ARTIFICIAL INTELLIGENCE (AI) IN GENOMICS MARKET ANALYSIS

Artificial Intelligence (AI) in Genomics MarketSize and Trends

The global artificial intelligence (AI) in genomics market was valued at US$ 1.15 Bn in 2023 and is forecast to reach a value of US$ 19.72 Bn by 2030 at a CAGR of 50.1% between 2023 and 2030. The global artificial intelligence (AI) in genomics market is experiencing strong growth owing to the increasing biomedical and genomic datasets, growing adoption of ai-based solutions, rising focus on reducing turnaround time in drug discovery & diagnostics is expected to boost the market growth. However, lack of skilled workforce & infrastructure, Ambiguous Regulatory Guidelines For Genomics Software, Poor Security & Storage Of Large Volumes Of Genome Sequencing Data.

Figure 1. Global Artificial Intelligence (AI) in Genomics Market Share (%), by Region, 2023

Global Artificial Intelligence (AI) in Genomics Market Trends:

Increasing Collaborations of Pharmaceutical and Software Companies

• The pharmaceutical industry is under pressure, with growing costs of research and development (R&D) corroding profit margins. AI has the ability to transform drug discovery by rapidly accelerating the R&D timeline, making drug development cheaper and faster,  and  improving  the  probability  of  approval.  Almost 100 partnerships have been identified between AI vendors and big pharma companies since 2015, with increasing numbers witnessed in recent years.
• AI is at the forefront of contemporary technology and has begun to parallel in the sphere of biotechnology. Several biopharma companies are using AI to drive innovation, improve their processes and discover new business models. Key drug discovery companies understand that AI can offer critical business advantages. It can facilitate the analysis of huge databases, speed up R&D, promote effective decision- making, and save costs. Big companies involving Johnson & Johnson, AstraZeneca, and  Pfizer  have  made  great  advances  in  integrating  AI  with  genomics  and engineering tools in pharmaceutical applications, as it assists in improving target identification and validation. An early adopter of AI, AstraZeneca is employing knowledge graphs and image analysis to collect new insights on diseases and classify biomarkers 30% faster than human pathologists. Collaborations with specialists in AI for drug hunting, such as New York-based Renalytix AI, Oakland-headquartered