Market Size – USD 3.58 Billion in 2019, Market Growth – CAGR of 22.4%, Market trends –Advancement in technology, and increased investment in R&D.

The global Computational Biology Market is forecasted to be worth USD 16.58 Billion by 2027, according to a current analysis by Emergen Research. Computational biology is used to analyze biological data such as cell populations, genetic sequences, and protein samples and also discover new predictions. The advent of innovative technologies such as sequencing, and high-throughput experimental methods like yeast two-hybrid, microarray, and chip-chip assays are generating a demand for mathematical modeling, analytical methods, and simulations for effective and hassle-free analysis of the data.

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Key Highlights From The Report

• In July 2020, the U.S. Department of Energy announced a funding of USD 5 million in computational biology for six new research projects. The purpose of the funding is to develop new analytical tools and software for managing an increase in the quantity of genomics and other data resulting from the study of microbes and other biological systems.
• The In-House service-type segment is anticipated to grow with the fastest CAGR of 22.8% during the forecast period. Several Biopharma companies are undertaking clinical trials in their own buildings to avoid extra cost and also to prevent the risk of leakage of their pipeline projects. Moreover, as technology is becoming affordable, more companies are opting for in-house service.
• The commercial end-use segment dominated the computational biology market. Increased usage of the technology for personalized medicine and drug designing by pharmaceutical companies is propelling its demand. Several genetic disorders require specific customized treatment, which is creating a trend for personalized medicine.
• North America is a hub for R&D in computational biology. The region witnessed increased investment by private and public companies in research for the development of effective medicine and therapies. It is also home to key companies involved in the market.
• Key participants include Chemical Computing Group, Compugen, Simulation Plus, Genedata, Certara, Insilico Biotechnology, Accelrys, Rhenovia Pharma, Entelos, Nimbus Discovery, among others.

For the purpose of this report, Emergen Research has segmented into the global Computational Biology Market on the basis of service-type, application, end-use, and region:

• Service-Type Outlook (Revenue, USD Billion; 2017-2027)
  • In-House
  • Contract
• Application Outlook (Revenue, USD Billion; 2017-2027)
  • Cellular & Biology Simulation
    1. Computational Genomics
       • Database
       • Infrastructure / Hardware
       • Software & Services
    2. Computational Proteomics
    3. Pharmacogenomics
    4. Others
  • Drug discovery and disease modeling
    1. Target identification
    2. Target Validation
    3. Lead Discovery
    4. Lead Optimization
  • Pre-clinical drug development
    1. Pharmacokinetics
    2. Pharmacodynamics
  • Clinical trials
    1. Phase I
    2. Phase II
    3. Phase III
  • Human Body Simulation Software
• End-Use Outlook (Revenue, USD Billion; 2017-2027)
  • Academics
  • Industry
  • Commercial

North America (U.S., Canada)

Europe (U.K., Italy, Germany, France, Rest of EU)

Asia Pacific (India, Japan, China, South Korea, Australia, Rest of APAC)

Latin America (Chile, Brazil, Argentina, Rest of Latin America)

Middle East & Africa (Saudi Arabia, U.A.E., South Africa, Rest of MEA)

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Key Factors influencing market remuneration:

• The global Computational Biology market report includes a detailed study of the product spectrum of the market and further describes the different product types, including One-sided, Two-sided, and Others.
• The report zeroes in on the overall market dynamics and presents information with regard to the producers and distributors, manufacturing cost structure, and downstream buyers.
• Details pertaining to the expected growth rate, industry share, revenue accumulated, and product segmentationare depicted in this report.
• The application landscape of the global Computational Biology market can be categorized into For Human, For Animals, and Others.
• The study further examines the industry share and product demand of each application, coupled withthe predicted growth patterns of the various application segments.
• Other vital factors, such as market concentration ratioand raw material processing rate, have also been covered under the latest study.

Table of Content

Chapter 1. Methodology & Sources
    1.1. Market Definition
    1.2. Research Scope
    1.3. Methodology
    1.4. Research Sources
          1.4.1. Primary
          1.4.2. Secondary
          1.4.3. Paid Sources
    1.5. Market Estimation Technique
Chapter 2. Executive Summary
    2.1. Summary Snapshot, 2019-2027
Chapter 3. Key Insights
Chapter 4. Computational Biology Market Segmentation & Impact Analysis
    4.1. Computational Biology Market Material Segmentation Analysis
    4.2. Industrial Outlook
          4.2.1. Market indicators analysis
          4.2.2. Market drivers analysis
                    4.2.2.1. Rising demand for customized medicine
                    4.2.2.2. Increased cost of drug discovery process
          4.2.3. Market restraints analysis
                    4.2.3.1. Lack of skilled professionals to operate computational biology
                    4.2.3.2. Requirement of different algorithms for different sequences
    4.3. Technological Insights
    4.4. Regulatory Framework
    4.5. Porter’s Five Forces Analysis
    4.6. Competitive Metric Space Analysis
    4.7. Price trend Analysis
    4.8. Covid-19 Impact Analysis

Chapter 5. Computational Biology Market By Service Type Insights & Trends Revenue (USD Million)
    5.1. Service Type Dynamics & Market Share, 2019 & 2027
          5.1.1. In-House
          5.1.2. Contract

Chapter 6. Computational Biology Market By Application Insights & Trends Revenue (USD Million)
    6.1. Application Dynamics & Market Share, 2019 & 2027
          6.1.1. Cellular & Biology Simulation
                    6.1.1.1. Computational Genomics
                                 6.1.1.1.1. Database
                                 6.1.1.1.2. Infrastructure / Hardware
                                 6.1.1.1.3. Software & Services
                    6.1.1.2. Computational Proteomics
                    6.1.1.3. Pharmacogenomics
                    6.1.1.4. Others
          6.1.2. Drug discovery and disease modeling
                    6.1.2.1. Target identification
                    6.1.2.2. Target Validation
                    6.1.2.3. Lead Discovery
                    6.1.2.4. Lead Optimization
          6.1.3. Pre-clinical drug development
                    6.1.3.1. Pharmacokinetics
                    6.1.3.2. Pharmacodynamics
          6.1.4. Clinical trials
                    6.1.4.1. Phase I
                    6.1.4.2. Phase II
                    6.1.4.3. Phase III
          6.1.5. Human Body Simulation Software

CONTINUED…!!

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