cloud, Dell, NVIDIA Corp., BIO-HPC, and Microsoft Azure, among others

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