How AI is Transforming the Drug Discovery Market Landscape

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The AI In Drug Discovery Market Size is Anticipated to Exceed USD 19.9 Billion by 2033, Growing at a CAGR of 38.25% from 2023 to 2033.

The report Global AI In Drug Discovery Market provides highlighting new business opportunities and supporting strategic and tactical decision-making. This report recognizes that in this rapidly-evolving and competitive environment, up-to-date marketing information is essential to monitor performance and make critical decisions for growth and profitability. It provides information on trends and developments and focuses on markets capacities and on the changing structure of the AI In Drug Discovery. The report highlights powerful factors augmenting the demand in the global AI In Drug Discovery market and even those hampering the market on a worldwide scale.

The AI In Drug Discovery Market Size is Anticipated to Exceed USD 19.9 Billion by 2033, Growing at a CAGR of 38.25% from 2023 to 2033.

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Valuable Market Analytical Insights Included in the Report:

1. Size Capacity, Generation, Investment Trends, Regulations and Top Key Company Profiles | Scrutinized in New Research.
2. Revenue growth of the AI In Drug Discovery Market over the assessment period.
3. Rival Information about Future Scenarios and Main Business Opportunity Analysis.
4. Recent collaborations, mergers, acquisitions, and partnerships.
5. Value chain analysis of prominent players in the AI In Drug Discovery Market.

Key Players Detail:

IBM Watson
NVIDIA Corporation
Exscientia
GNS Healthcare
Aria Pharmaceuticals, Inc.
Alphabet (DeepMind)
Benevolent AI
BioSymetrics
Insilico Medicine
Envisagenics

The AI In Drug Discovery Market Research Report offers a thorough analysis that includes the current situation and potential future growth. This report offers an in-depth look at several key research industry statistics as well as a trend for the future, which aids different sectors in identifying goods and boosting profitability and revenue growth.

Segment Analysis

By Therapeutic Area

Oncology
Infectious Diseases
Neurology
Metabolic

By Technology

Machine Learning
Natural Language Processing
Context-Aware Processing

This report also splits the market by region:

North America
- US
- Canada
- Mexico
Europe
- Germany
- Uk
- France
- Italy
- Spain
- Russia
- Rest of Europe
Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Rest of Asia Pacific
South America
- Brazil
- Argentina
- Rest of South America
Middle East & Africa
- UAE
- Saudi Arabia
- Qatar
- South Africa
- Rest of Middle East & Africa

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The scope of the report is to provide a 360-degree view of the market by assessing the entire value chain and analyzing the key AI In Drug Discovery market trends from 2021 to 2032 underlying in specific geographies. Qualitative and quantitative aspects are interlinked to provide rationales on market numbers, CAGR, and forecasts.

Key highlights of the AI In Drug Discovery market report:

Regional demand estimation and forecast
Before commodity price fluctuations
Technology update analysis
Raw material procurement strategy
Competition analysis
Product portfolio matrix
Supplier Management

In September 2023, Exscientia entered into a collaboration with Merck KGaA focused on the discovery of novel small molecule drug candidates across oncology, neuroinflammation, and immunology. The multi-year collaboration will utilize Exscientia’s AI-driven precision drug design and discovery capabilities while leveraging Merck KGaA’s disease expertise in oncology and neuroinflammation, clinical development capabilities, and footprint.

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What's covered in the report?

1. Overview of the AI In Drug Discovery market.

2. The current and forecasted regional (North America, Europe, Asia-Pacific, Latin America, the Middle East and Africa) market size data for the AI In Drug Discovery market, based on segement.

3. AI In Drug Discovery Market trends.

4. AI In Drug Discovery Market drivers.

5. Analysis of major company profiles.

Why buy?

1. To assess the viability of the business, understand the demand for the AI In Drug Discovery market.

2. Identify the established and emerging markets where AI In Drug Discovery products are used.

3. Determine the best location for the product and develop a product market strategy based on the position in the value chain.

4. Identify the areas of weakness and fill them.

5. Create strategies for each of the categories based on the economic and industrial conditions.

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