Market Overview

The Worldwide AI in Drug Discovery Industry is Expected to Achieve a CAGR of 43% Between 2020 and 2026 -


The "AI in Drug Discovery Market by Component, Technology, by Application, by End User, by Geography - Global Opportunity Analysis and Industry Forecast up to 2026" report has been added to's offering.

Artificial intelligence is the simulation of human intelligence in machines that are designed to think like humans and copy their actions. This gives the potential to transform the pharmaceutical industry as well. Many pharma competitors are now investing in this technology at some level.

The market value of AI in Drug Discovery recorded in 2020 is $343.78 million and predictions are made on its future growth at a CAGR of 43.24%.

There are four major factors which are the result of its increasing growth:

  • Requisite control on Cost and Time of Drug Discovery & Development
  • Demanding requirement of precision medicine
  • Expanding Cross-Industry Collaborations and Partnerships
  • Growing number of troublemakers of AI drug discovery

AI in drug discovery has enlightened the productivity of medical facilities, and on the same page has helped in boosting care facilities. Extensive medical facilities always try to opt for better services and latest technologies with minimum space for mistakes. This technology has fastened the drug construction procedures for cases which need specialized medicinal attention, which subsequently decreases failure risks and also the cost of research & development procedures.

Some of the vital players within the space of AI in Drug Discovery are as follows:

  • IBM Corporation
  • Microsoft Corporation
  • Google Inc.
  • NVIDIA Corporation
  • Pfizer, Merck
  • GSK
  • Novartis
  • AstraZeneca
  • Abbvie
  • Elli Lilly
  • Atomwise, Inc
  • Deep Genomics
  • Cloud Pharmaceuticals
  • Exscientia
  • Cyclica
  • Numerate
  • Envisagenics
  • OWKIN, Inc.
  • Verge Genomics

Another important factor of reducing the drug price has pressured the drug manufacturers to boost the production of AI for the drug discovery market. Efficient working of AI reduced the failure rate of clinical trials and also eradicated the cost of length research and development in drug discovery. Another factor which can bolster the anticipated growth of the Global AI for the drug discovery market is the lack of skilled health care professionals.

Currently, only one out of ten drugs are approved after clinical trials. Mostly because of lack of effectiveness and safety issues. Considering the growing cost of bringing a drug into the market, a minimum of ten percent improvement in the prediction of accuracy can save billions of dollars invested on drug development for AI in Drug Discovery vendors which compensate for both the residential as well as commercial sectors. So, improving the accuracy of predictions on the efficacy and safety of drugs is highly required. With a predicted CAGR of 43.24%, we have a lot of opportunities at our disposal and this report will help in understanding the current market dynamics, changing needs, and innovations that might be needed to make the user experience enriching.

This report would be the foundation for any research on the AI in Drug Discovery, vendor capabilities, SWOT of the vendors and framework for data analysis for further advanced innovation

An insight to the major competitors in the market, their journey and the competitive edge which one should have to beat other players is given

The report contains an understanding of technological innovations and advanced solutions for the AI in Drug Discovery.

Key Topics Covered:

1. Executive Summary

2. Industry Outlook

  • Industry Overview
  • Industry Trends

3. Market Snapshot

  • Market Definition
  • Market Outlook
  • PEST Analysis
  • Porter Five Forces
  • Related Markets

4. Market Characteristics

  • Market Evolution
  • Market Trends and Impact
  • Advantages/Disadvantages of Market
  • Regulatory Impact
  • Market Offerings
  • Market Segmentation

5. Market Dynamics

  • Drivers
  • Restraints
  • Opportunities
  • DRO - Impact Analysis

6. End User: Market Size & Analysis

  • Overview
  • Research Centers and Academic & Government Institutes
  • Pharmaceutical & Biotechnology Companies
  • Contract Research Organizations

7. Application: Market Size & Analysis

  • Overview
  • Cardiovascular Diseases
  • Metabolic Diseases
  • Neurodegenerative Diseases
  • Immuno-oncology
  • Other Applications

8. Technology: Market Size & Analysis

  • Overview
  • Machine Learning
  • Deep Learning
  • Supervised Learning
  • Reinforcement Learning
  • Unsupervised Learning
  • Other Machine Learning Technlogies
  • Others Technologies
  • Offering: Market Size & Analysis
  • Overview
  • Services
  • Software

9. Geography: Market Size & Analysis

  • Overview
  • North America
  • Europe
  • Asia Pacific
  • Rest of the World

10. Competitive Landscape

  • Competitor Comparison Analysis
  • Market Developments
  • Mergers and Acquisitions, Legal, Awards, Partnerships
  • Product Launches and execution

11. Vendor Profiles

12. Companies to Watch

13. Analyst Opinion

14. Annexure

  • Report Scope
  • Market Definitions
  • Research Methodology
  • Data Collation and In-house Estimation
  • Market Triangulation
  • Forecasting
  • Report Assumptions
  • Declarations
  • Stakeholders
  • Abbreviations

For more information about this report visit

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