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Updated: Feb 14, 2026

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集団ベースのPBPKから個別化された仮想双子へ:臨床的検証と医学における応用
Marta Gonçalves1,2, Pedro Barata3,4,5, Nuno Vale1,2,6
1PerMed Research Group, RISE-Health, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal.
Journal of clinical medicine
|February 13, 2026
まとめ
生理学に基づく薬動力学 (PBPK) モデルは,パーソナライズされた医療のために仮想双子 (VTs) に移行しています. 個々の患者データを組み込むことは,薬物投与の予測を向上させ,精密医学のための集団レベルの分析を超越します.
科学分野:
- ファルマコキネティクスと薬物代謝
- パーソナライズされた医療と精密の投与量
- 計算生物学とモデリング
背景:
- 生理学的にベースの薬動力学 (PBPK) モデルは,薬物の吸収,分布,代謝および排泄 (ADME) を予測します.
- 伝統的な集団レベルのPBPKモデルは,真の精度の投与に限界があります.
- 仮想ツイン (VTs) と呼ばれる個々のPBPKモデリングへの移行が牽引力を増しています.
研究 の 目的:
- バーチャルツイン (VTs) を使用して,集団ベースのPBPKモデリングから個々のPBPKモデリングへの移行をレビューする.
- PBPKモデルのパーソナライゼーションと予測精度に関する患者特有のデータを組み込むことの影響を調査する.
- PBPKモデルの性能と臨床検証を評価するための方法論について議論する.
主な方法:
- 個別PBPKモデリングと仮想ツイン開発に関する文献のレビュー.
- 人口統計,生理学,現象型,遺伝子型データを含む研究の分析.
- 臨床検証を重視し,予測された薬剤濃度と観察された薬剤濃度を比較する.
主要な成果:
- 患者特有のデータを組み込む個々のPBPKモデル (VTs) は,特に腎機能のような生理学的パラメータに関する予測パフォーマンスを改善します.
- 人口統計学的変数は,特定の患者集団における精度を高めます.
- サイトクロームP450 (CYP) のデータを含めることの利点は矛盾しています.
結論:
- 仮想双子の個別PBPKモデリングは,パーソナライズド医療における精密投与への道を提供します.
- 臨床的検証とデータ制限の対処は,日常的な実装に不可欠です.
- デジタルツインのフレームワークへの統合は,臨床翻訳の有望さを示しています.
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