市場調査レポート
商品コード
1191727
臨床試験におけるAIの成長の機会と革新的な使用事例Growth Opportunities and Innovative Use Cases for AI in Clinical Trials |
臨床試験におけるAIの成長の機会と革新的な使用事例 |
出版日: 2022年12月21日
発行: Frost & Sullivan
ページ情報: 英文 64 Pages
納期: 即日から翌営業日
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AI技術は、実世界のデータの収集と分析、臨床試験の第I相と第II相のシームレスな組み合わせ、患者を中心とした新しいエンドポイントの開発など、臨床試験を変革するための基本的なイノベーションをもたらすものです。AIを活用することで、さまざまな入力から標準化、構造化、デジタル化されたデータ要素を作成することができ、AIを活用した試験デザインは、患者中心のデザインの作成を最適化・加速するため、患者の負担を大幅に減らし、成功の可能性を高め、修正回数を減らし、試験全体の効率性を向上させることが可能です。大手テクノロジープロバイダーと製薬スタートアップは共に、今後のより効果的な臨床試験の方向性を示しています。
当レポートでは、臨床試験におけるAI市場について調査し、市場の概要とともに、戦略的インペラティブ、成長の機会などを提供しています。
Integrating Real-world Insights into Intelligent Platforms to Enable Patient-centric Trial Design
As clinical pipelines globally witness a surge in novel complex therapies, the clinical trial industry demands new tools in predictive analytics to improve trial design, planning, and execution. Artificial intelligence is gaining large-scale recognition as support for decentralized trial designs, thus enabling patient-centric clinical trial designs. The rapid adoption of AI/ML algorithms and platforms to structure and utilize electronic health records (EHRs) allows the industry to tap into a vast, rich, and highly relevant data source that holds tremendous potential in improving the global clinical trial landscape.
Incorporating integrated AI-driven solutions in clinical trial design and patient retention will ease the go-to-market strategy for various CROs and pharma players as they will reduce costs, increase efficiency, and support the transition to decentralized trials by means of remote patient recruitment, management, as well as engagement through interactive platforms thus ensuring higher retention. Additionally, these platforms are highly beneficial in the selection of appropriate investigators and trial sites. Randomized control trials (RCTs) are another possible application for sponsors to leverage AI in analyzing vast site-level datasets for greater insight into trial design and implementation.
Leading CROs such as Syneos Health or IQVIA, as well as several pharmaceutical companies such as BMS, have successfully deployed AI-based platforms to support site selection and patient recruitment. Companies (including AstraZeneca and Novartis among others) are also applying AI in clinical trials to enable the optimization of different stages with the intent of reducing the overall trial timelines.
AI technologies bring fundamental innovations for transforming clinical trials, such as collecting and analyzing real-world data, seamlessly combining phases I and II of clinical trials, and developing novel patient-centered endpoints. AI can be leveraged to create standardized, structured, and digital data elements from a range of inputs, and as AI-enabled study design helps optimize and accelerate the creation of patient-centric designs, it significantly reduces patient burden, increases the likelihood of success, decreases the number of amendments, and improves the overall efficiency of trials. Together, big technology providers and pharmaceutical start-ups are setting the course for more effective clinical trials in the future.