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Artificial Intelligence (AI) In Drug Discovery Global Market Report 2021 Featuring IBM, Microsoft, Atomwise, Deep Genomics, Insilico Medicine, Benevolent AI, Exscientia, Cyclica, and BIOAGE – ResearchAndMarkets.com

DUBLIN–(BUSINESS WIRE)–The “Artificial Intelligence (AI) In Drug Discovery Global Market Report 2021: COVID-19 Growth and Change to 2030” report has been added to ResearchAndMarkets.com’s offering.

The global artificial intelligence (AI) in drug discovery market is expected to grow from $0.36 billion in 2020 to $0.47 billion in 2021 at a compound annual growth rate (CAGR) of 30.6%. The market is expected to reach $1.69 billion in 2025 at a CAGR of 38%.

Major players in the artificial intelligence (AI) in drug discovery market are IBM Corporation, Microsoft, Atomwise Inc., Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, Benevolent AI, Exscientia, Cyclica, and BIOAGE.

The artificial intelligence (AI) in drug discovery market consists of sales of AI for drug discovery and related services. Artificial Intelligence (AI) for drug discovery is a technology that uses a simulation of human intelligence process by machines to tackle complex problems in the drug discovery process. It helps to find new molecules to identify drug targets and develop personalized medicines in the pharmaceutical industry.

The artificial intelligence (AI) in drug discovery market covered in this report is segmented by technology into deep learning, machine learning. It is also segmented by drug type into small molecule, large molecules; by therapeutic type into metabolic disease, cardiovascular disease, oncology, neurodegenerative diseases, others and by end-users into pharmaceutical companies, biopharmaceutical companies, academic and research institutes, others.

The shortage of skilled professionals is expected to hamper the AI in drug discovery market. The employees have to re-train or learn new skill sets to work efficiently on the complex AI machines to get the desired results for the drug. The shortage of skills acts as a major hindrance to drug discovery through AI, discouraging companies to adopt AI-based machines for drug discovery.

According to The Pistoia Alliance, a global non-profit organization that works to encourage innovation in life sciences R&D cited that 44% of respondents agree that lack of skills was the biggest barrier to the adoption of AI and machine learning (ML) in 2019.

In July 2020, Curi Bio, a leading developer of human iPSC-based platforms for drug discovery, acquired Dana Solutions for an undisclosed amount. This acquisition will give Curi Bio access to Dana’s AI/ML platforms for modelling cell and tissue phenotype, automated platform for contractility analysis of beating cardiomyocyte and platform for predictive safety pharmacology. Dana Solutions is a leading AI solutions provider for the life sciences industry.

The rise in demand for a reduction in the overall time taken for the drug discovery process is a key driver propelling the growth of the artificial intelligence (AI) in drug discovery market. Traditionally, it takes three to five years for animal models to identify and optimize molecules before they are evaluated in humans whereas start-ups based on AI have been identifying and designing new drugs in a matter of few days or months. The reduction in overall time taken for the drug discovery process drives the artificial intelligence (AI) in drug discovery market’s growth.

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 September 2019, Atomwise Inc. and Jiangsu Hansoh Pharmaceutical Group Co. Ltd announced the collaboration of $1.5 billion to design and discover the potential drug candidates for up to 11 undisclosed target proteins in cancer and other therapeutic areas.

The collaboration is expected to combine Atomwise Inc’s AI technology, protein structure expertise, and medicinal chemistry with Jiangsu Hansoh Pharmaceutical Group Co. Ltd’s manufacturing, research & development, and commercial capabilities in order to improve and accelerate clinical development and drug discovery process.

Key Topics Covered:

1. Executive Summary

2. Artificial Intelligence (AI) In Drug Discovery Market Characteristics

3. Artificial Intelligence (AI) In Drug Discovery Market Trends and Strategies

4. Impact Of COVID-19 On Artificial Intelligence (AI) In Drug Discovery

5. Artificial Intelligence (AI) In Drug Discovery Market Size and Growth

5.1. Global Artificial Intelligence (AI) In Drug Discovery Historic Market, 2015-2020, $ Billion

5.1.1. Drivers Of the Market

5.1.2. Restraints On the Market

5.2. Global Artificial Intelligence (AI) In Drug Discovery Forecast Market, 2020-2025F, 2030F, $ Billion

5.2.1. Drivers Of the Market

5.2.2. Restraints On the Market

6. Artificial Intelligence (AI) In Drug Discovery Market Segmentation

6.1. Global Artificial Intelligence (AI) In Drug Discovery Market, Segmentation by Technology, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

6.2. Global Artificial Intelligence (AI) In Drug Discovery Market, Segmentation by Drug Type, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

6.3. Global Artificial Intelligence (AI) In Drug Discovery Market, Segmentation by therapeutic Type, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

6.4. Global Artificial Intelligence (AI) In Drug Discovery Market, Segmentation by End-Users, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

7. Artificial Intelligence (AI) In Drug Discovery Market Regional and Country Analysis

7.1. Global Artificial Intelligence (AI) In Drug Discovery Market, Split by Region, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

7.2. Global Artificial Intelligence (AI) In Drug Discovery Market, Split by Country, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

Companies Mentioned

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