Europe Artificial Intelligence (AI) in Drug DiscoveryMarket Global Industry Size, Share, Demand, Growth Analysis and Forecast By 2029
نشر بتاريخ 2023-10-04 12:13:17
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Being a proficient and all-inclusive Europe Artificial Intelligence (AI) in Drug Discovery Market report puts a light on primary and secondary drivers, market share, leading segments, possible sales volume, and geographical analysis. This market research report is a significant source of information about the industry, important facts and figures, expert opinions, and the newest developments across the globe. This report has reviews about key players in the market, major collaborations, merger and acquisitions along with trending innovation and business policies.
Furthermore, the world Europe Artificial Intelligence (AI) in Drug Discovery Market report deeply analyses the potential of the market with respect to current state of affairs and the future prospects by considering all aspects of Proprietary HMI (Human Machine Interface) Software Market industry. Not to mention, in this competitive market place, market research report has a very central role to play by offering important and consequential market insights for the business. The market drivers and restraints have been explained using SWOT analysis. With an absolute devotion and commitment, Europe Europe Artificial Intelligence (AI) in Drug Discovery market report has been provided with the best reasonable service and recommendations which can be relied upon confidently.
Data Bridge Market Research analyzes that the Europe Artificial Intelligence (AI) in drug discovery market is expected to reach the value of USD 4,891.95 million by 2029, at a CAGR of 52.0% during the forecast period. Software accounts for the largest technology segment in the market due to rapid developments in technological advancements to commercialize the use of AI in drug discovery market. This market report also covers pricing analysis, patent analysis, and technological advancements in depth.
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Market Overview:
AI has caught the attention and minds of medical technology practitioners in the past few years, as several companies and major research laboratories have worked to perfect these technologies for clinical use. The first commercialized demonstrations of how AI (also known as Deep Learning (DL), Machine Learning (ML), or Artificial Neural Networks (ANNs)) could assist clinicians are now available. These systems could lead to a paradigm shift in clinician workflow, and increase productivity while simultaneously enhancing treatment and patient throughput. AI for drug discovery is a technology that uses machines to simulate human intelligence to solve complicated challenges in the drug development procedure. The adoption of AI solutions in the clinical trial process eliminates possible obstacles, reduces clinical trial cycle time, and increases the productivity and accuracy of the clinical trial process. Therefore, the adoption of these advanced AI solutions in drug discovery processes is gaining popularity amongst life science industry stakeholders. In the pharmaceutical sector, it aids in the discovery of novel compounds, therapeutic target identification, and the development of customized medications. AI platforms used for drug discovery can prove to be a feasible option for deriving insights into the discovery of drugs to treat and minimize the severity of various chronic diseases.
Some of the key players operating in the market are NVIDIA Corporation, IBM Corp., Atomwise Inc., Microsoft, Benevolent AI, Aria Pharmaceuticals, Inc., DEEP GENOMICS, Exscientia, Cloud, Insilico Medicine, Cyclica, NuMedii, Inc., Envisagenics, Owkin Inc., BERG LLC, Schrödinger, Inc., XtalPi Inc. and BIOAGE Inc. among others..
Europe Artificial Intelligence (AI) in Drug Discovery Market Scope
Europe Artificial Intelligence (AI) in drug discovery market is segmented into application, technology, drug type, offering, indication, and end use. The growth among segments helps you analyze niche pockets of growth and strategies to approach the market and determine your core application areas and the difference in your target markets.
APPLICATION
Novel Drug Candidates
Drug Optimization and Repurposing Preclinical Testing and Approval
Drug Monitoring
Finding New Diseases Associated Targets and Pathways
Understanding Disease Mechanisms
Aggregating and Synthesizing Information
Formation & Qualification of Hypotheses
De Novo Drug Design
Finding Drug Targets of an Old Drug
Others
Based on application, the market is segmented into novel drug candidates, drug optimization and repurposing preclinical testing and approval, drug monitoring, finding new diseases associated targets and pathways, understanding disease mechanisms, aggregating and synthesizing information, formation & qualification of hypotheses, de novo drug design, finding drug targets of an old drug, and others.
TECHNOLOGY
Machine Learning (ML)
Deep Learning (DL)
Natural Language Processing (NLP)
Others
Based on technology, the market is segmented into Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and others.
DRUG TYPE
Small Molecule
Large Molecule
Based on drug type, the market is segmented into small molecule and large molecule.
OFFERING
Software
Services
Based on offering, the market is segmented into software and services.
INDICATION
Immuno-Oncology
Neurodegenerative Diseases
Cardiovascular Diseases
Metabolic Diseases
Others
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TABLE OF CONTENTS
Part 01: Executive Summary
Part 02: Scope of the Report
Part 03: Research Methodology
Part 04: Market Landscape
Part 05: Pipeline Analysis
Part 06: Market Sizing
Part 07: Five Forces Analysis
Part 08: Market Segmentation
Part 09: Customer Landscape
Part 10: Regional Landscape
Part 11: Decision Framework
Part 12: Drivers and Challenges
Part 13: Market Trends
Part 14: Vendor Landscape
Part 15: Vendor Analysis
Part 16: Appendix
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