The Business Research Company has updated its global market reports with latest data for 2024 and projections up to 2033.
The AI In Pharma by The Business Research Company provides market overview across 60+ geographies in the seven regions - Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa, encompassing 27 major global industries. The report presents a comprehensive analysis over a ten-year historic period (2010-2021) and extends its insights into a ten-year forecast period (2023-2033).
Learn More On The AI In Pharma Market:
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According to The Business Research Company’s AI In Pharma, The ai in pharma market size has grown exponentially in recent years. It will grow from $1.58 billion in 2023 to $2.06 billion in 2024 at a compound annual growth rate (CAGR) of 30.4%. The growth in the historic period can be attributed to increased adoption of artificial intelligence (ai) for cost efficient drug discovery and rising implementation of ai in radiology.The ai in pharma market size is expected to see exponential growth in the next few years. It will grow to $5.62 billion in 2028 at a compound annual growth rate (CAGR) of 28.5%.
The increasing government support for AI development is expected to drive the growth of the AI in pharmaceuticals market in the coming years. Governments worldwide are acknowledging the potential of AI technologies in transforming the pharmaceutical sector and are actively implementing policies and initiatives to encourage their adoption. Many countries have formulated national AI strategies that specifically target healthcare and pharmaceutical applications, aiming to foster scientific progress and address real-world challenges in the field. For instance, in April 2022, the Australian government unveiled a funding program amounting to AUD 44 million ($29.61 million) to bolster AI research among small and medium-sized enterprises (SMEs). This initiative is part of a broader strategy to boost AI utilization in Australia's key manufacturing and digital growth sectors, including pharmaceuticals. The funding will support the establishment of digital capability centers, acting as hubs for AI research and development. These centers will offer resources, training, and assistance to SMEs, empowering them to innovate and implement AI technologies. Hence, the increasing government support is poised to propel the growth of the AI in pharmaceuticals market in the forecast period.
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The ai in pharma 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 Molecule, Large Molecules
3) By Application: Diagnosis, Clinical Trial Research, Drug Discovery, Research and Development, Epidemic Prediction
Top Major Players
Concerto HealthAI,
Alphabet Inc.,
OWKIN,
Nvidia Corporation,
PathAI
The ai in pharma market report table of contents includes:
1. Executive Summary
2. AI In Pharma Market Characteristics
3. AI In Pharma Market Trends And Strategies
4. AI In Pharma Market - Macro Economic Scenario
5. Global AI In Pharma Market Size and Growth
6. AI In Pharma Market Segmentation
7. AI In Pharma Market Regional And Country Analysis
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34. Key Mergers And Acquisitions In The AI In Pharma Market
35. AI In Pharma Market Future Outlook and Potential Analysis
36. Appendix
List Of Tables :
Table 1: Global Historic Market Growth, 2018-2023, $ Billion
Table 2: Global Forecast Market Growth, 2023-2028F, 2033F, $ Billion
Table 3: Global AI In Pharma Market, Segmentation By Technology, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
Table 4: Global AI In Pharma Market, Segmentation By Drug Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
Table 5: Global AI In Pharma Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
...............
Table 74: Concerto HealthAI Financial Performance
Table 75: Alphabet Inc. Financial Performance
Table 76: OWKIN Financial Performance
Table 77: Nvidia Corporation Financial Performance
Table 78: PathAI Financial Performance
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As a well-positioned AI development company, Oodles AI explores effective applications of AI in Pharma across drug R, screening, and clinical trials.
Under machine learning development, deep learning is an approach that uses neural network structures for analyzing the target specificity.
The very technology that powers facial recognition is channelized to generate biologically relevant features for both drug and target.
Learn more: AI in Pharma: Evolution of Drug Discovery and Supply Chain
Therefore, the use of technology can save time and money, while providing a far better understanding of the relationships between different formulations and processes parameters.Key Drivers, Restraints, and Opportunities of AI in Pharma and Biotech MarketAdoption of artificial intelligence (AI) in the drug discovery market in developing regions such as APAC is increasing, thanks to the expansion of pharmaceutical industries by collaborating with other industries and rise in demand to reduce drug discovery time.
Furthermore, the expansion of biotechnology industries is estimated to offer significant opportunities for the market.An estimated 50% of U.S. citizens are affected by at least one chronic condition; consequently, the pharmaceutical segment of the healthcare industry is projected to be positively impacted by the expected trend of AI adoption.All top 10 so-called giant pharma companies (namely Novartis, Roche, Pfizer, Merck, AstraZeneca, GlaxoSmithKline, Sanofi, Abbvie, Bristol-Myers Squibb, and Johnson & Johnson) have either expressly collaborated with or acquired AI technologies to take advantage of the opportunities AI brings to the table.
Industry leaders are presently focused on the development of more efficient methods, and machine learning is emerging as a possible solution.The current machine learning initiatives of the top five pharmaceutical and biotechnology companies reveal trends within the following areas:Digital coaching solutions – Utilization of web-based technologies to simulate one-on-one coaching sessions so that all patients can have the benefit of a uniquely devised medication program.For instance: Johnson & Johnson’s Patient Athlete programPersonalized medicine – Personalized medicine, also called precision medicine, maybe a medical model that separates people into different groups—with medical decisions, practices, interventions, and/or products being tailored to the individual patient supported their predicted response or risk of disease.For instance.
Unlike other applications within healthcare facilities, drug discovery seems to own a clearer path to adoption.Recently, robots became more collaborative with humans and are more easily trained by moving them through the desired task.
Over time, it seems likely that an equivalent improvement in intelligence that we have seen in other areas of AI would be incorporated into physical robots.Surgical robots initially approved in the U.S. in 2000, provided ‘superpowers’ to surgeons, improving their ability to examine, create precise and minimally invasive incisions, and stitch wounds.
Common surgical procedures using robotic surgery include gynecologic surgery, prostate surgery, and head and neck surgery.Pre Book Ai In Pharma And Biotech Market Report – https://www.transparencymarketresearch.com/checkout.php?rep_id=79399=SNorth America to Capture Major Share of Global Market of AI in Pharma & BiotechNorth America is expected to account for a major share of the global market of AI in Pharma and Biotech due to the high prevalence of chronic diseases among the population.
