Artificial Intelligence (AI) in Drug Discovery Market – Thematic Research
In recent years, driven by the COVID-19 pandemic, the pharma industry has undergone increased levels of digital transformation. The availability of ultra-large datasets and technological advances has led to more interest in the use of artificial intelligence (AI) and big data analytics across the pharma value chain, from drug discovery and clinical trial design, right through to sales and marketing.
Over the past 3-4 years, there has been increased interest in the use of AI in drug discovery, as witnessed by the emergence of an ever-growing number of start-ups operating in this area, increasing number of drug discovery partnerships, and record levels of investment. While most drugs developed using AI are in the early stages of development, there have been some recent major milestones, including the first drug developed by AI to enter clinical trials and the repurposing of an already marketed drug to treat COVID-19.
GlobalData’s Smart Pharma survey shows that AI and big data are the top emerging technologies currently employed for drug discovery and development, and their use will increase over the next two years. Similarly, the Digital Transformation and Emerging Technology in the Healthcare Industry survey showed that across the pharma value chain, AI will lead technology investments over the next two years.
The artificial intelligence in drug discovery thematic intelligence report assesses provides an overview of the current landscape, including healthcare, technology, regulatory, and macroeconomic trends, as well as key players, while also highlighting opportunities for the use of AI in the future. Furthermore, it provides an industry-specific analysis based on GlobalData databases and surveys, as well as several case studies.
AI in Drug Discovery Theme: Key Trends
The key trends that will shape the AI in drug discovery theme can be classified into four categories: healthcare trends, technology trends, macroeconomic trends, and regulatory trends.
- Healthcare trends – The key healthcare trends that will shape the AI in drug discovery theme are COVID-19 on digital transformation in pharma, the rising cost of R&D and dwindling pipelines, increasing availability of ultra-large datasets, increased need for open science in drug discovery, pharma companies building in-house AI capabilities, formation of industry consortia in AI, and role of AI in precision and personalized medicine.
- Technology trends – The report focuses on key technology trends impacting AI in drug discovery theme including the role of technology giants in AI-based drug discovery, big data, cloud, quantum computing, and cybersecurity.
- Macroeconomic trends – The key macroeconomic trends that will shape the AI in drug discovery theme are addressing AI skills shortages, increased AI partnerships in drug discovery, increased volume and value of AI-related funding deals in drug discovery, mergers and acquisitions (M&As), and China’s quest for AI dominance.
- Regulatory trends – The report highlights the key regulatory trends shaping the AI in drug discovery theme including the International Coalition of Medicines Regulatory Authorities (ICMRA) report on the use of AI to develop drugs, regulatory divergence, the European Commission (EC) white paper, and the proposed framework on AI, and the US leadership in AI.
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AI in Drug Discovery – Industry Analysis
The pharma industry is slow when adopting new technologies such as AI. However, there has been increased activity over the past few years. Many more companies, including recognized leaders, are adopting AI as part of their digital transformation strategies. AI will be a key driver of healthcare innovation in the future through various applications that include management of chronic diseases, drug discovery and development, improvement of clinical trials, manufacturing, and supply chains. COVID-19 has been one of the reasons for the rapid innovation and investment in AI. Compared to pharma and medical device companies, GlobalData forecasts that healthcare providers will spend the most on AI platforms in 2024.
The AI in drug discovery market analysis also covers:
- Analysis of drugs discovered using AI
- Survey data on the adoption of AI in pharma
- Deals
- Case studies
- Hiring trends
- Company filing trends
- Social media trends
Global AI Platform Revenue in Pharma, Medical, and Healthcare, 2019-2024
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AI in Drug Discovery - Value Chain Analysis
The main applications of AI algorithms in drug discovery are the identification and validation of drug targets, virtual screening of compounds, de novo drug design, drug repurposing, and identification of treatment response biomarkers.
Drug discovery begins with the identification of drug targets, which are molecules that are inherently linked to a particular disease process. They should exhibit several features such as involvement in a crucial biological pathway, functionally and structurally characterized, and the ability to interact with drug-like compounds.
AI in Drug Discovery Value Chain
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Leading AI Technology Vendors
Some of the leading technology vendors within the AI in drug discovery theme are:
- Microsoft
- Alphabet
- IBM
Leading AI Specialists in Drug Discovery
Some of the leading AI specialists in drug discovery are:
- AbCellera
- Atomwise
- Auransa
Leading Pharma Adopters of AI in Drug Discovery
Some of the leading pharma adopters of AI in drug discovery are:
- AstraZeneca
- Bristol Myers Squibb
- GSK
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Drug Development Scorecard – AI Theme
At GlobalData, we use a scorecard approach to predict tomorrow’s leading companies within each sector. Our sector scorecards have three screens: a thematic screen, a valuation screen, and a risk screen. The drug development scorecard has two screens:
- The thematic screen tells us who are the overall leaders in the 10 themes that matter most, based on our thematic engine.
- The valuation screen ranks our universe of companies within a sector based on selected valuation metrics.
Drug Development Scorecard: Thematic Screen
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AI in Drug Discovery Market Overview
| Report Pages | 73 |
| Regions Covered | Global |
| Key Trends | Healthcare Trends, Technology Trends, Macroeconomic Trends, and Regulatory Trends |
| Value Chains | Target Identification and Validation, Generation of Molecule Leads/De Novo Drug Design, Drug Repurposing, and Response Biomarker Discovery |
| Leading AI Technology Vendors | Microsoft, Alphabet, and IBM among others |
| Leading Specialist AI Vendors | AbCellera, Atomwise, and Auransa among others |
| Leading Pharma adopters | AstraZeneca, Bristol Myers Squibb, and GSK among others |
Reasons to Buy
- See who the leading players are in the AI in drug discovery space.
- See how the competitive landscape is evolving, with a review of company activity including strategic partnerships and funding deals, as well as mergers and acquisitions (M&A).
- See what trends are driving the use of AI in drug discovery.
- See an analysis of drugs discovered by AI, including by company, phase of development, therapy area, and molecule type.
Key Players
Table of Contents
List of Tables
List of Figures
Frequently Asked Questions
The key healthcare trends shaping the AI in drug discovery theme are COVID-19 on digital transformation in pharma, the rising cost of R&D and dwindling pipelines, increasing availability of ultra-large datasets, increased need for open science in drug discovery, pharma companies building in-house AI capabilities, formation of industry consortia in AI, and role of AI in precision and personalized medicine.
The key technology trends shaping the AI in drug discovery theme are the role of technology giants in AI-based drug discovery, big data, cloud, quantum computing, and cybersecurity.
The key macroeconomic trends shaping the AI in drug discovery theme are addressing AI skills shortages, increased AI partnerships in drug discovery, increased volume and value of AI-related funding deals in drug discovery, mergers and acquisitions (M&As), and China’s quest for AI dominance.
The key regulatory trends shaping the AI in drug discovery theme are the International Coalition of Medicines Regulatory Authorities (ICMRA) report on the use of AI to develop drugs, regulatory divergence, the European Commission (EC) white paper, and the proposed framework on AI, and US leadership in AI.
GlobalData’s AI in drug discovery value chains can be divided into four segments: target identification and validation, generation of molecule leads/de novo drug design, drug repurposing, and response biomarker discovery.
Some of the leading technology vendors within the AI in drug discovery theme are Microsoft, Alphabet, and IBM.
Some of the specialists making their mark within AI in drug discovery theme are AbCellera, Atomwise, and Auransa.
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