Market Challenges And Opportunities

Global Computational Biology Market - Drivers

Increasing clinical trial activities using computational designs

Increasing research and development with the use of computational biology are expected to drive the global computational biology market growth over the forecast period. For instance, on April 13, 2021, Peptilogics, a U.S.-based biotechnology company, announced that by using computational design to discover novel peptide therapeutics, it has successfully completed Phase 1 clinical trial for its lead compound PLG0206, a potent, broad-spectrum anti-infective used in the treatment of prosthetic joint infections. Unlike existing antibiotics, PLG0206 directly addresses the biofilm and the persister pathogens that make PJI so difficult to treat and can be administered locally to the infected site, while maintaining a very low resistance profile.

Increasing launches of new technologies in computational biology

Increasing launch of new products in computational biology is expected to drive the global computational biology market growth. For instance, on May 31, 2023, Biognosys AG, a Switzerland-based next-generation proteomics contract research services provider, launched Spectronaut 18 and major scientific and technological advances for its proprietary proteomics research software and services. Spectronaut 18 provides DIA data analysis with unprecedented throughput and efficiency. Software and services like TrueDiscovery accelerates biomarker discovery in oncology and neuroscience, TrueTarget offers high-resolution drug target identification and deconvolution while Bruker ProteoScape a software for computational 4D Proteomics was introduced for the monitoring and optimization of system performance for timsTOF platform.

Global Computational Biology Market: Restraints

Lack of standardization of life science data

The lack of standardization of life science data is expected to hamper the global computational biology market growth. For instance, according to an article published by F1000 Research on May 10, 2022, reproducibility crisis is a challenge that needs action. Reasons for this crisis are manifold, among them one is lack of appropriate study design. Lack of proper controls or insufficient documentation are also some of reasons of reproducibility crisis. However, the main reason for reproducibility crisis is the absence of a unifying quality control and assurance framework. High-quality records are essential for the quality and reproducibility of research results and efficient technology transfer. Standards facilitate the alignment of consensus-based best practices, reduce variance, and improve reproducibility in research. There is rise in the need for combination of the available software to build a composite application for current single task tools. As there is lack of global standardization of the methodology, researchers face difficulties with the reproducibility of products.

To counterbalance this restraint, a protocol should be introduced to offer reproducibility in results.

Issues of data storage

The lack of proper management of large amount of data generated is expected to hamper the global computational biology market growth. For instance, according to an article published in Journal Gene reports on December 2020, there is a need to bridge the gap between high-throughput technological development and ability to manage, analyze and integrate the biological data. Expertise in data management is needed to solve this problem. Rapid data accumulation poses challenges in organizing the data as it is diverse and may belong to populations, disease associations, symptoms, therapeutic drugs, and others. Data privacy and security is also necessary to manage in bioinformatics and computational biology.

To counterbalance this restrain, more training to personnel and efficient network should be prepared to manage a large amount of data.