Computational Immunology Industry Market Size, Share, Trends, Growth to be Fuelled by 2022-2031

Kenneth Research recently added a report on Computational Immunology Industry Market in its database of market research reports which provides its readers an in-depth analysis on the latest trends, growth opportunities and growth drivers that are associated with the growth of the market. The report additionally shares critical insights on the COVID-19 impacts on the Computational Immunology Industry Market along with the compound growth rate (CAGR) of the market for a projected period between 2022 and 2031. The report also includes analysis of the market by utilizing different analytical tools, such as PESTEL analysis and Porter’s five forces analysis. These tools also provide an in-depth analysis on the micro and macro-environmental factors that are associated with the growth of the market during the forecast period.

The U.S. Market recovers fast; In a release on May 4th, 2021, the U.S. Bureau and Economic Analysis and U.S. Census Bureau mention the recovery in the U.S. International trade in March 2021. Exports in the country reached $200 billion, up by $12.4 billion in Feb 2021. Following the continuous incremental trend, imports tallied at $274.5 billion, picked up by $16.4 billion in Feb 2021. However, as COVID19 still haunts the economies across the globe, year-over-year (y-o-y) average exports in the U.S. declined by $7.0 billion from March 2020 till March 2021 whilst imports increased by $20.7 billion during the same time. This definitely shows how the market is trying to recover back and this will have a direct impact on the Healthcare/ICT/Chemical industries, creating a huge demand for Computational Immunology Industry Market  products.

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” In 2021, the global computational biology/immunology market is likely to be worth USD 3.8 billion and is expected to grow at a compound annual growth rate of 20% during the forecast period 2022-2030. Computational biology is an interdisciplinary applied science that uses basic biological concepts to study biological systems through the use of mathematics, theories, and computer simulation models. Drivers of market growth include increased research and development of drug discovery, demand for predictive models, use in population-based sequencing projects (such as the Human Genome Project), and government funding. Visualize the simulation to examine the complexity of the biological model in the virtual space. Computational genetics is a subfield of computational biology in which genome sequencing is performed to understand homology and internal biological mechanisms.

The Human Genome Project is one of the main examples of successful sequencing of the entire human genome. In neurology, computational biology is used to map complex interconnecting pathways to visualize and decipher 3D simulation models of the brain. Computational pharmacology uses computer-aided visualization tools to simulate advanced drug interactions in the drug design process. Increasing research and development of drug discovery, demand for predictive models, use in population-based sequencing projects such as the Human Genome Project, and government funding are key drivers. Factors driving market growth.

For example, in March 2019, Ambrx Inc., a clinical-stage biopharmaceutical company focused on the field of protein therapy, and BeiGene, a commercial-stage pharmaceutical company engaged in the development of immuno-oncology drugs, reached a research and development cooperation. drug. Ambrx has a proprietary extended genetic code platform designed to integrate unnatural amino acids into E. coli cells and Chinese Hamster Ovary (CHO) protein sequences.

Through this cooperation, the two will use Ambrs drug discovery platform and the latters knowledge and experience as well as a series of resources to develop clinically advanced biological agents. In January 2018, the German Center of Excellence for Translational Biodiversity Genomics received a US$20 million grant for more than seven years to sequence thousands of organisms with high quality. Similarly, in October 2016, 23andMe received $1.7 million in funding from the National Human Genome Institute of the National Institutes of Health (NIH) within a year to create a sequencing panel for the African American genome. In addition, in 2016, Science Canada announced an investment of US$4 million for 16 new computational biology projects. However, market growth is limited by the lack of well-trained professionals.


According to applications, the computational biology market is divided into cell and biological simulation, drug discovery and disease modeling, preclinical drug development, clinical trials, and human simulation software. Cell and biological simulation are further subdivided into genomics and computational proteomics, pharmacogenomics, etc. Drug discovery and disease modeling are further subdivided into target identification, target verification, lead discovery and optimization. Preclinical development is further subdivided into pharmacokinetics and pharmacodynamics.

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The clinical trials are further divided into phases I, II, and III. It is expected that by 2030, cell and biological simulation will continue to lead, with a market share of over 33%. Computational cell modeling and biological simulation help to decipher the biological and physiological functions of cells. Increasing unmet medical needs and growing demand for personalized medicine are expected to affect the future growth of this segment. For example, HPE high-performance computing capabilities are used for personalized medicine to improve healthcare services and patient diagnosis. To this end, Dassault Systemes organized the "Living Heart Project and created a simulated 3D model of the human heart. Due to investments in new drug development and growth, drug discovery and disease modeling are expected to be the fastest growing part of the forecast period.

In the case of a clinical trial failure. Today, the drug discovery and disease modeling market is in a healthy development stage to improve diagnosis and prognosis. In addition, due to the growing global demand for drugs, preclinical drug development is expected to record the second highest compound annual growth rate during the forecast period. High-quality sequencing of thousands of organisms. Similarly, in October 2016, 23andMe received $1.7 million in funding from the National Human Genome Institute of the National Institutes of Health (NIH) for a one-year period for African Americans to create genome sequencing panels. In addition, in 2016, Science Canada announced an investment of US$4 million for 16 new computational biology projects. However, due to the lack of well-trained professionals, the growth of the market is limited.

Information about services: 

According to services, the market is divided into internal services and contract services. In 2020, contract services have the largest market share and are expected to continue to lead during the forecast period. It is estimated that by 2030, the market share of this segment will exceed 45%, because the cost of contract services is lower than that of internal services. The Computational Biology Contract Research Organization (CRO) accelerates biomedical research around the world. These CROs have increased computing power and eliminated a lot of waste from contract research companies. With the latest developments in cloud computing and other IT technologies, contract services are expected to flourish during the research period.

End-use information: 

According to the end-use, the market is divided into commercial, academic, and industrial. Business led the end-use market segment in 2020 due to increased use of bioinformatics research, drug design, and personalized medicine. For example, in August 2018, the European Union and the Indian Department of Biotechnology (DBT) announced a research and innovation fund of $17.2 million for the development of the next generation of influenza viruses to protect people from world-level influences. These initiatives bring business and government academia together on the same platform, with the same purpose.

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