The global Artificial Intelligence in Drug Discovery Market is estimated to be valued at US$ 1,266.7 Mn in 2023 and is expected to exhibit a CAGR of 5.7% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market Overview:
Artificial intelligence in drug discovery uses machine learning and deep learning algorithms to analyze large and complex datasets for faster drug discovery. It helps identify new target molecules, generate new compounds for specific disease conditions and analyze clinical trials.
Market key trends:
One of the major trends in the artificial intelligence in drug discovery market is the increasing adoption of machine learning. Machine learning algorithms can analyze huge volumes of biochemical and genomic data to reveal novel biological insights and accelerate drug discovery. It helps find patterns in large datasets that are otherwise impossible to detect manually. Another key trend is the growing use of artificial intelligence and cloud computing. Pharmaceutical companies are leveraging cloud-based AI solutions to gain insights from petabytes of data in real-time and drive faster decision making. This has significantly reduced costs and improved the efficiency of drug development processes.
SWOT Analysis
Strength: AI is highly suited for drug discovery as it can analyze huge amounts of chemical and biological data more efficiently than humans can. It can also identify new drug targets by quickly scanning biological knowledge and find new uses for existing drugs.
Weakness: Lack of explainability is a challenge as AI systems work as black boxes and do not provide rationales for their decisions. Building accurate computational models also requires huge amounts of high-quality data which is often limited in drug discovery.
Opportunity: AI can help accelerate each stage of drug discovery from target identification to clinical trials. It also provides opportunities to discover new drug targets and drug candidates for diseases lacking effective treatments. Personalized medicine can also benefit through AI-based approaches.
Threats: Heavy reliance on AI can reduce human judgment and understanding of disease biology. Technical challenges around data quality and privacy also pose threats. Competition from startups and tech giants is intensifying.
Key Takeaways
The Global Artificial Intelligence in Drug Discovery Market Share is expected to witness high growth, exhibiting a CAGR of 5.7% over the forecast period, due to increasing demand for intelligent systems in drug R&D. North America currently dominates the market due to concentration of key pharma companies and availability of venture funding for AI startups in the region.
Regional analysis: North America is expected to continue dominating the market throughout the forecast period owing to rising investments by pharmaceutical companies as well as venture capital funding for AI drug discovery startups in the US and Canada. Asia Pacific is anticipated to exhibit the fastest growth due to growing biopharmaceutical industry in China and India along with initiatives to adopt advanced technologies including AI.
Key players: Key players operating in the Artificial Intelligence in Drug Discovery market are IBM Corporation (IBM Watson Health), Exscientia, GNS Healthcare, Alphabet, Inc. (DEEPMIND), Benevolent AI, Biosymetrics, Euretos, Berg LLC., Atomwise, Inc., Insitro, and among others. These players are adopting various organic and inorganic growth strategies like partnerships, new service launches and investments to remain competitive in the market.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it