相关实验视频

Updated: Jan 17, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

托克斯伯特:一种可解释的AI框架,用于提高对药物不良反应和结构洞察力的预测

Yujie He¹, Xiang Lv¹, Wulin Long¹

¹College of Chemistry, Sichuan University, Chengdu, 610064, China.

Journal of pharmaceutical analysis

|September 22, 2025

概括

ToxBERT是一种新型变压器模型,可以从分子结构准确预测药物诱导的药物不良反应 (ADR). 它通过提供更好的解释性和识别与ADRs相关的关键子结构来改进现有方法.

科学领域:

计算化学是一种计算化学.
药理学药理学是指药理学的学科.
药物发现药物发现

背景情况:

准确预测药物诱导的药物不良反应 (ADRs) 对药物安全和公共健康至关重要.
当前的ADR预测模型需要提高准确性和可解释性,通常依赖于有偏见的手动特征选择.

研究的目的:

从分子结构中开发一个高效和可解释的模型来预测ADRs.
解决现有模型的局限性,包括缺乏可解释性和依赖手动功能选择.

主要方法:

提出ToxBERT,一个高效的变压器编码器模型,利用注意力和掩盖机制.
应用ToxBERT到简化分子输入线输入系统 (SMILES) 表示,用于ADR预测.
评估模型性能使用特定ADR接收器操作特征曲线 (AUROC) 下的面积.

主要成果:

托克斯伯特在药物诱导的QT延长 (DIQT) 中获得了0.839的AUROC得分,在狂肌溶解中获得了0.759的得分,在肝损伤中获得了0.664的得分.
在预测这些副作用方面,ToxBERT的表现优于之前的研究.
该模型成功识别了与特定副作用相关的药物亚结构,提高了可解释性.

结论:

托克斯伯特 (ToxBERT) 是一个有价值的工具,用于预测药物诱导的不良反应,具有高准确性和更好的解释性.
该模型有助于理解ADR机制,并减轻药物发现中的风险.
托克斯伯特 (ToxBERT) 为提高药物安全性评估提供了一个有希望的方法.

关键词:

深度学习是一种深度学习.药物安全药物安全药物诱导的药物不良反应可以解释性解释性结构性警报是指结构性警报.

相关概念视频

Pharmacovigilance

Pharmacovigilance

Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...

Structure-Activity Relationships and Drug Design

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...

Predicting Reaction Outcomes

Predicting Reaction Outcomes

Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...

Drug Discovery: Overview

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...