Integration of biosensors and drug delivery technologies for early detection and chronic management of illness
Open accessAbstract
Recent advances in biosensor design and sensing efficacy need to be amalgamated with research in responsive drug delivery systems for building superior health or illness regimes and ensuring good patient compliance. A variety of illnesses require continuous monitoring in order to have efficient illness intervention. Physicochemical changes in the body can signify the occurrence of an illness before it manifests. Even with the usage of sensors that allow diagnosis and prognosis of the illness, medical intervention still has its downfalls. Late detection of illness can reduce the efficacy of therapeutics. Furthermore, the conventional modes of treatment can cause side-effects such as tissue damage (chemotherapy and rhabdomyolysis) and induce other forms of illness (hepatotoxicity). The use of drug delivery systems enables the lowering of side-effects with subsequent improvement in patient compliance. Chronic illnesses require continuous monitoring and medical intervention for efficient treatment to be achieved. Therefore, designing a responsive system that will reciprocate to the physicochemical changes may offer superior therapeutic activity. In this respect, integration of biosensors and drug delivery is a proficient approach and requires designing an implantable system that has a closed loop system. This offers regulation of the changes by means of releasing a therapeutic agent whenever illness biomarkers prevail. Proper selection of biomarkers is vital as this is key for diagnosis and a stimulation factor for responsive drug delivery. By detecting an illness before it manifests by means of biomarkers levels, therapeutic dosing would relate to the severity of such changes. In this review various biosensors and drug delivery systems are discussed in order to assess the challenges and future perspectives of integrating biosensors and drug delivery systems for detection and management of chronic illness.
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Because the major carrier density is proportional to the glucose concentration, the relative change in resistance (ΔR/R0) of the sensor can be detected as a function of the glucose concentration.
“Because the major carrier density is proportional to the glucose concentration, we can detect the relative change in resistance (ΔR/R0) of the sensor as a function of the glucose concentration generated from the above reaction processes (14, 38).”
From Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays (2018) · cites this paper as [38]
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References 171 · Cited by 92
Research works printed but not linked: 3
- [27]Kwon Y.M. Kim S.W. Polymeric Drug Delivery Systems Kwon G.S. Taylor & Francis group New York, NY, USA 2005 Volume 148 Chapter 6 251 264
- [57]Ramanavieius A. Herberg F.W. Hutschenreiter S. Zimmermann B. Lapenaite I. Kausaite A. Finkelsteinas A. Ramanavieiene A. biological application of surface Plasmon resonance biosensors (review) Acta Med. Litu. 2005 12 1 9
- [165]Shah V. Chavda E. Injecting new ideas into drug delivery systems: A brief review on microchips as controlled drug delivery systems IJRPB 2011 1 1 7
- Authors
- Ngoepe, M., Choonara, Y., Tyagi, C., Tomar, L., Du Toit, L., Kumar, P., Ndesendo, V., & Pillay, V.
- Affiliations
- University of the Witwatersrand (ZA)
- Department of Pharmacy and Pharmacology, Faculty of Health Sciences, University of the Witwatersrand, 7 York Road, Parktown, 2193, Johannesburg, South Africa
- St. John's University of Tanzania (TZ)
- Corresponding author
- Pillay, Viness
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2013-06-14
- Volume
- 13
- Issue
- 6
- Pages
- 7680-7713
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC3715220
- OpenAlex
- W2048549892
- Cited by
- 92
- References
- 171
- Citations by year
- 2026: 2 · 2025: 17 · 2024: 12 · 2023: 12 · 2022: 11 · 2021: 6 · 2020: 7 · 2019: 4 · 2018: 7 · 2017: 3 · 2016: 4 · 2015: 3 · 2014: 3
- FWCI
- 0.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrochemical sensors and biosensors
- Physical Sciences › Engineering › Biomedical Engineering › Biosensors and Analytical Detection
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Advanced Drug Delivery Systems
- Keywords
- biosensors, stimuli-responsive drug delivery, biomedical implants, closed-loop systems, biomarkers, early disease detection, chronic disease management, medication adherence, adverse drug reactions, targeted drug release
- MeSH terms
- Blood Glucose, Cardiovascular Diseases, Cholesterol, Chronic Disease, Diabetes Mellitus, Humans, Biosensing Techniques, Biomarkers, Drug Delivery Systems, Early Diagnosis, Electrochemical Techniques
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