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Cited by 268

The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.

On-Site Therapeutic Drug Monitoring

Open access
Ates, H. Ceren, Roberts, Jason A., Lipman, Jeffrey, Cass, Anthony E.G., Urban, Gerald A., Dincer, Can·2020·Trends in Biotechnology

Abstract

Recent technological advances have stimulated efforts to bring personalized medicine into practice. Yet, traditional application fields like therapeutic drug monitoring (TDM) have remained rather under-appreciated. Owing to clear dose-response relationships, TDM could improve patient outcomes and reduce healthcare costs. While chromatography-based routine practices are restricted due to high costs and turnaround times, biosensors overcome these limitations by offering on-site analysis. Nevertheless, sensor-based approaches have yet to break through for clinical TDM applications, due to the gap between scientific and clinical communities. We provide a critical overview of current TDM practices, followed by a TDM guideline to establish a common ground across disciplines. Finally, we discuss how the translation of sensor systems for TDM can be facilitated, by highlighting the challenges and opportunities.

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Metadata

Authors
Ates, H. C., Roberts, J. A., Lipman, J., Cass, A. E. G., Urban, G. A., & Dincer, C.
Venue
Trends in Biotechnology
Publisher
Elsevier BV
Published
2020-11
Volume
38
Issue
11
Pages
1262-1277
ISSN
0167-7799 (ISSN-L)
OpenAlex
W3015167435
Cited by
268
References
60
FWCI
1.23
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: On-Site Therapeutic Drug Monitoring. https://app.cochat.ai/papers/10.1016/j.tibtech.2020.03.001
The paper
Ates, H. C., Roberts, J. A., Lipman, J., Cass, A. E. G., Urban, G. A., & Dincer, C. (2020). On-Site Therapeutic Drug Monitoring. Trends in Biotechnology. https://doi.org/10.1016/j.tibtech.2020.03.001

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.