用大型语言模型为药物协同作用分析构建统一模型
bioRxiv : the preprint server for biology
|April 16, 2025
概括
我们开发了BAITSAO,一种使用大型语言模型嵌入的新型模型,用于准确预测药物协同作用. 这种方法增强了癌症治疗策略,并有助于发现新的药物组合.
科学领域:
- 计算生物学是一种计算生物学.
- 药理学 药理学是指药理学的学科.
- 医学中的人工智能.
背景情况:
- 药物协同作用预测对于治疗癌症等复杂疾病至关重要.
- 现有的方法往往难以处理多样化的数据集,缺乏统一的方法.
研究的目的:
- 介绍BAITSAO,一种用于药物协同效应预测的新型统一模型.
- 为了利用大型语言模型的嵌入,改善药物和细胞系的表征.
- 建立一个强大的管道来处理各种药物协同效应数据集.
主要方法:
- 构建训练数据集使用大语言模型的上下文丰富嵌入.
- 预训练BAITSAO模型与大规模的药物协同效应数据库.
- 采用一个多任务学习框架,精心挑选任务.
主要成果:
- 证明BAITSAO的架构和预培训策略在现有方法上的优势.
- 综合基准分析验证模型的性能.
- 调查BAITSAO的敏感性和独特的功能能力.
结论:
- BAITSAO提供了一种优越的,统一的药物协同效应预测方法.
- 该模型有助于发现新药,分析药物基因相互作用,并预测多种药物协同作用.
- BAITSAO代表了精准医学计算方法的重大进步.
相关概念视频
Combined Effects of Drugs: Antagonism
8.1K
The combined effects of drugs can result in various interactions, of which an important type is antagonism. Antagonism is a mechanism where one drug inhibits or counteracts the effects of another drug. Antagonism can occur through various means, including receptor binding, allosteric modulation, functional interaction, chemical reactions, and pharmacokinetic processes.
The most common type is receptor antagonism, where one drug acts as an antagonist to block the effects of another drug by...
The most common type is receptor antagonism, where one drug acts as an antagonist to block the effects of another drug by...
8.1K
Combined Effects of Drugs: Synergism
3.6K
Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...
Such synergistic combinations...
3.6K
Pharmacokinetic Models: Overview
504
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...
504
Analysis of Population Pharmacokinetic Data
199
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...
199
Agonism and Antagonism: Quantification
258
When drugs are administered, they can elicit either an agonist or antagonist effect on the body. Agonism occurs when a drug activates a specific receptor, triggering a biological response. On the other hand, antagonism happens when a drug binds to the same receptors but blocks their activation, thereby preventing a biological response.
To quantify these effects, researchers use a dose-response curve, which provides valuable information about the potency and efficacy of a drug. Potency refers to...
To quantify these effects, researchers use a dose-response curve, which provides valuable information about the potency and efficacy of a drug. Potency refers to...
258
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
47
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...
47


