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Updated: Feb 18, 2026

Profiling Sensitivity to Targeted Therapies in EGFR-Mutant NSCLC Patient-Derived Organoids
08:52

Profiling Sensitivity to Targeted Therapies in EGFR-Mutant NSCLC Patient-Derived Organoids

Published on: November 22, 2021

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EGFRをターゲットとするPROTACsのための機械学習ベースの薬理学予測器 (EGFR-PROPK)

Ran Zhang1, Fenglei Li1,2, Yao Liu3

  • 1Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China.

Communications chemistry
|February 16, 2026
PubMed
まとめ

PROTEOLYSIS Tターゲティングキメラ (PROTACs) は治療効果が有望だが,その薬物動態 (PK) を最適化することは困難である. この研究では,PROTAC特有のモデル,EGFR-PROPKを開発し,半減期やクリアランスなどの主要なPK特性の予測精度を向上させました.

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A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

Published on: April 6, 2016

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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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