Computational Biology Market - Size, Share, Outlook, and Opportunity Analysis, 2020 - 2027
The development and implementation of data-analytical and theoretical approaches, mathematical modelling, and computational simulation techniques in life sciences is the emphasis of computational biology.
Statistics:
By the end of 2027, the global computational biology market is expected to be worth US$ 12,601.1 million.
Drivers of the Global Computational Biology Market
Over the forecast period, the worldwide computational biology market is expected to rise due to the high cost of drug development. According to a study published in JAMA in March 2020, between 2009 and 2018, U.S. biopharmaceutical companies spent roughly $1 billion to bring each of their new medications to market.
Several advantages of computational biology are also projected to contribute to the market's growth. In computational biology, predictive modelling methods can provide crucial information to help speed up the drug development process. Predictive modelling aids in reducing the overall number of patients recruited and reducing the length of clinical trials.
Statistics:
In terms of value, North America dominated the global computational biology market in 2019, with a 44.2 percent share, followed by Europe and Asia Pacific, respectively.
Restraints in the Global Computational Biology Market
The expansion of the computational biology sector has been stifled by vast amounts of data and a lack of uniformity. For present single task tools, there is a growing demand for combining available technologies to create a composite application. The tools should be able to communicate with one another and successfully utilise the same data. To reduce the time and effort now spent analysing petabytes of data held by organisations and governments around the world, user-friendly databases are required.
Furthermore, data storage and organisation concerns are constraining the market's growth. Rapid data gathering creates organisational issues because the data is diverse and may pertain to demographics, illness associations, symptoms, therapeutic medications, and other topics.
For players in the worldwide computational biology market, developing computer networks for disease surveillance and mapping the pathways and biological networks linked with illness beginning are projected to provide lucrative growth prospects.
By the end of 2027, the global computational biology market is expected to be worth US$ 12,601.1 million.
Drivers of the Global Computational Biology Market
Over the forecast period, the worldwide computational biology market is expected to rise due to the high cost of drug development. According to a study published in JAMA in March 2020, between 2009 and 2018, U.S. biopharmaceutical companies spent roughly $1 billion to bring each of their new medications to market.
Several advantages of computational biology are also projected to contribute to the market's growth. In computational biology, predictive modelling methods can provide crucial information to help speed up the drug development process. Predictive modelling aids in reducing the overall number of patients recruited and reducing the length of clinical trials.
Statistics:
In terms of value, North America dominated the global computational biology market in 2019, with a 44.2 percent share, followed by Europe and Asia Pacific, respectively.
Restraints in the Global Computational Biology Market
The expansion of the computational biology sector has been stifled by vast amounts of data and a lack of uniformity. For present single task tools, there is a growing demand for combining available technologies to create a composite application. The tools should be able to communicate with one another and successfully utilise the same data. To reduce the time and effort now spent analysing petabytes of data held by organisations and governments around the world, user-friendly databases are required.
Furthermore, data storage and organisation concerns are constraining the market's growth. Rapid data gathering creates organisational issues because the data is diverse and may pertain to demographics, illness associations, symptoms, therapeutic medications, and other topics.
For players in the worldwide computational biology market, developing computer networks for disease surveillance and mapping the pathways and biological networks linked with illness beginning are projected to provide lucrative growth prospects.
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