創薬におけるAI市場：戦略的インテリジェンス

近年、製薬業界はデジタルトランスフォーメーションの波に飲み込まれ、製薬バリューチェーンのさまざまな側面で先端技術の統合が進んでいます。人工知能（AI）とビッグデータは、創薬の強化から臨床試験デザインの最適化まで、イノベーションを推進する最前線にあります。

創薬プロセスは非常に高価で時間のかかるプロセスです。最近の技術動向にもかかわらず、研究開発（R&D）の成功率は非常に低く、効率と成果を改善するためのAIなどの革新的技術の必要性が強調されています。

当レポートは、創薬におけるAI市場について調査し、医療、マクロ経済、技術、規制の動向が創薬のAIにどのような影響を与えるかについての考え方と予測をまとめています。

目次

図表一覧

表の一覧

• 参入企業
• テーマ別ブリーフィング
• 動向
• 業界分析
• バリューチェーン
• 企業
• 医薬品開発カード
• 略語
• その他の情報
• 著者について
• テーマ別調査手法

List of Tables

• Table 1: Healthcare trends
• Table 2: The key technology trends impacting AI in drug discovery
• Table 3: The key macroeconomic trends impacting AI in drug discovery
• Table 4: The key regulatory trends impacting AI in drug discovery
• Table 5: Drugs in clinical development and includes information
• Table 6: Strategic alliances
• Table 7: Top VC deals associated with AI in drug discovery announced from June 2022 to August 2024
• Table 8: M&A
• Table 9: Target identification and validation
• Table 10: The time taken to identify novel drug targets.
• Table 11: The different platforms and libraries used for drug repurposing
• Table 12: The leading technology players within the AI in drug discovery theme and summarizes their competitive position
• Table 13: The specialist AI vendors in drug discovery and summarizes their competitive position
• Table 14: The leading adopters of AI in drug discovery and summarizes their competitive position
• Table 15: Abbreviations
• Table 16: GlobalData reports

List of Figures

• Figure 1: Examples of leading players in AI in drug discovery and place in the value chain
• Figure 2: The five categories of advanced AI capabilitiesp
• Figure 3: Global AI platform, hardware, and consulting and support services revenue in pharma, 2019-28
• Figure 4: Top companies by number of drugs developed using AI-based technologies
• Figure 5: Breakdown of drugs by therapy area
• Figure 6: Pharma companies' confidence level in AI within the pharma industry
• Figure 7: AI can benefit different aspects of the pharmaceutical value chain.
• Figure 8: Top Influencer trends related to AI
• Figure 9: Top influencer posts related to AI and drug discovery, 2024
• Figure 10: AI in drug discovery value chain
• Figure 11: Examples of leaders and challengers in target identification and validation
• Figure 12: The use of AI in clinical trials
• Figure 13: Examples of leaders and challengers in target identification and validation
• Figure 14: Examples of leaders and challengers in drug repurposing
• Figure 15: Who does what in the drug development space?
• Figure 16: Our 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
• Figure 17: Our valuation screen ranks our universe of companies within a sector based on selected valuation metrics
• Figure 18: Our risk screen ranks companies within a particular sector based on overall investment risk

In recent years, the pharma industry has been taken over by a wave of digital transformation, leading to the integration of advanced technologies across different aspects of the pharma value chain.

Artificial intelligence (AI) and big data are at the forefront of driving innovation, from enhancing drug discovery to optimizing clinical trial design.

The drug discovery process is a very expensive and time-consuming process. Despite recent technological advancements, the success rate of research and development (R&D) is very low, adding emphasis to the need for innovative technologies, such as AI, to improve efficiency and outcomes.

This report consolidates GlobalData's latest thinking and forecasts around how the healthcare, macroeconomic, technology, and regulatory trends will impact the AI in drug discovery, as well as providing insights into the leading players and future disruptors across the value chain, and providing insights into key drugs and markets from GlobalData's Pharma Intelligence Center. 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.

Scope

• 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 for the growth of the AI in drug discovery market.

Reasons to Buy

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

Table of Contents

Table of Contents

List of Figures

List of Tables

• Players
• Thematic Briefing
• Trends
• Industry Analysis
• Value Chain
• Companies
• Drug Development Scorecard
• Abbreviations
• Further Reading
• About the Authors
• Our Thematic Research Methodology