Global AI in Drug Discovery Market (2023-2032) by Offering, Technology, Use Cases, Applications, End-User, and Regional Analysis, AI and Sustainability Footprints, and Market Share Analysis

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The Global AI in Drug Discovery Market is set to surge from USD xxx in 2023 to a projected USD xxx Bn by 2028, growing at a CAGR of xxx%.

The pharmaceutical industry stands at the precipice of a ground-breaking revolution, driven by the transformative power of Artificial Intelligence (AI). In recent years, AI has become the cornerstone of drug discovery, reshaping traditional research methodologies and propelling innovation to unprecedented heights.

The exponential growth of biological data, encompassing genomes, proteomics, and clinical data, has increased the adoption of AI-driven computational methods. The large volume and complexity of this data necessitate sophisticated algorithms for analysis and interpretation, driving the Global AI in Drug Discovery Market.

Innovative AI-driven solutions are indispensable for uncovering novel therapeutic targets, optimizing lead compounds, and predicting treatment outcomes. As diseases become increasingly intricate, and the demand for personalized medicine intensifies, AI offers solutions to combat illness and enhance patient care.

The integration of AI technologies expedites the discovery of promising drug candidates, significantly reducing research time and costs. By streamlining the drug development pipeline, AI not only enhances efficiency but also paves the way for the rapid introduction of life-saving medications into the market.

Moreover, AI helps repurpose existing drugs for new uses, creating new revenue opportunities and meeting medical needs. This approach speeds up innovation and makes the most of current pharmaceutical assets, optimizing resource use.

However, limitations surrounding the quality and quantity of data, characterized by incompleteness, bias, and heterogeneity, pose a hindrance to the accuracy and reliability of AI models.

Additionally, for smaller enterprises and academic institutions, the exorbitant upfront costs associated with AI implementation present significant barriers to entry. From talent acquisition to infrastructure development and regulatory compliance, the financial burdens associated with AI adoption can hinder market growth.

Segment Analysis

The Global AI in Drug Discovery Market is segmented based on Offering, Technology, Use Cases, Applications, and End-User.

By Technology, the Global AI in Drug Discovery Market is segmented into Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Others. The Deep Learning (DL) segment holds the largest market share in the global AI in drug discovery market. This is due to its unparalleled ability to analyse vast and complex datasets with unprecedented accuracy and efficiency.

DL algorithms, inspired by the structure and function of the human brain, excel at uncovering intricate patterns and relationships within biological data, such as genomic sequences, protein structures, and chemical compounds. This capability is particularly crucial in drug discovery, where researchers grapple with immense amounts of molecular information.

DL techniques empower pharmaceutical and biotechnology companies to expedite the identification and optimization of potential drug candidates, thereby significantly reducing the time and resources required for traditional drug development processes.

Furthermore, DL’s versatility enables its application across various stages of the drug discovery pipeline, from target identification and validation to lead optimization and clinical trial design.

Regional Analysis

The Global Artificial Intelligence (AI) in Drug Discovery market is projected to experience significant regional variations in growth. Americas region is currently the dominant leader, holding the largest market share due to its advanced technological infrastructure, established pharmaceutical companies, and high research and development spending. Europe follows closely behind, driven by government initiatives and a strong presence of leading pharmaceutical and biotechnology players.

Asia Pacific is expected to witness the fastest growth rate in the coming years, fuelled by rising healthcare expenditure, increasing government support for AI adoption, and a large patient population. However, challenges like fragmented healthcare infrastructure and varying regulatory landscapes may hinder its growth in certain regions. Latin America and the Middle East & Africa are expected to exhibit slower growth due to limited resources, lower investment in AI technology, and underdeveloped infrastructure. As these regions address these challenges, they hold potential for future growth in the AI-powered drug discovery market.

List of Companies

The report provides profiles of the key companies, outlining their history, business segments, product overview, and company financials. Some companies from competitive analysis are Atomwise, Inc., Insilico Medicine, Inc., BenevolentAI, Recursion Pharmaceuticals, Numerate Inc. etc

Key Developments

Elsevier and Iktos Partner to Deliver an AI-Driven Synthetic Chemistry Platform for Drug Discovery. – March 2024

Aurigene Pharmaceutical Services, a part of Dr. Reddy’s Laboratories has launched Aurigene.AI, an AI and ML-assisted platform for accelerating drug discovery projects from hit identification to candidate nomination.. – April 2024

Frequently Asked Questions

What Is The Major Global AI in Drug Discovery Market Driver?

  • Increasing Demand for Novel Therapies

  • Cost and Time Efficiency

  • Increasing Collaboration Between Pharmaceutical and AI Companies

What are the restraints of the AI in Drug Discovery Market?

  • Regulatory Hurdles and Concerns Related to the Safety and Efficacy

  • High Initial Setup Costs

Who Are The AI in Drug Discovery Market Players?

Atomwise, Inc., Insilico Medicine, Inc., BenevolentAI, Recursion Pharmaceuticals, Numerate Inc., etc.

1. Introduction
1.1 Scope of the Study
1.2 Purpose of the Study
1.3 Limitations of the Study
1.4 Currency

2. Executive Summary
2.1 Market Definition
2.2 Market Size and Segmentation
2.3 Insights for CXOs

3. Market Forces
3.1 Drivers
3.1.1 Increasing Demand for Novel Therapies
3.1.2 Cost and Time Efficiency
3.1.3 Integration of Omics Data
3.1.4 Increasing Collaboration Between Pharmaceutical and AI Companies
3.2 Restraints
3.2.1 Regulatory Hurdles and Concerns Related to the Safety and Efficacy
3.2.2 High Initial Setup Costs
3.3 Opportunities
3.3.1 Patent Expiry of Drugs
3.3.2 Advancements in AI Technology
3.3.3 Focus on Developing Human-Aware AI Systems
3.4 Challenges
3.4.1 Ethical and Privacy Concerns
3.4.2 Lack of Skilled Workforce

4. AI and Sustainability Footprints
4.1 Market Trends of AI and Sustainability
4.2 Application of AI - AI Adoption Levels
4.3 Environmental and Emission Reduction Initiatives

5. Market Analysis
5.1 Government Regulations
5.2 Value Chain Analysis
5.3 PESTLE Analysis
5.4 Porter's Five Forces Analysis
5.5 Ansoff Analysis
5.6 Technology Trends

6. Market Segmentations
6.1 Global AI in Drug Discovery Market, By Offering
6.1.1 Market Overview, Size and Forecast
6.1.2 Software
6.1.3 Services
6.2 Global AI in Drug Discovery Market, By Technology
6.2.1 Market Overview, Size and Forecast
6.2.2 Machine Learning (ML)
6.2.3 Deep Learning (DL)
6.2.4 Natural Language Processing (NLP)
6.2.5 Others
6.3 Global AI in Drug Discovery Market, By Use Case
6.3.1 Market Overview, Size and Forecast
6.3.2 Small Molecule Design and Optimization
6.3.3 Understanding Disease
6.3.4 Safety & Toxicity
6.3.5 Vaccines Design and Optimization
6.3.6 Antibody & Other Biologic Design and Optimization
6.4 Global AI in Drug Discovery Market, By Applications
6.4.1 Market Overview, Size and Forecast
6.4.2 Target Identification & Validation
6.4.3 Drug Optimization & Design
6.4.4 Lead Identification & Optimization
6.4.5 Preclinical & Clinical Trail Optimization
6.4.6 Biomarker Discovery
6.4.7 Others
6.5 Global AI in Drug Discovery Market, By End-User
6.5.1 Market Overview, Size and Forecast
6.5.2 Pharmaceuticals and Biotechnology Companies
6.5.3 Contact Research Organizations
6.5.4 Academic and Government Institutes

7. Region Analysis of the Global AI in Drug Discovery Market
7.1 Americas
7.1.1 Brazil
7.1.2 Canada
7.1.3 Mexico
7.1.4 US
7.1.5 Others
7.2 Europe
7.2.1 France
7.2.2 Germany
7.2.3 Italy
7.2.4 Russia
7.2.5 United Kingdom
7.2.6 Others
7.3 Middle East & Africa
7.3.1 Israel
7.3.2 Nigeria
7.3.3 Saudi Arabia
7.3.4 South Africa
7.3.5 UAE
7.3.6 Others
7.4 Asia
7.4.1 Australia – New Zealand
7.4.2 China
7.4.3 India
7.4.4 Japan
7.4.5 South Korea
7.4.6 Others

8. Competitive Analysis
8.1 Market Share Analysis
8.2 Alphabet
8.3 Atomwise, Inc.
8.4 BenevolentAI
8.5 Berg Health
8.6 BioSymetrics Inc.
8.7 BioXcel Therapeutics, Inc.
8.8 Cloud Pharmaceuticals, Inc.
8.9 Cresset
8.10 Cyclica Inc.
8.11 Deep Genomics
8.12 Envisagenics
8.13 Exscientia Ltd.
8.14 Healx Ltd.
8.15 Iktos
8.16 Insilico Medicine, Inc.
8.17 Kebotix
8.18 Lantern Pharma Inc.
8.19 Microsoft Corp.
8.20 Morphic Therapeutic
8.21 Numerate, Inc.
8.22 Pharnext
8.23 Recursion Pharmaceuticals
8.24 Schrodinger, Inc.
8.25 TwoXAR, Inc.
8.26 XtalConcepts GmbH
8.27 XtalPi Inc.

9. Appendix
9.1 Research Methodology
9.2 Assumptions for the Report
9.3 List of Abbreviations

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