eHealth Size, Share, Growth, Demand, Segments and Forecast by 2029
Being a proficient and all-inclusive North
America 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 North America 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
North America 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 North America Artificial Intelligence (AI) in drug discovery
market is expected to reach the value of USD 14,913.08 million by 2029, at a
CAGR of 54.9% 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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Sample PDF Copy of this Report to understand structure of the complete report@ https://www.databridgemarketresearch.com/request-a-sample/?dbmr=north-america-artificial-intelligence-ai-in-drug-discovery-market
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.
North America
Artificial Intelligence (AI) in Drug Discovery Market Scope
North America 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.
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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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