Artificial Intelligence (AI) in Drug Discovery – Strategic Intelligence

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Published: November 06, 2024 Report Code: GDHCHT536-TH

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Reasons to buy the ‘AI in Drug Discovery’ strategic intelligence report:

  • Understand the key trends accelerating or hindering AI in the drug discovery space.
  • See market forecasts for different therapies within AI up to 2028.
  • Understand recent and influential developments in AI.
  • Review leaders and disruptors across the AI value chain.

How is our ‘AI in Drug Discovery’ report unique from other reports in the market?

  • A dedicated report examining the pivotal healthcare, technological, macroeconomic, and regulatory trends shaping the AI-driven drug discovery landscape.
  • This report also provides an in-depth analysis of how these trends are poised to either accelerate progress or create obstacles to the growth of AI in the drug discovery market.
  • This report consolidates GlobalData’s latest thinking and forecasts around how the healthcare, macroeconomic, technology, and regulatory trends will impact AI in drug discovery, as well as providing insights into the leading players and future disruptors across the value chain
  • Additionally, this report is designed to provide strategic planners, competitive intelligence professionals, and key stakeholders in the pharmaceutical industry a clear view of the opportunities and risks over the foreseeable future for AI.

We recommend this valuable source of information to anyone involved in:

  • ​​​​Healthcare and Pharma Technology Leaders and Start-ups
    • Leading AI Adopters in Healthcare
    • Specialist AI Vendors in Healthcare
  • Distributors, Pharmacies, Research Scientists, and Healthcare IT Specialists
  • Executives Leading the Digital Healthcare Segment
  • Healthcare Supplies and Manufacturing (Pharma and Medical Devices)
  • Products Pipeline Research and Drug Development/Clinical Research Organisations
  • Consulting and Professional Services (e.g., Investment Companies, Investment Banks, Equity Companies, etc.)
  • Financial Institutions (Investors in Pharma/Biotech, Pricing Consultancies)

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Artificial Intelligence (AI) in Drug Discovery Strategic Report Overview

Over the past two years, AI’s use in drug discovery has become more popular, evidenced by the growing number of drug discovery-related collaborations between specialist AI vendors, AI technology vendors, and pharma companies. Additionally, there has been an increase in drug discovery start-ups entering the industry that use their AI-powered platform to improve drug discovery or utilize AI to advance the development of their pipeline drugs.

The ‘Artificial Intelligence (AI) in Drug Discovery’ strategic intelligence report gives you an in-depth insight into how the AI theme can impact the drug discovery industry. It further entails a deep-dive analysis of the industry including the AI value chain as well as market values for the current and forecast period. The report gives an insight into the market players and the competitive landscape within the theme.

Report Pages 66
Regions Covered Global
Key Trends ·       Healthcare Trends

·       Technology Trends

·       Macroeconomic Trends

·       Regulatory Trends
Value Chain ·       Identification and Validation of Drug Targets

·       Clinical Trials

·       Drug Repurposing
Leading AI Technology Vendors ·       Alphabet

·       Amazon

·       IBM
Specialist AI Vendors ·       1910 Genetics

·       AiCure

·       Antidote Technologies
Leading Pharma Adopters ·       AstraZeneca

·       Bayer

·       Bristol Myers Squibb (BMS)
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AI in Drug Discovery – Key Trends

The main trends shaping the AI in drug discovery theme over the next 12 to 24 months are classified into healthcare, technology, macroeconomic, and regulatory trends.

  • Healthcare trends: Compound screening, the rising popularity of mRNA and antibody-based drugs, precision and personalized medicine, and digital biomarkers are among the healthcare trends impacting the theme.
  • Technology trends: The key technology trends impacting the AI in drug discovery theme are the use of Generative AI and Three-dimensional (3D) printing. Additionally, big data, tech giants, and cybersecurity also play a role within the theme.
  • Macroeconomic trends: Mergers and acquisitions (M&As) and the growth of AI in the drug discovery market are among the points to be considered for macroeconomic trends.
  • Regulatory trends: The FDA’s position on the use of AI in drug discovery, ethical considerations of the use of AI in drug discovery, and data privacy and security are impacting the theme.

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AI in Drug Discovery Value Chain Analysis

The main applications of AI in drug discovery are the identification and validation of drug targets, clinical trials, and drug repurposing.

Target identification and validation: Target identification is the first step of the drug discovery process. It is the idea of choosing a target, based on available information, that can provide an effective treatment for a specific disease. This target will aim to show good drug-like properties so that, when interacting with the desired drug molecule, can bring about a biological response without any adverse effects. These targets include a wide range of biological molecules, but the most common types are proteins such as enzymes, antibodies, G-protein-coupled-receptors, and more.

AI in Drug Discovery Value Chain Analysis

AI in Drug Discovery Value Chain Analysis

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AI in Drug Discovery – Competitive Landscape

The key companies that will make their mark within the AI in drug discovery theme are as follows:

Leading AI Technology Vendors: A few of the technology players within the AI in drug discovery theme are Alphabet, Amazon, and IBM, among others.

Specialist AI Vendors in Drug Discovery: A few of the specialist AI vendors in the drug discovery sector are 1910 Genetics, AiCure, and Antidote Technologies, among others.

Leading Pharma Adopters of AI in Drug Discovery: A few of the leading adopters of AI in drug discovery include AstraZeneca, Bayer, and Bristol Myers Squibb (BMS).

Key Companies in AI Theme

Key Companies in AI Theme

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Drug Development Sector Scorecard

At GlobalData, we use a scorecard approach to predict tomorrow’s leading companies within each sector. Our sector scorecard has three screens: a thematic screen, a valuation screen, and a risk screen.

  • The thematic screen ranks companies based on overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of future performance.
  • Our valuation screen ranks our universe of companies within a sector based on selected valuation metrics.
  • Our risk screen ranks companies within a particular sector based on overall investment risk.

Drug Development Sector Scorecard – Thematic Screen

pment Sector Scorecard – Thematic Screen

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Alphabet
Amazon
Dassault Systèmes
IBM
Cisco
Informatica
Oracle
Microsoft
BenevolentAI
Exscientia
Recursion
IQVIA
Insilico Medicine
Syneos Health
Parexel
AstraZeneca
Boehringer Ingelheim
GSK
Eli Lilly and Co
Novartis
Pfizer
Roche
Sanofi
Takeda
Merck & Co

Table of Contents

  • 1. Executive Summary

  • 2. Players

  • 3. Thematic Briefing

    • 3.1. What is AI?

    • 3.2. Advanced AI capabilities

    • 3.3. AI in drug discovery

  • 4. Trends

    • 4.1. Healthcare trends

    • 4.2. Technology trends

    • 4.3. Macroeconomic trends

    • 4.4. Regulatory trends

  • 5. Industry Analysis

    • 5.1. Market size and growth forecasts

    • 5.2. Analysis of drugs discovered using AI

    • 5.3. Survey data on the adoption of AI in pharma

    • 5.4. AI in Drug Discovery key opinion leader research

      • 5.4.1. Challenges associated with traditional drug discovery

      • 5.4.2. How AI is used to address the challenges of drug discovery

      • 5.4.3. Limitations of the use of AI in drug discovery

      • 5.4.4. The role of AI over the next five to 10 years

      • 5.4.5. Current AI-driven drug discovery market trend

      • 5.4.6. The most critical stage of AI in drug discovery

      • 5.4.7. Key Lessons from working with AI in drug discovery.

  • 6. Deals

    • 6.1. Strategic alliances

    • 6.2. Funding

    • 6.3. M&A

    • 6.4. Case Studies

      • 6.4.1. Exscientia and AWS Provide an Innovative Approach to Drug Discovery

      • 6.4.2. Predictive Oncology Employs Innovative 3D Cell Technology to Develop Cancer Therapies

      • 6.4.3. Eurofins Discovery’s New AI-Driven Platform Accurately Predicts ADMET Properties of Molecules

      • 6.4.4. 1910 Genetics Collaborates with Microsoft to Bring Change to Drug Discovery

      • 6.4.5. Dyno Therapeutics to Use Nvidia’s BioNeMo to Improve Drug Discovery of Gene Therapies

      • 6.4.6. ImmunitoAI’s AI Platform to Enhance Antibody-Based Drug Discovery

      • 6.4.7. Standigm Partner with Institut Pasteur Korea to Develop a New Drug for Resistant Tuberculosis

      • 6.4.8. Selection of a New Heart Failure Target Shows Continued Success Between BenevolentAI and AstraZeneca

    • 6.5. Social media trends

  • 7. Value Chain

    • 7.1. Target identification and validation

    • 7.2. Clinical trials

    • 7.3. Drug repurposing

  • 8. Companies

    • 8.1. Leading AI technology vendors

    • 8.2. Specialist AI vendors in drug discovery

    • 8.3. Leading pharma adopters of AI in drug discovery

  • 9. Sector Scorecards

    • 9.1. Drug development sector scorecard

      • 9.1.1. Who’s who

      • 9.1.2. Thematic screen

      • 9.1.3. Valuation screen

      • 9.1.4. Risk screen

  • 10. Abbreviations

  • 11. Bibliography

  • 12. Further Reading

    • 12.1. GlobalData reports

  • 13. Our Thematic Research Methodology

  • 14. About GlobalData

  • 15. Contact Us

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