评估生成人工智能模型的潜力,以协助专家开发药理动力学模型
Sergio Sánchez-Herrero1, Laura Calvet Liñan2
1Department of Computer Science, Multimedia and Telecommunication, Universitat Oberta de Catalunya, Barcelona, 08018, Spain.
Advanced pharmaceutical bulletin
|September 9, 2025
概括
生成型人工智能工具可以帮助专家构建药理动力学 (PK) 模型,ChatGPT在生成人口PK分析和可视化R代码方面表现强. 这有助于PK专业人员开发复杂的模型.
科学领域:
- 药理动力学和药理计量学
- 人工智能在药物开发中的作用
- 计算药理学计算药理学
背景情况:
- 药理动力学 (PK) 建模对于理解药物在人体中的行为至关重要.
- 开发 PK 模型需要专门的编程技能,这往往是专家的障碍.
- 生成型人工智能为自动化和简化PK模型开发提供了潜在的解决方案.
研究的目的:
- 评估免费生成AI工具 (ChatGPT,Gemini,Copilot) 在协助制药动力学 (PK) 模型的开发中的实用性.
- 评估人工智能产生R代码的能力,以构建一个两个分区的群体PK模型.
- 确定人工智能生成的 PK 模型的准确性和可重复性.
主要方法:
- 使用R Studio开发了PK模型,利用生成AI工具来生成代码.
- 关键任务包括模型描述,输入要求,结果解释和代码创建.
- 模型性能通过将估计和模拟图表与参考值进行比较来评估.
主要成果:
- 在评估的AI工具中,ChatGPT表现出优越的性能,显示出强大的PK代码结构和语法.
- 人工智能生成的模型表现出高精度,关键参数如清除率 (Cl) 和分布量 (Vc,Vp) 的差异很小.
- 验证指标 (AFE,AAFE,MPE) 表明了人工智能生成模型的可靠性.
结论:
- 生成性AI可以有效地提取PK数据,在R中构建人口PK模型,并创建可视化.
- 人工智能工具,特别是ChatGPT,显示出有很大的潜力来帮助PK专业人士,即使是那些没有广泛的编程经验的人.
- 专家支持对于有效地利用人工智能在PK建模和确保可重现性至关重要.
相关概念视频
Pharmacokinetic Models: Overview
1.9K
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
1.9K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
243
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...
243
Pharmacokinetic Models: Comparison and Selection Criterion
341
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
341
Mechanistic Models: Overview of Compartment Models
362
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
362
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
495
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
495
Model Approaches for Pharmacokinetic Data: Physiological Models
249
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
249


