Prediction of Broad-Spectrum Pathogen Attachment to Coating Materials for Biomedical Devices.
Prediction of Broad-Spectrum Pathogen Attachment to Coating Materials for Biomedical Devices.
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DOI：
10.1021/acsami.7b14197
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发表时间：
2018-01-10
影响因子：
9.5
通讯作者：
Winkler DA
中科院分区：
文献类型：
--
作者：
Mikulskis P;Hook A;Dundas AA;Irvine D;Sanni O;Anderson D;Langer R;Alexander MR;Williams P;Winkler DA
细菌感染在医疗机构是一个常见的伴随常规程序，如导管插入术和手术部位干预。随着用于管理慢性健康状况和改善生活质量的医疗设备数量的增加，它们的影响变得更加明显。病原体对多种抗生素的耐药性也在增加，使采用安全有效的医疗程序的问题更加复杂。降低与植入和留置医疗器械相关的感染率的一种方法是使用抵抗细菌生物膜形成的聚合物。为了显著加速此类材料的发现，我们首次展示了最先进的机器学习方法如何在单个模型中对多种病原体附着到大型聚合物库中产生定量预测。这种模型有助于设计具有非常低病原体附着的聚合物，这些聚合物将成为植入式或留置医疗设备（如导尿管、人工耳蜗和起搏器）的候选材料。
Bacterial infections in healthcare settings are a frequent accompaniment to both routine procedures such as catheterization and surgical site interventions. Their impact is becoming even more marked as the numbers of medical devices that are used to manage chronic health conditions and improve quality of life increases. The resistance of pathogens to multiple antibiotics is also increasing, adding an additional layer of complexity to the problems of employing safe and effective medical procedures. One approach to reducing the rate of infections associated with implanted and indwelling medical devices is the use of polymers that resist the formation of bacterial biofilms. To significantly accelerate the discovery of such materials, we show how state of the art machine learning methods can generate quantitative predictions for the attachment of multiple pathogens to a large library of polymers in a single model for the first time. Such models facilitate design of polymers with very low pathogen attachment across different bacterial species that will be candidate materials for implantable or indwelling medical devices such as urinary catheters, cochlear implants, and pacemakers.
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影响因子：
46.9
作者：
通讯作者：
--
DOI：
10.1002/qsar.200810173
发表时间：
2009-07-01
期刊：
QSAR & COMBINATORIAL SCIENCE
影响因子：
--
作者：
Burden, F. R.;Winkler, D. A.
通讯作者：
Winkler, D. A.
影响因子：
4.9
作者：
Le, Tu C.;Mulet, Xavier;Winkler, David A.
通讯作者：
Winkler, David A.
影响因子：
6.7
作者：
Harapanahalli AK;Younes JA;Allan E;van der Mei HC;Busscher HJ
通讯作者：
Busscher HJ
影响因子：
5.6
作者：
Alexander DL;Tropsha A;Winkler DA
通讯作者：
Winkler DA