Artificial Intelligence in Drug Discovery Market Research Report Forecast to 2030

The Artificial Intelligence in Drug Discovery Market is anticipated to register a substantial CAGR of 29.83% during the forecast period. The increasing reception of simulated intelligence in drug discovery, rising key initiatives for man-made intelligence in drug discovery, and the increasing number of man-made intelligence-powered drug discovery new companies are driving business sector development.

The reception of simulated intelligence in drug discovery is rising among industries, including drug and biotechnology organizations. This is essentially owing to the way that artificial intelligence offers progressed benefits to discovering drug particles and paces up the drug discovery process. Further, artificial intelligence gives significant insights to work on the designing, optimizing, and synthesizing of drugs. There are a few factors that are increasing the reception of man-made intelligence for drug discovery. The absolute most predominant ones include the rising incidences of ongoing illnesses and accuracy medicine, owing to the emerging way to deal with the counteraction and treatment of sicknesses. Besides, a few market members are increasing the accuracy of their drug portfolios, a cycle that has been seen to exhibit an increase in the reception of man-made intelligence advancements.

Market Segmentation

Based on product and service Artificial Intelligence in Drug Discovery, is classified into software and services. Based on a molecule type the market is divided into large molecules and small molecules. The Market of Artificial Intelligence in Drug Discovery based on technology is divided into machine learning, deep learning, and others.

Based on an indication the market is classified into immuno-oncology, neurodegenerative diseases, cardiovascular diseases, metabolic diseases, and others. Based on an application the market is categorized into target identification, candidate screening, de novo drug designing, drug optimization and repurposing, and preclinical testing.

Regional Insights

The North American artificial intelligence in the drug discovery market represented the biggest piece of the pie in 2022. This is because of the increasing incidences of ongoing illnesses, many leading new companies, and increasing drug Research and development investments in the region.

Europe's artificial intelligence in the drug discovery market represents the second-biggest piece of the pie because of the rising pervasiveness of uncommon illnesses across Europe and increasing the demand for a simulated intelligence-driven stage for drug discovery. Moreover, Germany's market of artificial intelligence

The Asia-Pacific artificial intelligence in drug discovery market is supposed to develop at a huge offer from 2023 to 2030. This is because of the rising weight of sickness and the tremendous number of biopharmaceutical industries that are adopting computer-based intelligence abilities in the Asia-Pacific region.

The rest of the World is fragmented into the Center East, Africa, and Latin America. Artificial intelligence in the drug discovery market in the previously mentioned regions is probably going to observe development because of the increasing demand for drugs because of the rising incidences of persistent and infectious illnesses.

Major Players

Key Companies in the Artificial Intelligence in Drug Discovery Market include IBM (US), Alphabet Inc (US), Atomwise Inc (US), Deep Genomics (Canada), Cloud Pharmaceuticals, Inc (US), Microsoft corporation (US), Insilico Medicine (China), Cyclica (Canada), BenevolentAI (UK), and Exscientia (UK).

Product Code: MRFR/Pharma/7918-CR

TABLE OF CONTENTS

1 EXECUTIVE SUMMARY

1.1 OVERVIEW
- 1.1.1 MARKET SYNOPSIS

2 MARKET INTRODUCTION

2.1 DEFINITION
2.2 SCOPE OF THE STUDY
2.3 RESEARCH OBJECTIVE
2.4 MARKET STRUCTURE
2.5 LIST OF ASSUMPTIONS

3 RESEARCH METHODOLOGY

3.1 OVERVIEW
3.2 DATA MINING
3.3 SECONDARY RESEARCH
3.4 PRIMARY RESEARCH
- 3.4.1 PRIMARY INTERVIEWS AND INFORMATION GATHERING PROCESS
- 3.4.2 BREAKDOWN OF PRIMARY RESPONDENTS
3.5 FORECASTING TECHNIQUES
3.6 RESEARCH METHODOLOGY FOR MARKET SIZE ESTIMATION
- 3.6.1 BOTTOM-UP APPROACH
- 3.6.2 TOP-DOWN APPROACH
3.7 DATA TRIANGULATION
3.8 VALIDATION

4 MARKET DYNAMICS

4.1 OVERVIEW
4.2 DRIVERS
- 4.2.1 INCREASING ADOPTION OF AI IN DRUG DISCOVERY
- 4.2.2 RISING STRATEGIC INITIATIVES FOR AI IN DRUG DISCOVERY
- 4.2.3 INCREASING NUMBER OF AI-POWERED DRUG DISCOVERY START-UPS
4.3 RESTRAINTS
- 4.3.1 SHORTAGE OF AI WORKFORCE
4.4 OPPORTUNITIES
- 4.4.1 EMERGING MARKETS

5 MARKET FACTOR ANALYSIS

5.1 VALUE CHAIN ANALYSIS
- 5.1.1 R&D
- 5.1.2 MANUFACTURING
- 5.1.3 DISTRIBUTION & SALES
- 5.1.4 POST-SALES MONITORING
5.2 PORTER'S FIVE FORCES MODEL
- 5.2.1 THREAT OF NEW ENTRANTS
- 5.2.2 BARGAINING POWER OF SUPPLIERS
- 5.2.3 THREAT OF SUBSTITUTES
- 5.2.4 BARGAINING POWER OF BUYERS
- 5.2.5 INTENSITY OF RIVALRY
5.3 IMPACT OF COVID-19 ON THE GLOBAL AI IN DRUG DISCOVERY
- 5.3.1 IMPACT ON SUPPLY CHAIN
- 5.3.2 IMPACT ON SERVICE DEMAND
- 5.3.3 IMPACT ON MARKET PLAYERS

6 GLOBAL AI IN DRUG DISCOVERY MARKET, BY PRODUCT AND SERVICE

6.1 OVERVIEW
6.2 SOFTWARE
6.3 SERVICES

7 GLOBAL AI IN DRUG DISCOVERY MARKET, BY MOLECULE TYPE

7.1 OVERVIEW
7.2 LARGE MOLECULE
7.3 SMALL MOLECULE

8 GLOBAL AI IN DRUG DISCOVERY MARKET, BY TECHNOLOGY

8.1 OVERVIEW
8.2 MACHINE LEARNING
8.3 DEEP LEARNING
8.4 OTHERS

9 GLOBAL AI IN DRUG DISCOVERY MARKET, BY INDICATION

9.1 OVERVIEW
9.2 IMMUNO-ONCOLOGY
9.3 NEURODEGENERATIVE DISEASES
9.4 CARDIOVASCULAR DISEASES
9.5 METABOLIC DISEASES
9.6 OTHERS

10 GLOBAL AI IN DRUG DISCOVERY MARKET, BY APPLICATION

10.1 OVERVIEW
10.2 TARGET IDENTIFICATION
10.3 CANDIDATE SCREENING
10.4 DE NOVO DRUG DESIGNING
10.5 DRUG OPTIMIZATION AND REPURPOSING
10.6 PRECLINICAL TESTING

11 GLOBAL AI IN DRUG DISCOVERY MARKET, BY REGION

11.1 OVERVIEW
11.2 NORTH AMERICA
- 11.2.1 US
- 11.2.2 CANADA
11.3 EUROPE
- 11.3.1 GERMANY
- 11.3.2 FRANCE
- 11.3.3 UK
- 11.3.4 ITALY
- 11.3.5 SPAIN
- 11.3.6 REST OF EUROPE
11.4 ASIA-PACIFIC
- 11.4.1 CHINA
- 11.4.2 JAPAN
- 11.4.3 INDIA
- 11.4.4 AUSTRALIA
- 11.4.5 SOUTH KOREA
- 11.4.6 REST OF ASIA-PACIFIC
11.5 REST OF THE WORLD
- 11.5.1 MIDDLE EAST
- 11.5.2 AFRICA
- 11.5.3 LATIN AMERICA

12 COMPETITIVE LANDSCAPE

12.1 OVERVIEW
12.2 COMPETITIVE BENCHMARKING
12.3 MAJOR GROWTH STRATEGY IN THE GLOBAL AI IN DRUG DISCOVERY MARKET
12.4 THE LEADING PLAYER IN TERMS OF THE NUMBER OF DEVELOPMENTS IN THE GLOBAL AI IN DRUG DISCOVERY MARKET
12.5 KEY DEVELOPMENT ANALYSIS
12.6 KEY DEVELOPMENTS & GROWTH STRATEGIES
- 12.6.1 SERVICE/COMPANY LAUNCH
- 12.6.2 MERGER/ACQUISITION
- 12.6.3 PARTNERSHIP/COLLABORATION/AGREEMENT

13 COMPANY PROFILES

13.1 IBM
- 13.1.1 COMPANY OVERVIEW
- 13.1.2 FINANCIAL OVERVIEW
- 13.1.3 SOFTWARE/SERVICES OFFERED
- 13.1.4 KEY DEVELOPMENTS
- 13.1.5 SWOT ANALYSIS
- 13.1.6 KEY STRATEGIES
13.2 ALPHABET INC.
- 13.2.1 COMPANY OVERVIEW
- 13.2.2 FINANCIAL OVERVIEW
- 13.2.3 SOFTWARE/SERVICES OFFERED
- 13.2.4 KEY DEVELOPMENTS
- 13.2.5 SWOT ANALYSIS
- 13.2.6 KEY STRATEGIES
13.3 ATOMWISE INC.
- 13.3.1 COMPANY OVERVIEW
- 13.3.2 FINANCIAL OVERVIEW
- 13.3.3 SOFTWARE/SERVICES OFFERED
- 13.3.4 KEY DEVELOPMENTS
- 13.3.5 SWOT ANALYSIS
- 13.3.6 KEY STRATEGIES
13.4 DEEP GENOMICS
- 13.4.1 COMPANY OVERVIEW
- 13.4.2 FINANCIAL OVERVIEW
- 13.4.3 SOFTWARE/SERVICES OFFERED
- 13.4.4 KEY DEVELOPMENTS
- 13.4.5 KEY STRATEGIES
13.5 CLOUD PHARMACEUTICALS, INC.
- 13.5.1 COMPANY OVERVIEW
- 13.5.2 FINANCIAL OVERVIEW
- 13.5.3 SOFTWARE/SERVICES OFFERED
- 13.5.4 KEY DEVELOPMENTS
- 13.5.5 KEY STRATEGIES
13.6 MICROSOFT CORPORATION
- 13.6.1 COMPANY OVERVIEW
- 13.6.2 FINANCIAL OVERVIEW
- 13.6.3 SERVICES OFFERED
- 13.6.4 KEY DEVELOPMENTS
- 13.6.5 SWOT ANALYSIS
- 13.6.6 KEY STRATEGIES
13.7 INSILICO MEDICINE
- 13.7.1 COMPANY OVERVIEW
- 13.7.2 FINANCIAL OVERVIEW
- 13.7.3 SERVICES OFFERED
- 13.7.4 KEY DEVELOPMENTS
- 13.7.5 KEY STRATEGIES
13.8 CYCLICA
- 13.8.1 COMPANY OVERVIEW
- 13.8.2 FINANCIAL OVERVIEW
- 13.8.3 SERVICES OFFERED
- 13.8.4 KEY DEVELOPMENTS
- 13.8.5 KEY STRATEGIES
13.9 BENEVOLENTAI
- 13.9.1 COMPANY OVERVIEW
- 13.9.2 FINANCIAL OVERVIEW
- 13.9.3 SERVICES OFFERED
- 13.9.4 KEY DEVELOPMENTS
- 13.9.5 SWOT ANALYSIS
- 13.9.6 KEY STRATEGIES
13.10 EXSCIENTIA
- 13.10.1 COMPANY OVERVIEW
- 13.10.2 FINANCIAL OVERVIEW
- 13.10.3 SOFTWARES OFFERED
- 13.10.4 KEY DEVELOPMENTS
- 13.10.5 KEY STRATEGIES

14 APPENDIX

14.1 REFERENCES
14.2 RELATED REPORTS