Abstract
Nanocarriers’ usage turned out to be a revolutionizing factor in the field of medical diagnosis and therapies. One of these therapies includes drug delivery system, where the nanocarriers are utilized for targeted and controlled delivery of drug to the diseased sites. Toxicity is one of the crucial issues which can arise during this process and needs to be addressed seriously and as early as possible. This paper reports an automated system for the relatively new and undiscovered area, where cell detection and evaluation play a major role in toxicity prediction of nanocarriers during the drug delivery process. The toxicity level was decided on the basis of dead cells count present in the microscopic images. The algorithm takes a few seconds to run and the overall accuracy of the proposed algorithm was found to be approx. 97% and 83% for different sets of images. The various image peculiarities which led to error include high cells clustering, poor contrast, and noisy background
Highlights
Nanotechnology has prominently advanced in biomedical applications such as drugs/ gene delivery systems, probing of DNA structure, tissue engineering etc. with the utilization of nanoparticles (NP)
This paper focuses on relatively new or undiscovered area, where cell detection and estimation plays an important role in toxicity prediction of drug delivery nanocarriers
The current study has developed an image analysis framework which could possibly be utilized for regular toxicity determination of a compound in drug delivery system
Summary
Nanotechnology has prominently advanced in biomedical applications such as drugs/ gene delivery systems, probing of DNA structure, tissue engineering etc. with the utilization of nanoparticles (NP). One of the main reasons for using these nanoparticles in therapeutic applications is their small size [1, 2] that makes them eligible for fast absorption and release behaviour of bioactive molecules including drugs. The prevailing synthetic organic chemistry has begun a new pathway to design these nanomaterials (NM) using different chemical compositions, diverse material resources, and various synthetic routes. All these advancements have resulted in a breakneck increment in the requirement of various types of nanomaterials in biological applications. The small size of NM exposes their large surface area to cellular units that can lead to some toxic effects
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