Artificial intelligence (AI) is the advancement of computer systems that can complete tasks that usually need human intelligence. In some areas, such as clinical genomics, a particular type of AI algorithm called deep learning is utilized to process complex and large genomic datasets. Imitating human intelligence is the motivation for AI algorithms, but AI applications in clinical genomics tend to target tasks that are impractical to achieve using human intelligence and error-prone when addressed with standard statistical approaches. Many techniques have been modified to address the numerous steps included in the clinical genomic analysis—including genome annotation, phenotype-to-genotype correspondence variant calling, variant classification, and possibly they can also employ for genotype-to-phenotype predictions.
COVID-19 Impact analysis
COVID-19 is an infectious disease that originated in Hubei province of the Wuhan city in China in late December. The highly contagious disease, caused by a virus, severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), is transmitted from human to human. Since the outbreak in December 2019, the disease has spread to almost 213 countries around the globe with the World Health Organization declaring it a public health emergency on March 11, 2020.
At the early phase of COVID-19 pandemic, there was no availability of specific diagnostic tests to detect the disease in patients. Alternative diagnostic tests were used initially but were not much effective. This unavailability of specific COVID-19 diagnostic tests presented lucrative opportunities for diagnostic manufacturers to introduce their COVID-19 diagnostic kits. Many leading players as well as some start-ups from various countries utilized this opportunity and introduced COVID-19 diagnostics kits into local as well as global market. These players achieved edge over other diagnostics players capitalizing the opportunity from demand for COVID-19 diagnostic tests, which, in turn, helps them in maintaining their revenues in such a crisis.
Owing to such factors, COVID 19 is expected to have a significant impact on the artificial intelligence in genomics market.
Top Impacting Factors
- Increase in public and private investments in AI in genomics, rise in adoption rate of AI solutions in precision medicine, and necessity to control drug development and time and discovery costs drive the growth of artificial intelligence in the genomics market.
- In addition, increase in healthcare expenditure; availability of skilled professionals; rise in R&D activities, and technological advancements, are some factors, which boost the market growth for artificial intelligence in genomics.
- However, lack of a skilled AI workforce and strict regulatory guidelines for medical software, and lack of curated genomics data hinder the market growth.
- Contrarily, concentrating on developing human-aware AI systems is expected to present new pathways in the industry.
Artificial Intelligence In Genomics Market Trends
New product launches to flourish the market
- In February 2020, IBM Watson Health signed an agreement with Broad Institute of MIT and Harvard (US). An extended partnership will enable the Broad Institute to examine and explore genomics data to comprehend intrinsic susceptibility.
- In October 2020, NVIDIA declared collaboration with global healthcare company GSK and its AI group. GSK’s new hub in London is anticipated to help its UK-based team and scientists from NVIDIA to improve drug and vaccine discovery using NVIDIA platforms.
Key Benefits of the Report
- This study presents the analytical depiction of the artificial intelligence in genomics industry along with the current trends and future estimations to determine the imminent investment pockets.
- The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the artificial intelligence in genomics market share.
- The current market is quantitatively analyzed to highlight the artificial intelligence in genomics market growth scenario.
- Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.
- The report provides a detailed artificial intelligence in genomics market analysis based on competitive intensity and how the competition will take shape in coming years
Questions answered in the artificial intelligence in genomics Report
- Which are the leading players active in the artificial intelligence in genomics market?
- What are the current trends that will influence the artificial intelligence in genomics market in the next few years?
- What are the driving factors, restraints, and opportunities of the artificial intelligence in genomics market?
- What future projections would help in taking further strategic steps?
- What is "Artificial intelligence in genomics"?
- What is "Artificial intelligence in genomics" Market prediction in the future?
- Who are the leading global players in the "Artificial intelligence in genomics" Market?
- What are the current trends and predicted trends?
- What are the key benefits of the "Artificial intelligence in genomics" Market report?
Artificial Intelligence in Genomics Market Report Highlights
By End User
Key Market Players
Verge Genomics, Cambridge Cancer Genomics, MolecularMatch Inc., IBM, Freenome Holdings, Inc., NVIDIA Corporation, Fabric Genomics Inc., BenevolentAI, Deep Genomics, Microsoft