by Market Overview (200 words)- Artificial Intelligence (AI) in pharmaceutical refers to application of various machine learning algorithms and neural networks to process large amounts of data from clinical trials, research, diagnoses, and more. AI helps in reducing time and cost of drug discovery process by virtually screening thousands of potential drug compounds in shorter duration. It also assists pharmaceutical companies in precision medicine by analyzing large patient datasets to determine best treatment path for an individual. The global artificial intelligence (AI) in pharmaceutical market is driven by increasing investment in pharmaceutical R&D and growing need to manage complexity in drug discovery process.
The Global Artificial Intelligence (AI) In Pharmaceutical Market is estimated to be valued at US$ 1,108.1 Mn in 2024 and is expected to exhibit a CAGR of 32.% over the forecast period 2024 to 2031.
Key Takeaways
Key players operating in the Global Artificial Intelligence (AI) in Pharmaceutical are NVIDIA Corporation, IBM Corporation, Exscientia, Insilico Medicine, Atomwise, Inc., Cloud Pharmaceuticals, Inc., Cyclica Inc., Envisagenics, Inc., Numerate, Inc., Schrödinger, Inc., Standigm, Turbine.ai. These players are focusing on developing new AI platforms andtools for applications across drug discovery and clinical trials.
In terms of opportunities, AI has potential to reduce R&D costs by upto 30% by discovering 60% of compounds that enter trials. It can help pharmaceutical companies in developing personalized treatment approaches through precision medicine and reduce time taken in drug discovery from several years to just one year.
Global Artificial Intelligence (AI) In Pharmaceutical Market Demand due to presence of major pharmaceutical companies investing in AI based solutions. However, Asia Pacific region is expected to offer lucrative growth opportunities during forecast period with increasing investments by governments and private organizations in development of AI-based healthcare solutions.
Market Drivers
The key driver for growth of global AI in pharmaceutical market includes increasing investment by pharmaceutical companies in R&D. Pharmaceutical companies are adopting AI solutions extensively to speed up drug discovery process and manage rising R&D costs. Furthermore, growing need for personalized treatment approaches aided by precision medicine is also accelerating adoption of AI in pharmaceutical sector globally.
PEST Analysis
Political: Government initiatives and regulations related to data privacy and AI ethics will impact the development and use of AI techniques in drug discovery.
Economic: Global Artificial Intelligence (AI) In Pharmaceutical Market Size And Trends and high failure rates of drug candidates are driving increased investment in AI to improve success rates and productivity.
Social: Aging population and rising disease burden is increasing demand for more effective and personalized treatments, driving interest in AI and drugs.
Technological: Advancements in machine learning, computing power, data analytics and cloud infrastructure enable powerful drug discovery tools based on large biomedical datasets. Deep learning models can now screen millions of potential drug candidates in silico.
Geographical Regions of Concentration
North America, especially the United States, currently accounts for the largest share of the global artificial intelligence in pharmaceuticals market in terms of value. This is due to presence of major pharmaceutical companies and technology giants as well as favorable government funding for AI and biotech research.
Fastest Growing Region
The Asia Pacific region is expected to experience the highest growth in the artificial intelligence in pharmaceutical market during the forecast period. This is because of increasing healthcare expenditure, growing biopharma industry, and government initiatives to promote digital health and adoption of advanced technologies in countries like China, India, and South Korea.
*Note:
1.Source: Coherent Market Insights, Public sources, Desk research
2.We have leveraged AI tools to mine information and compile it
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