Computational Biology Market Observes Tremendous Rise in CAGR of 17.6% with Revenue up to US$ 12,601.1 Mn by 2027| Coherent Market Insights

Computational Biology is an inter-disciplinary applied science that studies biological systems using mathematical, theoretical, and computer simulation models based on basic biology concepts. The rise in R&D for drug discovery, demand for predictive models, use in population-based sequencing projects such as the human genome project, and government funding are all factors driving market growth.

The development and application of data-analytical and theoretical methods, mathematical modelling, and computational simulation techniques in life sciences is the focus of computational biology. The global computational biology market is expected to be worth US$ 12,601.1 Mn by the end of 2027. Over the forecast period, the high cost of drug development is expected to drive growth in the global computational biology market. For example, according to a March 2020 JAMA analysis, US biopharmaceutical companies spent approximately US$ 1 billion to bring each of their new drugs to market between 2009 and 2018.

Computational Biology Market

The Global Computational Biology Market was valued at US$ 3,453.2 Mn in 2019 and is forecast to reach a value of US$ 12,601.1 Mn by 2027 at a CAGR of 17.6% between 2020 and 2027.

Furthermore, several advantages of computational biology are expected to aid in Global Computational Biology Market growth. Predictive modelling tools in computational biology can provide invaluable information to help streamline the drug development process. Predictive modelling aids in reducing the total number of recruited patients and shortening the duration of clinical trials. North America dominated the global computational biology market in 2019, accounting for 44.2% of the total value, followed by Europe and Asia Pacific, respectively.

Furthermore, data storage and organisation issues are limiting market growth. Rapid data accumulation poses organisational challenges because the data is diverse and may pertain to populations, disease associations, symptoms, therapeutic drugs, and others. Massive amounts of data, combined with a lack of standardisation, have stifled the growth of the computational biology market. There is a growing demand for combining available software to create a composite application for current single task tools. The tools must be compatible with one another and be able to effectively use the same data. User-friendly databases are required to reduce the time and effort currently spent on analysing the petabytes of data available to institutions and governments worldwide.

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