本研究旨在通过引入一种新颖的理论框架来解决为肿瘤患者选择最佳药物递送策略的挑战。我们提出了一种基于模糊逻辑的框架来定量评估肿瘤患者的健康状态（HS）。该框架将量化的 HS 评估与因果关系强度分析相结合，从药代动力学和药效学角度全面了解各种药物输送方案的有效性。我们的方法的有效性通过一系列真实患者案例研究得到证明，强调了其在以下方面的潜力：加强靶向药物递送策略的评估和选择。我们的工作通过展示模糊逻辑在靶向药物递送系统（TDD）中的实际应用并为药物递送策略选择的精确性建立新的基准，为该领域做出了贡献。这项研究具有重要意义用于开发个性化医疗，可能会通过更细致和科学严谨的方法来评估和选择药物输送方案，从而彻底改变该领域。开发模糊逻辑框架，用于精确量化肿瘤患者的健康状态。因果系统的创新整合，用于全面评估靶向给药策略。版权所有 © 2024 Elsevier Ltd。保留所有权利。

This study aims to address the challenge of selecting optimal drug delivery strategies for tumor patients by introducing a novel theoretical framework.We propose a fuzzy logic-based framework for quantitatively assessing Health States (HS) in tumor patients. This framework integrates quantified HS assessments with causality strength analyses, offering a comprehensive understanding of various drug delivery schemes' effectiveness from pharmacokinetic and pharmacodynamic perspectives.The efficacy of our approach is demonstrated through a series of real-world patient case studies, highlighting its potential to enhance the evaluation and selection of targeted drug delivery strategies.Our work contributes to the field by showcasing practical applications of fuzzy logic in targeted drug delivery systems (TDDs) and establishing a new benchmark for precision in drug delivery strategy selection.This study has significant implications for developing personalized medical treatments, potentially revolutionizing the field with a more nuanced and scientifically rigorous method for evaluating and selecting drug delivery protocols.Development of a fuzzy logic framework for precise quantification of health states in tumor patients. Innovative integration of a causal system for comprehensively evaluating targeted drug delivery strategies.Copyright © 2024 Elsevier Ltd. All rights reserved.