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Microengineering and Biomedical Engineering are Used to Identify Predictive Prodrugs in Neuro-Oncology
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Journal of Bioengineering & Biomedical Science

ISSN: 2155-9538

Open Access

Commentary - (2022) Volume 12, Issue 9

Microengineering and Biomedical Engineering are Used to Identify Predictive Prodrugs in Neuro-Oncology

Gianfranco Chibbaro*
*Correspondence: Gianfranco Chibbaro, Department of Neurosurgery, Toronto Western Hospital, University of Toronto, Toronto, ON M5T 2S8, Canada, Email:
Department of Neurosurgery, Toronto Western Hospital, University of Toronto, Toronto, ON M5T 2S8, Canada

Received: 24-Aug-2022, Manuscript No. jbbs-23-87850; Editor assigned: 26-Aug-2022, Pre QC No. P-87850; Reviewed: 08-Sep-2022, QC No. Q-87850; Revised: 15-Sep-2022, Manuscript No. R-87850; Published: 22-Sep-2022 , DOI: 10.37421/2155-9538.22.12.321
Citation: Chibbaro, Gianfranco. “Microengineering and Biomedical Engineering are used to Identify Predictive Prodrugs in Neuro-Oncology.” J Bioengineer & Biomedical Sci 12 (2022): 321.
Copyright: © 2022 Chibbaro G. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Description

For the purpose of streamlining medical screening for early and ultraearly analysis of numerous diseases, including cancer, the identification of appropriate biomarkers is crucial in quantitative neuroscience. Quantitative organic signatures of a particular physiological state or pathological condition are known as biomarkers, and they are utilized in numerous fields of medicine to estimate the likelihood of new diseases developing, the rate at which they progress, and their impact. In my opinion, additional applications of biomarkers include: In point of fact, a biosignature is typically referred to as a profile of information gathered from imaging, genomics, and proteomics testing that consists of two or more biomarkers. When compared to the sensitivity and specificity of each individual measure, a composite measure, such as a biosignature, can typically significantly enhance the diagnostic protocols' sensitivity and specificity [1].

As biomarkers became incorporated into drug development, clinical trials, and current medicine, they gained prominence and assumed a major role in the constant dialogue among numerous stakeholders, including the scientific community, multinational pharmaceutical corporations, high-tech biomedical startups, investors, and certain patients. In recent years, because of the interest in their role, there has been a need for a common understanding of biomarkers and consistent language. For instance, the first version of the thesaurus included in the Biomarkers, EndpointS, and other Tools (BEST) resource was published by the Food and Drug Administration (FDA) and the National Institutes of Health (NIH) at the beginning of 2016. This resource was created to harmonize and clarify terms utilized in translational science and scientific product development and to provide a common ground for discussion among these groups. The BEST tool accurately divides biomarkers into the following more homogeneous groups based on their distinct functions: susceptibility risk biomarkers, diagnostic biomarkers, monitoring biomarkers, prognostic biomarkers, predictive biomarkers, and pharmacodynamic response biomarkers [2].

Before being implemented into clinical practice, each group of biomarkers intended for use in patient care is subjected to a rigorous evaluation. This properly described method for determining their accuracy and reliability applies equally to the analytical assessments that are proposed to be used to measure a candidate biomarker. A great deal of attention is currently being paid to high assurance and, in particular, assay validation because the integration of multiple technologies is essential to innovation and proved crucial to not only the identification and characterization of biomarkers but additionally their validation. The "European Society of Medical Oncologists (ESMO) Translational Research and Personalised Medicine Working Group" has developed a standardized word list of applicable terms in order to improve the readability of the language utilized by oncologists and fundamental scientists within the context of precision medicine, in a manner that is analogous to what was carried out with the BEST resource.

This group of workers highlighted five significant areas of interest: 1) decision-making mechanisms; 2) characteristics of molecular changes; 3) characteristics of tumors; 4) scientific trials and statistics; and 5) new lookup tools. In light of the latter's significance, the purpose of this systematic evaluation is to summarize the contributions made by nanotechnology and biomedical engineering to the definition of clinically significant predictive biomarkers with a plausible application in the treatment of intelligence tumor patients. Particularly, we will focus on recent advances in quantitative neuroscience, particularly those that are unexpectedly gaining ground in modern medical practice and, as a result, continue to hold the potential to advance personalized treatment in neuro-oncology. This article aims to provide readers with an overview of the most recent research [3] that highlights the role of new devices based on recent discoveries in the fields of nanotechnology and biomedical engineering in medical and purposeful profiling in neuro-oncology.

Specifics of the Study: This article focuses on fundamental sciences and medical research that have utilized advancements in nanotechnology or biomedical engineering applied to genomics, epigenomics, and proteomics to validate existing biomarkers and biosignatures or to discover new ones with the potential to predict medical and surgical outcomes in patients with talent tumors (of any kind, essential and secondary Genius tumors). This is in response to the search query that was presented earlier. Although any experimental paper, including research using animal models, has been included in this review, the following types of articles have not: articles, letters, editorials and comments, assembly abstracts, and books provide an overview. Sources of Information: In the past, to find relevant studies, a systematic search was carried out in MEDLINE, MEDLINE in Process, EMBASE, and/or the Cochrane Central Register of Controlled Trials [4].

Method of Search: In collaboration with a librarian who specializes in neuroscience research, we developed a search strategy. The strategy was initially developed for MEDLINE before being precisely adapted to the various databases. At the time of querying all databases (November 2017), the following search terms were utilized: Brain Tumors, Nanotechnology, Biomedical Engineering, Biomarkers, Biosignatures, Clinical Outcomes, and Surgical Outcomes are just a few examples. There were no other restrictions placed on the type of study (basis science/clinical study) and only Englishlanguage research was considered for inclusion. This search's effects have been thoroughly examined: initially by four authors with extensive experience conducting straightforward laboratory studies, and finally by four authors with medical knowledge regarding the administration of genius tumors. A comprehensive review with all authors was carried out to ensure that only experimental research provided: a) A substances and strategies section with a specific description of new screening methods based on nanotechnology or biomedical engineering and b) a results section describing their correlation with medical and surgical outcomes were retained for the same evaluation and record in this systematic review [5].

Acknowledgement

None.

Conflict of Interest

None.

References

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Citations: 307

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