by Artificial intelligence (AI) has greatly transformed the drug discovery process by assisting in target identification, lead optimization, and clinical trials. AI techniques such as machine learning and deep learning have enabled analysis of large and complex datasets to identify viable drug targets and candidate molecules for various therapeutic areas more efficiently. This has significantly reduced the time and costs associated with drug development. The global Artificial Intelligence in Drug Discovery Market is estimated to be valued at US$ 1266.7 Mn in 2023 and is expected to exhibit a CAGR of 6.9% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
AI in drug discovery uses biological and chemical data to identify and validate new drug targets, design potential drug molecules, and predict how well each drug candidate will perform in clinical trials. Drugs developed using AI show higher success rates and reduced costs compared to conventional methods. AI has enabled processing of massive genomic and chemical data to understand disease pathways at a molecular level. This helps identify novel targets and create digital models of diseases and patients. Machine learning algorithms can screen billions of chemical structures in digital libraries to propose new molecules for synthesis and testing. Such techniques enhance the speed, efficiency and outcomes of drug R&D.
Market key trends:
Some of the key trends in the artificial intelligence in drug discovery market include growing government investments to support AI in healthcare, increasing focus on personalized medicine, and rise of open innovation models. Governments across regions are providing funding for research in AI for drug discovery and its clinical applications. Pharma companies are also forming open innovation partnerships with AI startups and labs to tap external innovative ideas and solutions. Adoption of AI is enabling discovery of tailored therapies based on an individual’s genetic profile and disease characteristics which is driving the trend towards personalized medicines.
Porter’s Analysis
Threat of new entrants: The threat of new entrants into the Artificial Intelligence in Drug Discovery Market is moderate. While emerging technologies are lowering barriers to entry, development of AI technologies for drug discovery requires significant capital investment and access to large datasets.
Bargaining power of buyers: The bargaining power of buyers in the Artificial Intelligence in Drug Discovery Market is high. Life science companies and pharmaceutical firms can negotiate on price and choose from various AI solution providers for their drug discovery needs.
Bargaining power of suppliers: The bargaining power of suppliers is moderate as there are many AI technology companies developing solutions for drug discovery. However, access to specialized skills and huge pharma databases provides some vendors an edge.
Threat of new substitutes: Threat from new substitutes is low as AI is still evolving and there are no perfect substitutes for data-driven techniques in drug discovery currently.
Competitive rivalry: The competitive rivalry in the Artificial Intelligence in Drug Discovery Market is high owing to presence of many global as well as regional players offering proprietary techniques and solutions.
Key Takeaways
The Global Artificial Intelligence In Drug Discovery Market Share is expected to witness high growth.
Regional analysis: The North America region currently dominates the market due to presence of major pharmaceutical companies and AI technology providers in the US. However, Asia Pacific is expected to witness the highest growth owing to increasing investments by Chinese and Indian governments in developing AI-based healthcare solutions.
Key players related content comprises Key players operating in the Artificial Intelligence in Drug Discovery Market are Lenzing A.G., Aditya Birla Group, AkzoNobel N.V., Smartfiber AG, Nien Foun Fiber Co., Ltd., Invista , Baoding Swan Fiber Co. Ltd., Qingdao Textiles Group Fiber Technology Co., Ltd., China Bambro Textile (Group) Co., Ltd., Acegreen Eco-Material Technology Co. Ltd., China Populus Textile Ltd., and Acelon Chemicals & Fiber Corp. Life science giants are also developing their own AI-based drug discovery platforms and collaborating with AI companies. For instance, Pfizer partnered with IBM Watson to enhance drug discovery using AI techniques.
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Source: Coherent Market Insights, Public sources, Desk research
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