医薬品と医療機器に関する英国連合データネットワークに関する規制の見通し: "Study-A-Thon"からの教訓
Helen P Booth1, John Connelly2, Daniel Dedman2
1Medicines and Healthcare products Regulatory Agency, 10 South Colonnade, Canary Wharf, London, E14 4PU, UK. helen.booth@mhra.gov.uk.
Therapeutic innovation & regulatory science
|August 20, 2025
まとめ
イギリスの分散型データネットワークは,現実世界のデータ (RWD) を利用して規制の意思決定を改善できる. リアル・ワールド・エビデンス (RWE) をタイムリーに生成するために,よりよいデータアクセスと共通のモデルの必要性が強調されました.
科学分野:
- 医療情報学
- 規制科学
- データサイエンス
背景:
- 国際医療規制機関は,現実世界のデータ (RWD) で意思決定を強化することを目指しています.
- 英国国立保健局は人口データを豊富に保有しているが,データサイロ化,相互運用性,クロスセットアクセスといった課題に直面している.
- イギリスの分散型データネットワークを動員することは,規制上の利用のためのリアルワールド・エビデンス (RWE) をタイムリーに生成するために極めて重要です.
研究 の 目的:
- 規制上の目的でRWEを生成するための英国の分散データネットワークの可能性を調査する.
- ケーススタディを通じて,医療機器と二次医療の処方に関する優先度の高いデータ不足を解決する.
- RWD戦略に関する英国の医薬品およびヘルスケア製品規制局 (MHRA),関係者,および国際パートナーのための重要な学びを特定する.
主な方法:
- 2023年に『Study-A-Thon』イベントが開催されました.
- 2つのケーススタディは,医療機器と二次ケアを処方するデータギャップに焦点を当てた.
- データ不足の分析と現地データと臨床専門知識の重要性
主要な成果:
- 研究A-Thonは両方のケーススタディで成果を上げ,アプローチの可行性を実証しました.
- 特定された欠陥には,介護環境における患者フォローアップの欠如と,製品利用のための共通のデータモデルの必要性があります.
- 地元データと臨床専門知識がデータ収集と解釈において果たす重要な役割を強調した.
結論:
- イギリスの統合データモデルは,さらに発展すれば,製品のライフサイクル全体を通して,国家規制の意思決定を大幅に強化することができる.
- 医療現場でのデータ収集の改善と 信頼性の高い解釈は,RWEの生成に不可欠です.
- 協力とデータインフラストラクチャの課題に取り組むことは,規制上の目的でRWDを活用する鍵です.
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