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Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
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Designing a dosage regimen, which refers to the manner of drug administration, is a complex process involving the selection of drug dose, route, and frequency. This process is underpinned by pharmacokinetic parameters derived from tests and population averages. These parameters are then tailored to patient-specific variables such as diagnosis, demographics, and allergy status. Once therapy commences, therapeutic response monitoring is critical and achieved through clinical and physical...
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Diagonal Method to Measure Synergy Among Any Number of Drugs
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[Study on prescription combination and design method based on dichotomy and greedy algorithm].

Fang Dong, Xiao-He Li, Hong-Ling Guo

    Zhongguo Zhong Yao Za Zhi = Zhongguo Zhongyao Zazhi = China Journal of Chinese Materia Medica
    |October 4, 2014
    PubMed
    Summary

    Traditional Chinese Medicine (TCM) prescription design lacks a definitive method for medicinal property combinations. This study introduces a novel approach using bipartite graphs and greedy algorithms for efficient herbal medicine selection.

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    Area of Science:

    • Pharmacology
    • Computational Biology
    • Traditional Chinese Medicine

    Context:

    • Traditional Chinese Medicine (TCM) prescription formulation relies on principles like taste, channel tropism, and Qi movement.
    • Medicinal property theory is central to TCM combinations, yet lacks standardized methods for application.
    • Existing methods for TCM prescription design are often empirical and lack systematic approaches.

    Purpose:

    • To develop a systematic and computational method for designing TCM prescription combinations based on medicinal properties.
    • To address the limitations of current TCM prescription design, particularly the lack of a defined methodology for medicinal property compatibility.
    • To explore the application of graph theory and algorithms in optimizing TCM formulation.

    Summary:

    • This paper proposes a novel method for designing TCM prescription combinations utilizing bipartite graphs and a greedy algorithm.
    • The method focuses on optimizing the selection of herbal medicines based on their medicinal properties.
    • The efficacy of this approach was demonstrated using the example of Siweilurong Pills, showcasing its potential for rapid herbal medicine selection.

    Impact:

    • Provides a computational framework for TCM prescription design, enhancing efficiency and objectivity.
    • Offers a potential solution for identifying suitable alternatives for endangered or banned medicinal materials.
    • Facilitates the modernization and standardization of TCM practices through data-driven approaches.