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Global Computational Biology Market to reach USD 27.32 billion by the end of 2030.

Global Computational Biology Market Size study & Forecast, by Application (Cellular & Biological Simulation, Drug Discovery & Disease Modelling, Preclinical Drug Development, Clinical Trials, Human Body Simulation Software), by Services (Contract, In-house), by End Use (Academics & Research, Commercial) and Regional Analysis, 2023-2030

Product Code: HLSHIT-78356549
Publish Date: 4-08-2023
Page: 200

Global Computational Biology Market is valued at approximately USD 6.57 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 19.50% over the forecast period 2023-2030. Computational Biology is an interdisciplinary field that combines computational science and biological research to gain a deeper understanding of biological systems and solve biological problems using computational techniques and tools. It involves the application of mathematical modeling, statistical analysis, and computer algorithms to analyze and interpret biological data, simulate biological processes, and make predictions about biological systems. The Computational Biology market is expanding because of factors such as increasing bioinformatics research and an increasing number of clinical studies in pharmacogenomics and pharmacokinetics.

Bioinformatics and computational biology have undergone a lot of developments during the past 15 years, firmly establishing themselves as crucial components of modern biology. For instance, according to Department of Biotechnology (DBT) publications from February 2022, the demand for bioinformatics tools and knowledge has increased as a result of the expansion of sequence databases as a result of genome sequencing operations. According to the Alliance for Regenerative Medicine, Companies involved are working on cell and gene therapies raised around USD 23.1 billion in funding globally in 2021, an increase of about 16% from the USD 19.9 billion total year 2020.These, rising investments have led to a rise in the demand and adoption of bioinformatics biology, resulting in market growth. In addition, the growth of drug designing and disease modelling and growing R&D for drug discovery is creating a lucrative opportunity for the market. However, the high cost of computational biology stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Computational Biology Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the dominance of key market players, rising investment in drug discovery and research and development activities. Asia Pacific is expected to grow at a fastest rate during the forecast period, owing to factors such as an increase in the number of collaborations for product development, geographic expansion of key players, and active participation of government and nonprofit organizations in the market space.

Major market player included in this report are:
Nimbus Discovery LLC
Insilico Biotechnology AG
Compugen Ltd.
Simulation Plus Inc
Chemical Computing Group
Rhenovia Pharma SAS
Dassault Systèmes SE
Genedata AG
Rosa & Co. LLC
Strand Life Sciences

Recent Developments in the Market:
Ø In May 2021 update, the World Health Organization (WHO) and the Swiss Confederation signed a Memorandum of Understanding (MoU) to start the first WHO BioHub Facility as a part of the WHO BioHub System. The facility, located in Spiez, Switzerland, acts as a hub for the secure receipt, sequencing, storage, and preparation of biological samples for transfer to other laboratories, and it also supports worldwide pathogen preparedness and informs risk assessments.
Ø In April 2021, Peptilogics, announced the completion of its Phase I clinical trial for its lead compound PLG0206, a potent, broad-spectrum anti-infective that has been given the United States Food and Drug Administration Orphan Drug Designation and Qualified Infectious Disease Product Designation for its initial focus on the treatment of prosthetic joint infections (PJI).
Global Computational Biology Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Application, Services, End Use, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Application:
Cellular & Biological Simulation
Drug Discovery & Disease Modelling
Preclinical Drug Development
Clinical Trials
Human Body Simulation Software

By Services:

By End Use:
Academics & Research

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Computational Biology Market, by Region, 2020-2030 (USD Billion)
1.2.2. Computational Biology Market, by Application, 2020-2030 (USD Billion)
1.2.3. Computational Biology Market, by Services, 2020-2030 (USD Billion)
1.2.4. Computational Biology Market, by End Use, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Computational Biology Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Computational Biology Market Dynamics
3.1. Computational Biology Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing bioinformatics research Increasing number of clinical studies in pharmacogenomics and pharmacokinetics
3.1.2. Market Challenges High Cost of Computational Biology
3.1.3. Market Opportunities Growth of drug designing and disease modelling Growing R&D for drug discovery
Chapter 4. Global Computational Biology Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Computational Biology Market, by Application
5.1. Market Snapshot
5.2. Global Computational Biology Market by Application, Performance – Potential Analysis
5.3. Global Computational Biology Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
5.4. Computational Biology Market, Sub Segment Analysis
5.4.1. Cellular & Biological Simulation
5.4.2. Drug Discovery & Disease Modelling
5.4.3. Preclinical Drug Development
5.4.4. Clinical Trials
5.4.5. Human Body Simulation Software
Chapter 6. Global Computational Biology Market, by Services
6.1. Market Snapshot
6.2. Global Computational Biology Market by Services, Performance – Potential Analysis
6.3. Global Computational Biology Market Estimates & Forecasts by Services 2020-2030 (USD Billion)
6.4. Computational Biology Market, Sub Segment Analysis
6.4.1. Contract
6.4.2. In-house
Chapter 7. Global Computational Biology Market, by End Use
7.1. Market Snapshot
7.2. Global Computational Biology Market by End Use, Performance – Potential Analysis
7.3. Global Computational Biology Market Estimates & Forecasts by End Use 2020-2030 (USD Billion)
7.4. Computational Biology Market, Sub Segment Analysis
7.4.1. Academics & Research
7.4.2. Commercial
Chapter 8. Global Computational Biology Market, Regional Analysis
8.1. Top Leading Countries
8.2. Top Emerging Countries
8.3. Computational Biology Market, Regional Market Snapshot
8.4. North America Computational Biology Market
8.4.1. U.S. Computational Biology Market Application breakdown estimates & forecasts, 2020-2030 Services breakdown estimates & forecasts, 2020-2030 End Use breakdown estimates & forecasts, 2020-2030
8.4.2. Canada Computational Biology Market
8.5. Europe Computational Biology Market Snapshot
8.5.1. U.K. Computational Biology Market
8.5.2. Germany Computational Biology Market
8.5.3. France Computational Biology Market
8.5.4. Spain Computational Biology Market
8.5.5. Italy Computational Biology Market
8.5.6. Rest of Europe Computational Biology Market
8.6. Asia-Pacific Computational Biology Market Snapshot
8.6.1. China Computational Biology Market
8.6.2. India Computational Biology Market
8.6.3. Japan Computational Biology Market
8.6.4. Australia Computational Biology Market
8.6.5. South Korea Computational Biology Market
8.6.6. Rest of Asia Pacific Computational Biology Market
8.7. Latin America Computational Biology Market Snapshot
8.7.1. Brazil Computational Biology Market
8.7.2. Mexico Computational Biology Market
8.8. Middle East & Africa Computational Biology Market
8.8.1. Saudi Arabia Computational Biology Market
8.8.2. South Africa Computational Biology Market
8.8.3. Rest of Middle East & Africa Computational Biology Market

Chapter 9. Competitive Intelligence
9.1. Key Company SWOT Analysis
9.1.1. Company 1
9.1.2. Company 2
9.1.3. Company 3
9.2. Top Market Strategies
9.3. Company Profiles
9.3.1. Nimbus Discovery LLC Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
9.3.2. Insilico Biotechnology AG
9.3.3. Compugen Ltd.
9.3.4. Simulation Plus Inc
9.3.5. Chemical Computing Group
9.3.6. Rhenovia Pharma SAS
9.3.7. Dassault Systèmes SE
9.3.8. Genedata AG
9.3.9. Rosa & Co. LLC
9.3.10. Strand Life Sciences
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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