Drug Discovery Informatics Market Share, Size, Trends, Industry Analysis Report, By Workflow (Discovery Informatics, Development Informatics); By Mode (Outsourced, In-house); By Services (Sequence Analysis Platforms, Molecular Modeling, Docking, Clinical Trial Data Management, Others); By Regions; Segment Forecast, 2021 – 2028
The global drug discovery informatics market size is expected to reach USD 5.62 billion by 2028 according to a new study by Polaris Market Research. The report “Drug Discovery Informatics Market Share, Size, Trends, Industry Analysis Report, By Workflow (Discovery Informatics, Development Informatics); By Mode (Outsourced, In-house); By Services (Sequence Analysis Platforms, Molecular Modeling, Docking, Clinical Trial Data Management, Others); By Regions; Segment Forecast, 2021 – 2028” gives a detailed insight into current market dynamics and provides analysis on future market growth.
In 2020, the sequence analysis market segment accounted for the largest share and is likely to register a significant market growth over the study period. For sequence analysis, bioinformatics tools play an important role. They are widely used for the development of in-proprietary databases of protein, nucleic acid, and other biomolecule sequences. With the rising application of informatics solutions, gene sequencing is done through the identification of proteins and genes, which could further help in the development of potential drugs.
Basic drug discovery requires the involvement of different sets of databases, sequence analysis tools, such as BLAST, FASTA, and CLUSTALW. Moreover, the introduction of new products and software tools with higher computing capabilities are further contributing to the segment’s market growth. In this line, in July 2019, Certara introduced its new version of D360, a drug discovery platform. The platform enabled analysis, representation, alignment of the small sections of peptides.
The molecular modeling market segment is projected to witness a lucrative market growth over the study period. The technique is gaining popularity, owing to its wide applicability in the drug discovery process. Such tools are mostly used for the simulation of small molecules to predict their behavior at the molecular level. Moreover, the technique is also able to accelerate cost-efficiency in the drug discovery process.
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