Global Computational Biology Market 2023-2030

Description

List of Tables

Title: Global Computational Biology Market Size, Share & Trends Analysis Report Market by Application (Drug discovery and development, Clinical trials, Human body simulation software, Preclinical drug development, and Others (Cellular and biological simulation)), by Service (Software platforms Infrastructure and hardware, Consulting services), End-use(Academia and research, Pharmaceutical and biotechnology companies, Clinical diagnostics companies)Forecast Period (2023-2030).

The global Computational biology market is anticipated to grow at a considerable CAGR of 15.8% during the forecast period. Computational biology is the use of data analysis, mathematical modeling, and computational simulations to understand biological systems and relationships. It's an interdisciplinary field that uses computational methods to analyze large collections of biological data, such as genetic sequences, cell populations, or protein samples. Chronic diseases, such as cancer, heart disease, and diabetes, are a major global health problem. Computational biology is being used to develop new drugs and treatments for chronic diseases, as well as to improve the diagnosis and management of these diseases. This is one of the key drivers for the market growth. Computational biology tools can be used to analyze large datasets of genomic, transcriptomic, and proteomic data to identify new genes and proteins that play a role in the development and progression of chronic diseases. Once these new drug targets have been identified, researchers can begin to develop new drugs that target these molecules. Computational biology tools can be used to design new drugs that are more effective and have fewer side effects. For example, computational biology tools can be used to simulate the interaction between a drug molecule and its target protein to identify the most effective drug structure. Computational biology tools can be used to predict the toxicity and efficacy of drugs before they are tested in clinical trials. This can help to save time and money in the drug development process. Computational biology tools can be used to develop new diagnostic tests and to develop personalized treatment plans for patients with chronic diseases. For example, computational biology tools can be used to analyze the patient's genetic profile to identify the most effective and safest treatments for that particular patient.

One example of how computational biology is being used to develop new drugs for chronic diseases is the development of targeted cancer therapies. Targeted cancer therapies are drugs that target specific molecules that are involved in the growth and survival of cancer cells. Computational biology tools are being used to identify new drug targets for cancer, to design new targeted cancer therapies, and to predict the efficacy of targeted cancer therapies in clinical trials. Another example of how computational biology is being used to improve the diagnosis and management of chronic diseases is the development of personalized medicine approaches for diabetes. Diabetes is a chronic disease that affects the body's ability to produce or use insulin, a hormone that regulates blood sugar levels. Computational biology tools are being used to analyze the genetic profile of patients with diabetes to identify the most effective and safest treatments for that particular patient.

Segmental Outlook

The global Computational biology market is segmented based on application, service, and end-use. Based on the application, the market is segmented into drug discovery and development, clinical trials, human body simulation software, preclinical drug development, and others (cellular and biological simulation) and others. Based on service, the market is sub-segmented into software platforms, infrastructure, and hardware, consulting services). Based on end-use, the market is sub-segmented into academia and research, pharmaceutical and biotechnology companies, clinical diagnostics companies, and others.

The End-use Segment showed a major market share for the Computational biology market

Pharmaceutical and biotechnology companies hold the major market share in the global computational biology market by end-use. This is because pharmaceutical and biotechnology companies are at the forefront of developing new drugs and treatments for diseases, and computational biology is playing an increasingly important role in this process. One example of how pharmaceutical and biotechnology companies are using computational biology is in the drug discovery process. Traditionally, drug discovery has been a long and expensive process, involving the screening of millions of compounds to find a few that may have potential therapeutic effects. However, computational biology tools can be used to accelerate this process by helping researchers to identify promising drug targets and to design new drugs that are more likely to be effective.

Regional Outlook

The global Computational biology market is further segmented based on geography, including North America (the US and Canada), Europe (Italy, Spain, Germany, France, and others), Asia-Pacific (India, China, Japan, South Korea, and others), and the Rest of the World (the Middle East & Africa and Latin America). Among these, North America holds the major market share for many reasons, one of which is the presence of major pharmaceutical and biotechnology companies, as well as leading academic institutions.

Europe is expected to grow at a consistent pace in the global market

The European region is experiencing a consistent growth rate in the global market. The growth of the computational biology market in Europe is being driven by increasing investments in drug discovery and development, as well as the growing adoption of personalized medicine. Europe is a major hub for pharmaceutical and biotechnology companies, and these companies are investing heavily in drug discovery and development. Computational biology is playing an increasingly important role in this process, helping researchers to identify new drug targets, design new drugs, and predict the toxicity and efficacy of drugs. Personalized medicine is a new approach to healthcare that affects treatments to the individual patient's genetic profile. Computational biology tools are essential for personalized medicine, as they can be used to analyze the patient's genetic profile to identify the most effective and safest treatments for that particular patient.

Market Players Outlook

The major companies serving the global Computational biology market include: Dassault Systemes, Illumina, Inc., QIAGEN GmbH, Schrodinger, LLC., and Thermo Fisher Scientific Inc. among others. The market players are considerably contributing to the market growth by the adoption of various strategies, including mergers and acquisitions, partnerships, collaborations, and new product launches, to stay competitive in the market. For instance, in May 2022, global professional services firm ZS acquired a Danish informatics and systems biology company named Intomics. The 42 members of Intomics will join ZS's staff of 12,000 employees worldwide and strengthen its team of molecular natives who combine scientific, data science, and technology expertise with a research mindset to advance the adoption of in-silico methods in drug discovery.

The Report Covers:

Market value data analysis of 2022 and forecast to 2030.
Annualized market revenues ($ million) for each market segment.
Country-wise analysis of major geographical regions.
Key companies operating in the global computational biology market. Based on the availability of data, information related to new product launches, and relevant news is also available in the report.
Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
Analysis of market-entry and market expansion strategies.
Competitive strategies by identifying 'who-stands-where' in the market.

Product Code: OMR2027853

1. Report Summary

Current Industry Analysis and Growth Potential Outlook
1.1. Research Methods and Tools
1.2. Market Breakdown
- 1.2.1. By Segments
- 1.2.2. By Region

2. Market Overview and Insights

2.1. Scope of the Report
2.2. Analyst Insight & Current Market Trends
- 2.2.1. Key Findings
- 2.2.2. Recommendations
- 2.2.3. Conclusion

3. Competitive Landscape

3.1. Key Company Analysis
3.2. Dassault Systemes
- 3.2.1. Overview
- 3.2.2. Financial Analysis
- 3.2.3. SWOT Analysis
- 3.2.4. Recent Developments
3.3. Illumina, Inc.
- 3.3.1. Overview
- 3.3.2. Financial Analysis
- 3.3.3. SWOT Analysis
- 3.3.4. Recent Developments
3.4. QIAGEN GmbH
- 3.4.1. Overview
- 3.4.2. Financial Analysis
- 3.4.3. SWOT Analysis
- 3.4.4. Recent Developments
3.5. Schrodinger, LLC.
- 3.5.1. Overview
- 3.5.2. Financial Analysis
- 3.5.3. SWOT Analysis
- 3.5.4. Recent Developments
3.6. Thermo Fisher Scientific Inc.
- 3.6.1. Overview
- 3.6.2. Financial Analysis
- 3.6.3. SWOT Analysis
- 3.6.4. Recent Developments
3.7. Key Strategy Analysis

4. Market Segmentation

4.1. Global Computational Biology Market by Application
- 4.1.1. Drug discovery and development
- 4.1.2. Clinical trials
- 4.1.3. Human body simulation software
- 4.1.4. Preclinical drug development
- 4.1.5. Others (Cellular and biological simulation)
4.2. Global Computational Biology Market by Service
- 4.2.1. Software platforms
- 4.2.2. Infrastructure and hardware
- 4.2.3. Consulting services
4.3. Global Computational Biology Market by End-use
- 4.3.1. Academia and research
- 4.3.2. Pharmaceutical and biotechnology companies
- 4.3.3. Clinical diagnostics companies

5. Regional Analysis

5.1. North America
- 5.1.1. United States
- 5.1.2. Canada
5.2. Europe
- 5.2.1. UK
- 5.2.2. Germany
- 5.2.3. Italy
- 5.2.4. Spain
- 5.2.5. France
- 5.2.6. Rest of Europe
5.3. Asia-Pacific
- 5.3.1. China
- 5.3.2. India
- 5.3.3. Japan
- 5.3.4. South Korea
- 5.3.5. Rest of Asia-Pacific
5.4. Rest of the World

6. Company Profiles

6.1. Agilent Technologies, Inc.
6.2. Bio-Rad Laboratories, Inc.
6.3. Certara, Inc.
6.4. Chemical Computing Group ULC ("CCG")
6.5. Compugen
6.6. DNAnexus, Inc.
6.7. DNASTAR
6.8. Genedata
6.9. InSilico Medicine
6.10. Intelisys, Inc.
6.11. Nimbus Therapeutics
6.12. Oxford Nanopore Technologies plc
6.13. PacBio.
6.14. PerkinElmer U.S. LLC.
6.15. PhenX
6.16. Simulations Plus
6.17. Yokogawa Insilico Biotechnology GmbH