Artificial Intelligence (AI) in Drug Discovery Market Size: Market Entry Strategies and Insights from matthew mile's blog
The size of the Artificial Intelligence (AI) in Drug Discovery Market reached US$ 722.3 million in 2022 and is expected to soar to US$ 11.15 billion by 2030, exhibiting a remarkable compound annual growth rate (CAGR) of 40.8% during the forecast period from 2023 to 2030.
This exponential growth can be attributed to the increasing adoption of AI technologies in the field of drug discovery. AI has revolutionized the pharmaceutical industry by enhancing the efficiency and effectiveness of drug development processes. By leveraging advanced algorithms and machine learning techniques, AI enables researchers to analyze vast amounts of data, identify potential drug candidates, and predict their efficacy with greater accuracy.
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The rising demand for personalized medicine and the need to accelerate the drug discovery process have further fueled the adoption of AI in this sector. With AI-powered tools, pharmaceutical companies can streamline their research and development efforts, reduce costs, and expedite the delivery of life-saving medications to patients.
Moreover, the COVID-19 pandemic has underscored the importance of AI in drug discovery. The urgent need for effective treatments and vaccines has prompted researchers to leverage AI algorithms to identify potential drug targets and repurpose existing drugs. This has not only accelerated the development of COVID-19 therapeutics but has also highlighted the immense potential of AI in addressing future healthcare challenges.
As the market continues to grow, key players in the AI in Drug Discovery industry are investing heavily in research and development to enhance their AI capabilities. Collaborations between pharmaceutical companies and AI technology providers are also on the rise, fostering innovation and driving the market forward.
KEY MARKET SEGMENTATION:
By Component
- Software
- Services
By Technology
- Machine Learning
- Deep Learning
- Supervised Learning
- Reinforcement Learning
- Unsupervised Learning
- Others Technologies
By End-Use
- Pharmaceutical & Biotechnology Companies
- Contract Research Organizations
- Research Centres
- Academic & Government Institutes
By Application
- Excavation and mining
- Immuno-Oncology
- Neurodegenerative Diseases
- Cardiovascular Diseases
- Metabolic Diseases
- Other Applications
Major Players Listed in the Report are as Follows:
IBM Corporation, Microsoft, Google, NVIDIA Corporation, Atomwise, Inc., Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, BenevolentAI, Exscientia, Cyclica, BIOAGE, Numerate, NuMedii, Envisagenics, twoXAR, OWKIN, Inc., XtalPi, Verge Genomics, BERG LLC and Other Players.
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