Wide application of computational biology in genomics, epigenomics, proteomics, and meta-genomics to understand 3D protein structural analysis, protein-protein interactions, and gene sequencing and expression along with increasing RD in drug designing and disease modeling are key factors contributing to high CAGR of Computational Biology during the forecast period.
Market Size – USD 28.68 billion in 2018, Market Growth - CAGR of 21.7%, Market Trends –technological advancements, research and development of advanced computational tools
According to the current analysis of Reports and Data, the global Computational Biology market was valued at USD 2.86 billion in 2018 and is expected to reach USD 13.77 billion by the year 2026, at a CAGR of 21.7%. Science is massively benefitted from data processing, such as computational biology. Computational biology is an interdisciplinary field of biology that applies computational methods for analyzing biological data, such as genetic sequences, cell populations, and protein samples, to discover new predictions. The computational techniques used in computational biology include analytical methods, mathematical modeling, and simulation. Moreover, new technologies such as sequencing, and high-throughput experimental methods like microarray, yeast two-hybrid, and chip-chip assays are creating enormous and increasing amounts of data that can be analyzed and processed effectively and hassle-free using computational techniques.
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The drive-in technological advancements have now opened the door to a world of innovation in the field of healthcare. Computational genetics is disciplinary of computational biology where homology and internal biological mechanism are studied using genome sequencing. The Human Genome Project is a classic example where the whole human genome was sequenced successfully. Computational biology also finds application in neurology, in which it is used to map complex interlinked pathways to visualize 3D simulation models of the brain. The medical advantage of computational biology is anticipated to boost the market during the forecast period. Additionally, computational pharmacology also uses tools of computational biology to visualize and simulate advanced drug-drug interactions in the drug designing process.
Government funding, increasing research and developments, increase in demand for predictive modeling and application in various sequencing projects, such as the human genome project, are some of the factors that support the market growth during forecast years. The rising demand for predictive models is, therefore, expected to boost the growth of the global computational biology market significantly. Moreover, the increasing funding from governments as well as private organizations for RD in this field supports market growth. The widening application of computational tools in genomics, drug development programs drug designing, and other such areas is expected to reduce the lead time of drug commercialization, therefore, reduce the average cost. However, unfavorable government scenario, the high initial cost and maintenance costs of the instruments, lack of standardization and shortage of skilled workforce is likely to be a significant hindrance to market growth.
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Further key findings from the report suggest
- Computational Biology market is growing at a CAGR of 2% in Asia-Pacific due to owing to increased spending on research works in pharmacogenomics and pharmacokinetics in clinical studies for new drugs in the region.
- In-house services are expected to be the fastest growing service segment during the forecast period 2019-2026. Several funding and RD initiatives are undertaken by private institutions, and biopharmaceutical companies for the detection of a biomarker for drug development and disorder are driving the market growth.
- North America region accounted for nearly 45% of the market share in 2018 owing to increasing RD activities for drug discovery processes and development of new biological computation tools.
- Several funding and RD initiatives are undertaken by private institutions, and biopharmaceutical companies for the detection of a biomarker for drug development and disorder are driving the market growth.
- Computational Genomics segment is expected to witness lucrative growth attributing to the recent technological advancements in cloud computing and other IT technologies. For instance, the Epidemiology and Genomics Research Program (EGRP) grants endowment to research-related activities and related need for personalization in healthcare owing to genetic variations, expanding application in non-oncology diseases,
- Market players are adapting various organic and inorganic expansion strategies. For instance, Paragon Genomics Introduces CleanPlex CFTR Panel and unveils new fusion detection enables identification of known and novel gene fusions as diagnostic and prognostic markers for tumor progression. The CFTR Panel leverages Paragon Genomics' CleanPlex technology in a multiplex PCR-based targeted resequencing assay designed to simplify the evaluation of somatic and germline variants across the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene.
- Bioinformatics expanded to the development and the use of computational tools for the biological interpretation of the large amounts of data. There is a very heterogeneous scientific community that covers all aspects of today’s genetic research. In the coming years the commitment to bioinformatics and system biology will be extended even further with increased funding and explicit commitment to both of these areas.
- Recently, in November 2019, Alibaba funded Hong Kong biotech firms to boost investments. The fund has invested in Hong Kong-based Prenetics, which provides genetics testing solutions for cancer screening and pharmacogenomics
- The global Computational Biology market consists of major players like include Chemical Computing Group, Compugen, Simulation Plus, Genedata, Certara, Insilico Biotechnology, Accelrys, Rhenovia Pharma, Entelos, Nimbus Discovery, and Rhenovia Pharma
For the purpose of this report, Reports and Data has segmented the Computational Biology market on the basis of application, service, end use, and region:
Service Type (Revenue, USD Million; 2016–2026)
Application Type (Revenue, USD Million; 2016–2026)
- Cellular Biology Simulation
o Computational Genomics
- Infrastructure / Hardware
- Software Services
o Computational Proteomics
- Drug discovery and disease modeling
o Target identification
o Target Validation
o Lead Discovery
o Lead Optimization
- Pre-clinical drug development
- Clinical trials
o Phase I
o Phase II
o Phase III
- Human Body Simulation Software
End Use (Revenue, USD Million; 2016–2026)
Regional Outlook (Revenue in USD Million; 2016–2026)
- North America
o Rest of the Europe
- Asia Pacific
o Rest of Asia-Pacific
- Middle East Africa
- Latin America
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Reasons to Purchase this report:
- To gain insightful information on the Computational Biology market for the period 2020-2027 to help readers better understand the global market and its commercial landscape.
- To investigate production processes, major issues and challenges, and solutions to capitalize on the growth opportunities.
- To study drivers and restraints that are influencing the growth of the Computational Biology market.
- An examination of strategic initiatives taken by leading companies.
- To give market estimation and prospects for the Computational Biology market.
- Market estimations for 2020-2027 include the growth trends with the latest market information and SWOT analysis.
- To provide information available on the past and present market scenarios of the Computational Biology industry and draw accurate forecasts.
- A detailed Computational Biology market demand supply dynamics.
- Identify the current opportunities in the Computational Biology Market by relying on the upcoming projects and market size overview.
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Table of contents
Table of Content
Chapter 1. Market Synopsis
1.1. Market Definition
1.2. Research Scope Premise
1.4. Market Estimation Technique
Chapter 2. Executive Summary
2.1. Summary Snapshot, 2018 – 2026
Chapter 3. Indicative Metrics
3.1. Increasing number of clinical studies trials
3.2. Rising demand for predictive models
Chapter 4. Computational Biology Segmentation Impact Analysis
4.1. Computational Biology Segmentation Analysis
4.2. Computational Biology Market Value Chain Analysis, 2016-2026
4.3. Regulatory framework
4.4. Computational Biology Market Impact Analysis
4.4.1. Market driver analysis
184.108.40.206. Rising demand for customized medicine
220.127.116.11. Increased cost of drug discovery process
4.4.2. Market restraint analysis
18.104.22.168. Lack of skilled professionals to operate computational biology
22.214.171.124. Requirement of different algorithms for different sequences
4.5. Key opportunities prioritized
4.6. Computational Biology Pricing Analysis
4.7. Industry analysis - Porter's
4.8. Computational Biology PESTEL Analysis
Chapter 5. Computational Biology Market By Application Type Insights Trends