人工智能驱动的经皮给药系统。

IF 9.6 2区 医学 Q1 ENGINEERING, BIOMEDICAL
Farzaneh Sabbagh, Anna Zakrzewska, Daniel Rybak, Julia Król, Asad Abdi, Paweł Nakielski, Filippo Pierini
{"title":"人工智能驱动的经皮给药系统。","authors":"Farzaneh Sabbagh, Anna Zakrzewska, Daniel Rybak, Julia Król, Asad Abdi, Paweł Nakielski, Filippo Pierini","doi":"10.1002/adhm.202503030","DOIUrl":null,"url":null,"abstract":"<p><p>Transdermal drug delivery systems (TDDSs) offer non-invasive therapy but face persistent challenges. Artificial intelligence (AI) transforms TDDSs by leveraging machine learning (ML) and predictive analytics to address these barriers. ML models predict drug entrapment with 93.0% accuracy, streamlining development. AI enhances transdermal patch formulations by forecasting drug release kinetics, skin penetration, and stability, minimizing reliance on costly clinical trials. Through virtual screening, AI identifies novel drug candidates and permeation enhancers, accelerating innovation. In microneedle systems, AI optimizes geometries, materials, and drug loading, improving precision and personalization. AI-integrated biosensors enable real-time monitoring, supporting adaptive dosing tailored to individual physiological profiles. Compared to traditional modeling, AI provides superior accuracy and scalability, handling complex datasets to reveal non-linear relationships. Despite challenges like data quality and privacy concerns, AI's integration with 3-dimensional printing and stimuli-responsive materials drives the development of personalized, efficient transdermal therapies. This perspective highlights AI's critical role in advancing therapeutic efficacy and patient-centric care in TDDSs, uniquely combining predictive modeling with real-time monitoring to envision next-generation personalized transdermal delivery systems.</p>","PeriodicalId":113,"journal":{"name":"Advanced Healthcare Materials","volume":" ","pages":"e03030"},"PeriodicalIF":9.6000,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Transdermal Drug Delivery Systems Powered by Artificial Intelligence.\",\"authors\":\"Farzaneh Sabbagh, Anna Zakrzewska, Daniel Rybak, Julia Król, Asad Abdi, Paweł Nakielski, Filippo Pierini\",\"doi\":\"10.1002/adhm.202503030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Transdermal drug delivery systems (TDDSs) offer non-invasive therapy but face persistent challenges. Artificial intelligence (AI) transforms TDDSs by leveraging machine learning (ML) and predictive analytics to address these barriers. ML models predict drug entrapment with 93.0% accuracy, streamlining development. AI enhances transdermal patch formulations by forecasting drug release kinetics, skin penetration, and stability, minimizing reliance on costly clinical trials. Through virtual screening, AI identifies novel drug candidates and permeation enhancers, accelerating innovation. In microneedle systems, AI optimizes geometries, materials, and drug loading, improving precision and personalization. AI-integrated biosensors enable real-time monitoring, supporting adaptive dosing tailored to individual physiological profiles. Compared to traditional modeling, AI provides superior accuracy and scalability, handling complex datasets to reveal non-linear relationships. Despite challenges like data quality and privacy concerns, AI's integration with 3-dimensional printing and stimuli-responsive materials drives the development of personalized, efficient transdermal therapies. This perspective highlights AI's critical role in advancing therapeutic efficacy and patient-centric care in TDDSs, uniquely combining predictive modeling with real-time monitoring to envision next-generation personalized transdermal delivery systems.</p>\",\"PeriodicalId\":113,\"journal\":{\"name\":\"Advanced Healthcare Materials\",\"volume\":\" \",\"pages\":\"e03030\"},\"PeriodicalIF\":9.6000,\"publicationDate\":\"2025-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Healthcare Materials\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1002/adhm.202503030\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Healthcare Materials","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1002/adhm.202503030","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

摘要

经皮给药系统(TDDSs)提供了非侵入性治疗,但面临着持续的挑战。人工智能(AI)通过利用机器学习(ML)和预测分析来解决这些障碍,从而改变tdds。ML模型预测药物夹带的准确率为93.0%,简化了开发。人工智能通过预测药物释放动力学、皮肤渗透和稳定性来增强透皮贴剂配方,最大限度地减少对昂贵的临床试验的依赖。通过虚拟筛选,人工智能识别新的候选药物和渗透增强剂,加速创新。在微针系统中,人工智能优化了几何形状、材料和药物装载,提高了精度和个性化。人工智能集成的生物传感器可实现实时监测,支持根据个人生理特征量身定制的自适应给药。与传统建模相比,人工智能提供了卓越的准确性和可扩展性,可以处理复杂的数据集以揭示非线性关系。尽管存在数据质量和隐私问题等挑战,但人工智能与三维打印和刺激反应材料的结合推动了个性化、高效透皮疗法的发展。这一观点强调了人工智能在提高TDDSs治疗疗效和以患者为中心的护理方面的关键作用,将预测建模与实时监测独特地结合起来,设想下一代个性化透皮给药系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transdermal Drug Delivery Systems Powered by Artificial Intelligence.

Transdermal drug delivery systems (TDDSs) offer non-invasive therapy but face persistent challenges. Artificial intelligence (AI) transforms TDDSs by leveraging machine learning (ML) and predictive analytics to address these barriers. ML models predict drug entrapment with 93.0% accuracy, streamlining development. AI enhances transdermal patch formulations by forecasting drug release kinetics, skin penetration, and stability, minimizing reliance on costly clinical trials. Through virtual screening, AI identifies novel drug candidates and permeation enhancers, accelerating innovation. In microneedle systems, AI optimizes geometries, materials, and drug loading, improving precision and personalization. AI-integrated biosensors enable real-time monitoring, supporting adaptive dosing tailored to individual physiological profiles. Compared to traditional modeling, AI provides superior accuracy and scalability, handling complex datasets to reveal non-linear relationships. Despite challenges like data quality and privacy concerns, AI's integration with 3-dimensional printing and stimuli-responsive materials drives the development of personalized, efficient transdermal therapies. This perspective highlights AI's critical role in advancing therapeutic efficacy and patient-centric care in TDDSs, uniquely combining predictive modeling with real-time monitoring to envision next-generation personalized transdermal delivery systems.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Advanced Healthcare Materials
Advanced Healthcare Materials 工程技术-生物材料
CiteScore
14.40
自引率
3.00%
发文量
600
审稿时长
1.8 months
期刊介绍: Advanced Healthcare Materials, a distinguished member of the esteemed Advanced portfolio, has been dedicated to disseminating cutting-edge research on materials, devices, and technologies for enhancing human well-being for over ten years. As a comprehensive journal, it encompasses a wide range of disciplines such as biomaterials, biointerfaces, nanomedicine and nanotechnology, tissue engineering, and regenerative medicine.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信