在稀缺的临床数据中利用神经ODE来研究达尔巴万辛的种群药动力学
Tommaso Giacometti1,2, Ettore Rocchi3,4, Pier Giorgio Cojutti3,5
1Department of Physics and Astronomy, Alma Mater Studiorum, University of Bologna, 40126 Bologna, Italy.
Entropy (Basel, Switzerland)
|June 26, 2025
概括
神经常规微分方程 (NODE) 为药物度预测提供了一种数据驱动的方法,在纳入患者共变量时,其表现优于传统模型. 这种方法通过改进有限数据的药理动力学建模来增强精确医学.
科学领域:
- 药理动力学和计算建模.
- 机器学习在药物开发中的应用.
- 精准医学和个性化疗法.
背景情况:
- 传统的药物动力学模型,如分区和非线性混合效应 (NLME) 模型,依赖于强有力的假设,并与复杂的共同变量关系作斗争.
- 神经常规微分方程 (NODE) 提供了一个数据驱动的替代方案,直接从数据中学习微分方程并集成共变量.
- 在药理动力学研究中,有限的数据可用性是常见的挑战.
研究的目的:
- 调查神经常规微分方程 (NODE) 作为药物度预测传统模型的优越替代方案.
- 为了评估NODE在捕捉复杂的共变相互作用中的性能,在药理动力学数据中.
- 为了评估NODE的可解释性,使用Shapley添加式解释 (SHAP) 值.
主要方法:
- 将NODE应用于现实世界的Dalbavancin药理动力学数据集 (n=218名患者).
- 将NODE与使用交叉验证的两部分模型和NLME模型进行比较.
- 由于数据有限,实施数据增强策略,用于预培训NODE.
- 评估具有和没有共变量的预测性表现,并通过SHAP值分析模型可解释性的分析.
主要成果:
- 在没有共变量时,NODE的表现与最先进的NLME模型相提并论.
- 与传统模型相比,当将共变量纳入时,NODE显示出更高的预测准确性.
- SHAP分析证实,NODE有效地利用共变量来改善预测.
- 数据增强策略有助于为稀疏数据集预培训NODE.
结论:
- NODE 代表了药理动力学建模的有前途的进步,特别是在处理复杂的共同变量相互作用时.
- NODE提供了更高的预测准确性,特别是在具有高维共变量和有限数据的场景中.
- 这种方法有助于改善药物度预测,支持精准医学中的个性化治疗策略.
相关概念视频
01:12Analysis of Population Pharmacokinetic Data
397
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
397
00:59Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
133
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
133
01:06Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
132
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
132
01:22Nonlinear Pharmacokinetics: Causes of Nonlinearity
351
Nonlinearity in drug pharmacokinetics is caused by various factors influencing how a drug is absorbed, distributed, metabolized, and excreted. Understanding these nonlinear processes is crucial for predicting drug behavior in the body and optimizing drug dosing regimens.
Nonlinear drug absorption can occur when the process is rate-limited by solubility, carrier-mediated transport systems, or saturation of the presystemic gut wall or hepatic metabolism. For instance, high doses of riboflavin...
Nonlinear drug absorption can occur when the process is rate-limited by solubility, carrier-mediated transport systems, or saturation of the presystemic gut wall or hepatic metabolism. For instance, high doses of riboflavin...
351
01:19Nonlinear Pharmacokinetics: Overview
573
Nonlinear or dose-dependent pharmacokinetics is a phenomenon that occurs when the pharmacokinetic parameters of certain drugs deviate from linear pharmacokinetics at higher doses. These drugs do not follow the expected first-order kinetics, where the rate of drug elimination is directly proportional to the drug concentration. Instead, they exhibit a nonlinear relationship, which can be attributed to several factors.
Nonlinearity can arise due to the saturation of plasma protein-binding or...
Nonlinearity can arise due to the saturation of plasma protein-binding or...
573
01:22Nonlinear Pharmacokinetics: Bioavailability and Protein-Drug Binding
286
When a drug follows nonlinear pharmacokinetics, its bioavailability, the amount of the drug that reaches the systemic circulation, can change with different doses. This is due to the presence of a saturable pathway. The pathway becomes saturated as the drug concentration increases, decreasing the absorption rate. Consequently, the drug's bioavailability may be lower than expected at higher doses.
To quantify the extent of bioavailability, pharmacologists often use a parameter called .
To quantify the extent of bioavailability, pharmacologists often use a parameter called .
286