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Report Scope & Overview:

Artificial intelligence in drug discovery market is projected to arrive at USD 11.15 billion by 2030 from USD 722.3 million of every 2022, at a CAGR of 40.8% during the gauge time frame 2023-2030. The development of the man-made brainpower in (AI)drug discovery market is fundamentally determined by elements like the developing number of cross-industry coordinated efforts and associations, the rising need to control drug disclosure and improvement costs and lessen the general time taken in this interaction, the rising reception of cloud-based applications and administrations, and the approaching patent expiry of blockbuster drugs.

Artificial Intelligence in Drug Discovery Market Revenue Analysis

Then again, an absence of informational collections in the field of medication disclosure and the deficient accessibility of gifted work are a portion of the elements testing the development of the market. Man-made reasoning has huge applications in the medication revelation field as it helps track sicknesses, make illness fixes and foresee which creature infections seem to transform. Man-made consciousness has been known to upgrade R&D in drug disclosure, which has assisted analysts with finding constant illness medicines. Drug disclosure and advancement in the fields of medication, pharmacology, and biotechnology are processes for the creation, plan, and acquisition of a medication through distinguishing a natural objective, like catalyst protein, quality, or receptor. Beforehand, the medications were found by distinguishing the dynamic fixing regular medicines. Subsequently, drug disclosure is the initial phase during the time spent distinguishing possible novel medications and their restorative reason. New standards for drugs are estimated in light of their bioavailability, adequacy, power, and poisonousness.

Impact of COVID on artificial intelligence for drug discovery
It is assessed that computerized reasoning for Artificial intelligence in drug discovery market  would show a critical market development because of the Covid-19 pandemic, inferable from ascending in the reception of AI to find and foster medications for treatment of COVID-19. For example, in June 2020 Repurpose.AI teamed up with Scripps Research to foster COVID-19 therapeutics with an emphasis on drug reusing. Man-made reasoning based drug screening strategies will hypothetically assist with making sense of significant pieces of the infection, (for example, protein structure) to survey how the elements of the infection can assume a fundamental part in a drug plan and speed up antibody advancements to battle COVID-19. Besides, Artificial knowledge can help drug disclosure and advancement process by rapidly recognizing drugs having viability against COVID-19. This overcomes any issues between a number of reused drugs (involving existing medications for different illnesses), clinical testing, and the last medication approval process.

The product section represented the biggest portion of the AI in the drug discovery market, by type, in 2021

In view of offering, the man-made brainpower in the medication disclosure market is sectioned into programming and administration. In 2020, the product fragment represented a bigger portion of the overall industry during the conjecture time frame. Factors, for example, less expense and time to advertise the medication, low disappointment rate, an enormous number of programming engineers for drug disclosure, and solid interest for the product among large pharma and biotech organizations and examination foundations are driving the development of the product fragment.

The neurodegenerative illnesses section is supposed to develop at the most elevated CAGR during the gauge time frame.

In view of the application, the computerized reasoning in the medication disclosure market is divided into neurodegenerative sicknesses, immuno-oncology, cardiovascular illness, metabolic infections, and different applications. Neurodegenerative illnesses structure the quickest developing application fragment, with a most noteworthy CAGR during the estimated time frame. The capacity of AI to find drugs for complex circumstances and the accentuation of market players on giving AI-based stages to neurological illnesses are liable for the quick development of this application portion.

The drug and biotechnology organizations portion represented the biggest portion of the AI in the drug discovery market in 2021

In light of end-client, the AI in the drug delivery market is sectioned into drug and biotechnology organizations, contract research associations, examination focuses, and scholarly, and government establishments. In 2018, the drug and biotechnology organizations section represented the biggest offer in the AI in the medication disclosure market.

North America represented the biggest portion of the AI in the drug discovery market in 2021

The worldwide AI in the medication disclosure market is sectioned into four significant areas, specifically, North America, Europe, APAC, and the Rest of the World. In 2022, North America was the biggest and the quickest developing provincial market for AI in drug revelation. North America, which involves the US, Canada, and Mexico, frames the biggest market for AI in drug disclosure. These nations have been early adopters of AI innovation in drug disclosure and advancement. In the North American market, the US is a significant supporter. Likewise, unmistakable AI innovation suppliers, like IBM, Google, Microsoft, NVIDIA, and Intel, are settled in the US; their solid presence is a critical supporter of market development. Different drivers incorporate the deep-rooted drug industry, high spotlight on R&D and significant speculation, and the presence of worldwide driving drug organizations. These are a portion of the central point answerable for the huge offer and high development pace of this market.

Key players in the AI in the drug discovery market

The AI in the medication revelation market is divided in nature, with an enormous number of players, including level 1, mid-level organizations, and startup firms, going after portions of the overall industry. The conspicuous players in the worldwide AI in drug revelation market incorporate IBM Corporation, Microsoft, and Google, NVIDIA Corporation, Atomwise, Inc., Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, BenevolentAI, Exscientia, Cyclica, BIOAGE, Numerate, NuMedii, Envisagenics, twoXAR, OWKIN, Inc., XtalPi, Verge Genomics, and BERG LLC.

KEY MARKET SEGMENTS:

By Component

  • Software

  • Services

By Technology

  • Machine Learning

  • Deep Learning

  • Supervised Learning

  • Reinforcement Learning

  • Unsupervised Learning

  • Others Technologies

By End-Use

  • Pharmaceutical & Biotechnology Companies

  • Contract Research Organizations

  • Research Centres

  • Academic & Government Institutes

By Application

  • Excavation and mining

  • Immuno-Oncology

  • Neurodegenerative Diseases

  • Cardiovascular Diseases

  • Metabolic Diseases

  • Other Applications 

Artificial Intelligence in Drug Discovery Market Segmentation Analysis

REGIONAL ANALYSIS:

North America held the major man-made consciousness for drug disclosure and improvement portion of the overall industry in 2021 and is supposed to proceed with its strength during the estimated time frame, attributable to solid economies like the U.S. furthermore, Canada; high reception pace of AI innovations because of an enormous number of speculations to support the medication disclosure industry; and a huge number of cross-industry joint efforts and associations, which significantly fuel the market development. Be that as it may, Asia-Pacific is supposed to develop at the most noteworthy CAGR during the estimated time frame, inferable from ascending in the reception of cutting edge AI advancements and development in the focal point of central parts on expanding their presence in arising Asian nations.

Exhaustive cutthroat examination and profiles of the major man-made consciousness for drug revelation and improvement market players like Alphabet Inc., Atomwise, Inc., Benevolent AI, Cloud Pharmaceutical, Deep Genomics, Exscientia, IBM Corporation, Insilico Medicine Inc., Microsoft Corporation, and Nvidia Corporation are given in this report.   

REGIONAL COVERAGE:

North America

  • USA

  • Canada

  • Mexico

Europe

  • Germany

  • UK

  • France

  • Italy

  • Spain

  • The Netherlands

  • Rest of Europe

Asia-Pacific

  • Japan

  • south Korea

  • China

  • India

  • Australia

  • Rest of Asia-Pacific

The Middle East & Africa

  • Israel

  • UAE

  • South Africa

  • Rest of Middle East & Africa

Latin America

  • Brazil

  • Argentina

  • Rest of Latin America

Artificial Intelligence in Drug Discovery Market Report Scope:
Report Attributes Details
Market Size in 2022 US$ 722.3 Million
Market Size by 2030 US$ 11.15 Billion
CAGR CAGR of 40.8% From 2023 to 2030
Base Year 2022
Forecast Period 2023-2030
Historical Data 2020-2021
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • By Components (software and service)
• By Technology (Machine learning, deep learning, Supervised Learning, Reinforcement Learning, Unsupervised Learning, Others)
• By Application
• By End Use
Regional Analysis/Coverage North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, Netherlands,
Rest of Europe), Asia-Pacific (Japan, South Korea,
China, India, Australia, Rest of Asia-Pacific), The
Middle East & Africa (Israel, UAE, South Africa,
Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America)
Company Profiles IBM Corporation, Microsoft, and Google, NVIDIA Corporation, Atomwise, Inc., Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, BenevolentAI, Exscientia, Cyclica, BIOAGE, Numerate, NuMedii, Envisagenics, twoXAR, OWKIN, Inc., XtalPi, Verge Genomics, and BERG LLC.

Frequently Asked Questions

Ans. The Global Artificial intelligence in drug discovery market is estimated to reach $11.15 billion by 2030.

Ans. Manufacturer and service provider, research institutes, university and private libraries, suppliers and distributers.

Ans. Neurodegenerative diseases, immuno-oncology, cardiovascular diseases, and metabolic diseases form AI in the drug discovery industry. Due to the growing demand for effective cancer treatment, the immuno-oncology segment holds the highest share of AI in the drug discovery market.

Ans. North America has the largest market share in AI in Drug Discovery Market.

Ans. The drivers of AI in Drug Discovery Market include Increasing Adoption of Artificial Intelligence in Healthcare Sector and growing Investment in Healthcare Sector

Table of Contents

 

1. Introduction

1.1 Market Definition

1.2 Scope

1.3 Research Assumptions

 

2. Research Methodology

 

3. Market Dynamics

3.1 Drivers

3.2 Restraints

3.3 Opportunities

3.4 Challenges

 

4. Impact Analysis

4.1 COVID-19 Impact Analysis

4.2 Impact of Ukraine- Russia war

4.3 Impact of ongoing Recession

4.3.1 Introduction

4.3.2 Impact on major economies

4.3.2.1 US

4.3.2.2 Canada

4.3.2.3 Germany

4.3.2.4 France

4.3.2.5 United Kingdom

4.3.2.6 China

4.3.2.7 Japan

4.3.2.8 South Korea

4.3.2.9 Rest of the World

 

5. Value Chain Analysis

 

6. Porter’s 5 forces model

 

7.  PEST Analysis

 

8. Artificial Intelligence in Drug Discovery Market Segmentation,by Component

8.1Software

8.2Services

 

9. Artificial Intelligence in Drug Discovery Market Segmentation, by  technology

9.1 Machine Learning

9.2 Deep Learning

9.3 Supervised Learning

9.4 Reinforcement Learning

9.5 Unsupervised Learning

9.7 Others Technologies

 

10 .Artificial Intelligence in Drug Discovery Market Segmentation, By end use

10.1 Pharmaceutical & Biotechnology Companies

10.2 Contract Research Organizations

10.3 Research Centres

10.4 Academic & Government Institutes

 

11. Artificial Intelligence in Drug Discovery Market Segmentation, By application

11.1Excavation and mining

11.2 Immuno-Oncology

11.3 Neurodegenerative Diseases

11.4 Cardiovascular Diseases

11.5 Metabolic Diseases

11.6 Others

 

12. Regional Analysis

12.1 Introduction

12.2 North America

12.2.1 USA

12.2.2     Canada

12.2.3     Mexico

12.3        Europe

12.3.1     Germany

12.3.2     UK

12.3.3     France

12.3.4     Italy

12.3.5     Spain

12.3.6     The Netherlands

12.3.7     Rest of Europe

12.4        Asia-Pacific

12.4.1     Japan

12.4.2     South Korea

12.4.3     China

12.4.4     India

12.4.5     Australia

12.4.6     Rest of Asia-Pacific

12.5        The Middle East & Africa

12.5.1     Israel

12.5.2     UAE

12.5.3     South Africa

12.5.4     Rest

12.6        Latin America

12.6.1     Brazil

12.6.2     Argentina

12.6.3     Rest of Latin America

 

13. Company Profiles

13.1 IBM

13.1.1 Financial

13.1.2 Products/ Services Offered

13.1.3 SWOT Analysis

13.1.4 The SNS view

13.2 AB VOLVO

13.3 CATTERPILLAR INC.

13.4 CNH INDUSTRIAL N.V

13.5 DEERE AND COMPANY

13.6 DOOSAN INFRACOE CO.LTD

13.7 J C BAMFORD EXCAVATORS. LTD.

13.8 KOMATSU LTD.

13.9 Liebherr-international AG

13.10 XCMG GROUP

 

14. Competitive Landscape

14.1 Competitive Benchmarking

14.2 Market Share analysis

14.3 Recent Developments

 

15. Conclusion

 

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

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The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data.  This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.

We at SNS Insider have divided Primary Research into 2 parts.

Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.

This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.

Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.

Step 3: Data Bank Validation

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Data Bank Validation

Step 4: QA/QC Process

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