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Clinical genomics regained significance during the pandemic with the development of the mRNA COVID-19 vaccine, and several non-invasive at-home test kits; an unprecedented feat in recent times. Genomics will take center stage, as large genome sequencing and research will continuously create data for new therapeutics. Artificial Intelligence (AI) and its sub-disciplines Machine Learning (ML) and Deep Learning (DL), are being used in the discovery of biomarkers for clinical diagnostics, consumer point-of-care-tests, and interpretative services.

AI algorithms will extract, analyze, and interpret deep phenotypic information gathered from diagnostic platforms (clinical genomic workflow: next-generation sequencing, whole genome sequencing, real-time PCR), microarray, pathology imaging platforms, gene testing platforms, multiomics and microfluidic platforms, EHRs, and other point-of-care tests. The AI-integrated software with sample management technology will provide workflow efficiency, scalability, automation and streamline end-to-end platform operations. AI-based decentralized solutions will evolve further to meet the need for intuitive, affordable, and accurate tests. Finally, the informatics and interpretive services will create clinical insights interpretation for actionable diagnosis. DNA sequencing interpretation of exomes and genomes, medical interpretation, and so on, will be based on expert-curated knowledge bases and automated tools.

The study offers insight into the industry environment of clinical genomics and AI, its value proposition, and applications and examines the participation of top technology companies in clinical genomics and the business opportunities created for all stakeholders.