Press release
Artificial Intelligence (AI) In Drug Discovery Global Market Report 2024 - By Demand, Report, Share, Analysis, Forecast To 2033
Artificial Intelligence (AI) In Drug Discovery Market
The Business Research Company offers in-depth market insights through Artificial Intelligence (AI) In Drug Discovery Global Market Report 2024, providing businesses with a competitive advantage by thoroughly analyzing the market structure, including estimates for numerous segments and sub-segments.
Market Size And Growth Forecast:
The artificial intelligence (ai) in drug discovery market size has grown exponentially in recent years. It will grow from $1.37 billion in 2023 to $1.79 billion in 2024 at a compound annual growth rate (CAGR) of 30.8%. The growth in the historic period can be attributed to growth in emerging markets, the rising prevalence of chronic diseases, the increased adoption of artificial intelligence (ai) for cost efficient drug discovery and the increasing strict quality regulations for drug manufacturers.
The artificial intelligence (ai) in drug discovery market size is expected to see exponential growth in the next few years. It will grow to $4.71 billion in 2028 at a compound annual growth rate (CAGR) of 27.4%. The growth in the forecast period can be attributed to the government support, the increasing healthcare expenditure and rising adoption of cloud-based applications and services. Major trends in the forecast period include integration of multi-omics data, use of ai in target selection, use of ai in drug screening, introduction of ai innovation labs, increasing investments and partnerships and collaborations.
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Market Segmentation:
The artificial intelligence (ai) in drug discovery market covered in this report is segmented -
1) By Technology: Context-Aware Processing, Natural Language Processing, Querying Method, Deep Learning
2) By Drug Type: Small Molecules, Large Molecules
3) By Therapeutic Type: Metabolic Disease, Cardiovascular Disease, Oncology, Neurodegenerative Diseases, Anti-Infective Diseases, Respiratory Diseases, Other Therapeutics
4) By End User: Pharmaceutical Companies, Biopharmaceutical Companies, Academic And Research Institutes, Other End-Users
Major Driver - AI In Drug Discovery Surges With Growing Demand For Personalized Medicine
The growing demand for personalized medicine is expected to propel the growth of the artificial intelligence (AI) in drug discovery market going forward. Personalized medicine refers to a type of medication that prevents, detects, or treats disease using knowledge about a person's own genes or proteins. AI can play a crucial role in the development of personalized medicines at all relevant phases of clinical development and implementation of new personalized health products by finding appropriate intervention targets and testing intervention targets for their utility. For instance, according to the Personalized Medicine Coalition, a US-based professional membership organization, in 2022, the US Food and Drug Administration (FDA) approved 12 personalized medicines, which accounted for approximately 34% of all newly approved therapeutic molecular entities. Thus, the growing demand for personalized medicine is driving the growth of the artificial intelligence (AI) in drug discovery market.
Competitive Landscape:
Major companies operating in the artificial intelligence (ai) in drug discovery market report are IBM Corporation, Microsoft Corporation, NVIDIA Corporation, Exscientia, Alphabet, Atomwise Inc., Insilico Medicine, Owkin Inc, Xtalpi Inc, Cloud Pharmaceuticals, Shanghai PharmaceuticS, Standigm, Indegene, Intuition Systems, Innoplexus, Takeda Pharmaceutical Company Ltd., RxPrism, Otsuka Pharmaceutical Co. Ltd., China National Pharmaceutical Group Co., Ltd., Jiangsu Hengrui Medicine Co., Ltd, Cipla Limited, Aurobindo Pharma Limited, Dr. Reddy's Laboratories Ltd., Sun Pharma, Tricog Health Services Pvt. Ltd., Alliance Pharm Pte Ltd., GSK Australia , CytoReason, IIPharma, StoneWise, Adagene, GT Apeiron Therapeutics, Xbiome, Accutar Biotech, DeepMind, Renalytix AI, Iktos, Ipsen Pharma, Galderma S.A., BenevolentAI, Deepflare, Novartis, Gero, Ardigen, Botkin, Care Mentor AI , Diagnocat, GNS Healthcare, Merck & Co., Apotex, Pfizer, Gilead Sciences, Roche, Bayer, AbbVie Inc., GlaxoSmithKline, AstraZeneca, Amgen, Sanofi Pasteur, Abbott Laboratories, Janssen Pharmaceutica, Teva Canada, Accord Healthcare Inc, Acerus Pharmaceuticals Corporation, AA Pharma Inc, Sanfer, Siegfried Rhein, Atomwise, Inc., Bioage, NuMedii, Envisagenics, Aria Pharmaceuticals, Verge Genomics, Berg LLC, Deep Genomics, Cyclica , IQVIA, Quris, GE Healthcare, Avanade , Group42 Holding Ltd, Ilara Health, Adcock Ingram , Johnson & Johnson, Eurolab , Ranbaxy (SA) (Pty) Ltd, Aspen, Rology, hearX Group, DilenyTech
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Top Trend - Strategic Collaborations Propel AI Drug Discovery
Major companies operating in the AI drug delivery market are adopting strategic collaborations to research and discover drugs using AI and are gaining significant popularity in the artificial intelligence in drug discovery market. For instance, in August 2022, Atomwise, a US-based artificial intelligence systems company, partnered with Sanofi. The partnership aimed at computationally identifying and investigating up to five pharmacological targets using the Atomwise AI-powered AtomNet technology. To find, create, and advance lead compounds for up to five Sanofi-exclusive targets, Atomwise received a $20 million upfront payment from Sanofi. Sanofi is a French pharmaceutical and healthcare company.
The Table Of Content For The Market Report Include:
1. Executive Summary
2. Artificial Intelligence (AI) In Drug Discovery Market Characteristics
3. Artificial Intelligence (AI) In Drug Discovery Market Trends And Strategies
4. Artificial Intelligence (AI) In Drug Discovery Market - Macro Economic Scenario
5. Artificial Intelligence (AI) In Drug Discovery Market Size And Growth
…..
27. Artificial Intelligence (AI) In Drug Discovery Market Competitor Landscape And Company Profiles
28. Key Mergers And Acquisitions
29. Future Outlook and Potential Analysis
30. Appendix
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