Computational and experimental analyses of anticancer and antibiotic drug adsorption on inner surfaces of infusion tubing
- Authors
- Kang, Ryun; Ha, Juchan; Lee, Solpa; Kang, Ju-Seop; Kim, Hyunsoo; Jang, Yongwoo
- Issue Date
- Feb-2026
- Publisher
- SPRINGER HEIDELBERG
- Keywords
- Polymer; Adsorption; Predictive; Computation/computing; Infrared (IR) spectroscopy
- Citation
- MRS COMMUNICATIONS, v.16, no.1, pp 68 - 77
- Pages
- 10
- Indexed
- SCIE
SCOPUS
- Journal Title
- MRS COMMUNICATIONS
- Volume
- 16
- Number
- 1
- Start Page
- 68
- End Page
- 77
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212113
- DOI
- 10.1557/s43579-025-00876-w
- ISSN
- 2159-6859
2159-6867
- Abstract
- Intravenous drug administration is frequently compromised by therapeutic adsorption onto polyvinyl chloride (PVC), polyurethane (PU), or polyolefin (PO) infusion lines, leading to inaccurate dosing and reduced efficacy. However, there is a notable lack of studies investigating the specific interactions between drugs and polymers at the molecular level. We employed a dual approach using molecular dynamics (MD) simulations to predict the binding energies between four key drugs (docetaxel, etoposide, vancomycin, and meropenem) and three polymer surfaces (PVC, PU, and PO). These computational predictions were experimentally verified by quantifying drug retention on the internal surfaces of the corresponding intravenous lines using Fourier-transform infrared (FT-IR) spectroscopy. MD simulations consistently predicted the lowest binding energies and thus the least adsorption for all the tested drugs on the PO surface. FT-IR analysis directly confirmed these findings, revealing significant drug-specific peaks on the PVC and PU surfaces, but negligible evidence of adsorption on PO. This combined methodology validated PO as an optimal material for minimizing drug loss during infusion. Our approach provides a powerful framework for assessing drug-material compatibility, paving the way for advanced infusion systems that ensure greater accuracy in drug delivery and improved patient outcomes.
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