scholarly journals Label-Free Bioelectrochemical Methods for Evaluation of Anticancer Drug Effects at a Molecular Level

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1812 ◽  
Author(s):  
Francesco Tadini-Buoninsegni ◽  
Ilaria Palchetti
Keyword(s):  
Anticancer Drugs ◽  
Anticancer Drug ◽  
Drug Effects ◽  
Cost Effective ◽  
Research Area ◽  
Screening Methods ◽  
Label Free ◽  
Supported Membranes ◽  
Drug Candidates ◽  
Novel Drug

Cancer is a multifactorial family of diseases that is still a leading cause of death worldwide. More than 100 different types of cancer affecting over 60 human organs are known. Chemotherapy plays a central role for treating cancer. The development of new anticancer drugs or new uses for existing drugs is an exciting and increasing research area. This is particularly important since drug resistance and side effects can limit the efficacy of the chemotherapy. Thus, there is a need for multiplexed, cost-effective, rapid, and novel screening methods that can help to elucidate the mechanism of the action of anticancer drugs and the identification of novel drug candidates. This review focuses on different label-free bioelectrochemical approaches, in particular, impedance-based methods, the solid supported membranes technique, and the DNA-based electrochemical sensor, that can be used to evaluate the effects of anticancer drugs on nucleic acids, membrane transporters, and living cells. Some relevant examples of anticancer drug interactions are presented which demonstrate the usefulness of such methods for the characterization of the mechanism of action of anticancer drugs that are targeted against various biomolecules.

Molecular Topological Properties of Alkylating Agents Based Anticancer Drug Candidates Via Some Ve-degree Topological Indices

2020 ◽  
Vol 16 (2) ◽  
pp. 190-195 ◽  
Author(s):  
Süleyman Ediz ◽  
Murat Cancan
Keyword(s):  
Anticancer Drugs ◽  
Anticancer Drug ◽  
Alkylating Agents ◽  
Topological Indices ◽  
Pharmacological Properties ◽  
Topological Properties ◽  
Drug Candidates ◽  
New Drug ◽  
Atom Bond ◽  
Dual Target

Background: Reckoning molecular topological indices of drug structures gives the data about the underlying topology of these drug structures. Novel anticancer drugs have been leading by researchers to produce ideal drugs. Materials and Methods: Pharmacological properties of these new drug agents explored by utilizing simulation strategies. Topological indices additionally have been utilized to research pharmacological properties of some drug structures. Novel alkylating agents based anticancer drug candidates and ve-degree molecular topological indices have been introduced recently. Results and Conclusion: In this study we calculate ve-degree atom-bond connectivity, harmonic, geometric-arithmetic and sum-connectivity molecular topological indices for the newly defined alkylating agents based dual-target anticancer drug candidates.

scholarly journals ANTICANCER ACTIVITY OF UPAVISHA ARKA: AN OVERVIEW

2020 ◽  
Vol 9 (6) ◽  
pp. 175-181
Author(s):  
Chandekar Deepali Boudhadas ◽  
Pawade Uday Venkatrao ◽  
Nikam Ashwin Vithalrao ◽  
Anjankar Meghsham Pramodrao
Keyword(s):  
Anticancer Activity ◽  
Anticancer Drugs ◽  
Anticancer Drug ◽  
Cost Effective ◽  
In Vivo Studies ◽  
Calotropis Procera ◽  
Calotropis Gigantea ◽  
Natural Derivative

Cancer is one amongst the dreadful diseases of present century. The incidence of cancer is increasing worldwide. Every year about 8,00,000 new cancer patients get registered with the national cancer registry program in India. Ayurveda an ancient Indian medicine science describes many useful herbal drugs for such types of advanced diseases. Upavisha the plant poisons of low potency are mentioned in Agadtantra. Arka (Calotropis procera/ Calotropis gigantea) is one among these Upavisha is emerging as an effective anticancer drug. It shows various pharmacological activities such as Anticancer, Antimicrobial, Antiimplantation etc. Different parts of Arka are used to treat cancer. In current scenario number of synthetic anticancer drugs are used to treat cancer. These synthetic anticancer drugs are expensive and shows harmful adverse effects. Upavisha like Arka which is natural derivative may be cost effective & less harmful as Anticancer drug. Anticancer activity of Calotropis procera/Calotropis gigantea is reported in scientific journals. This review summarizes various In Vitro and In Vivo studies of anticancer activity of Upavisha Arka.

A Review on Fast Dissolving Tablet

2017 ◽  
Vol 8 (03) ◽  
Author(s):  
Sagar T. Malsane ◽  
Smita S. Aher ◽  
R. B. Saudagar
Keyword(s):  
Drug Delivery ◽  
Patient Compliance ◽  
Research Area ◽  
Oral Route ◽  
Dosage Forms ◽  
The Novel ◽  
The Past ◽  
Orally Disintegrating Tablets ◽  
Novel Drug ◽  
Experience Difficulty

Oral route is presently the gold standard in the pharmaceutical industry where it is regarded as the safest, most economical and most convenient method of drug delivery resulting in highest patient compliance. Over the past three decades, orally disintegrating tablets (FDTs) have gained considerable attention due to patient compliance. Usually, elderly people experience difficulty in swallowing the conventional dosage forms like tablets, capsules, solutions and suspensions because of tremors of extremities and dysphagia. In some cases such as motion sickness, sudden episodes of allergic attack or coughing, and an unavailability of water, swallowing conventional tablets may be difficult. One such problem can be solved in the novel drug delivery system by formulating “Fast dissolving tablets” (FDTs) which disintegrates or dissolves rapidly without water within few seconds in the mouth due to the action of superdisintegrant or maximizing pore structure in the formulation. The review describes the various formulation aspects, superdisintegrants employed and technologies developed for FDTs, along with various excipients, evaluation tests, marketed formulation and drugs used in this research area.

Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs

2019 ◽  
Vol 20 (5) ◽  
pp. 488-500 ◽  
Author(s):  
Yan Hu ◽  
Yi Lu ◽  
Shuo Wang ◽  
Mengying Zhang ◽  
Xiaosheng Qu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Drug Design ◽  
Anticancer Drugs ◽  
Nearest Neighbor ◽  
Cost Effective ◽  
Support Vector ◽  
Learning Approaches ◽  
K Nearest Neighbor ◽  
Activity Prediction ◽  
Linear Discriminant

Background: Globally the number of cancer patients and deaths are continuing to increase yearly, and cancer has, therefore, become one of the world&#039;s highest causes of morbidity and mortality. In recent years, the study of anticancer drugs has become one of the most popular medical topics. </P><P> Objective: In this review, in order to study the application of machine learning in predicting anticancer drugs activity, some machine learning approaches such as Linear Discriminant Analysis (LDA), Principal components analysis (PCA), Support Vector Machine (SVM), Random forest (RF), k-Nearest Neighbor (kNN), and Naïve Bayes (NB) were selected, and the examples of their applications in anticancer drugs design are listed. </P><P> Results: Machine learning contributes a lot to anticancer drugs design and helps researchers by saving time and is cost effective. However, it can only be an assisting tool for drug design. </P><P> Conclusion: This paper introduces the application of machine learning approaches in anticancer drug design. Many examples of success in identification and prediction in the area of anticancer drugs activity prediction are discussed, and the anticancer drugs research is still in active progress. Moreover, the merits of some web servers related to anticancer drugs are mentioned.

scholarly journals Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pusheng Quan ◽  
Kai Wang ◽  
Shi Yan ◽  
Shirong Wen ◽  
Chengqun Wei ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Target ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Drug Candidates ◽  
Novel Drug

AbstractThis study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

scholarly journals Utilising Commercially Fabricated Printed Circuit Boards as an Electrochemical Biosensing Platform

Micromachines ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 793
Author(s):  
Uroš Zupančič ◽  
Joshua Rainbow ◽  
Pedro Estrela ◽  
Despina Moschou
Keyword(s):  
Printed Circuit Boards ◽  
Electrochemical Sensors ◽  
Cost Effective ◽  
Electrochemical Sensing ◽  
Label Free ◽  
Circuit Boards ◽  
Printed Circuit ◽  
Sensing Applications ◽  
Electrochemical Biosensing ◽  
Pre Treatment

Printed circuit boards (PCBs) offer a promising platform for the development of electronics-assisted biomedical diagnostic sensors and microsystems. The long-standing industrial basis offers distinctive advantages for cost-effective, reproducible, and easily integrated sample-in-answer-out diagnostic microsystems. Nonetheless, the commercial techniques used in the fabrication of PCBs produce various contaminants potentially degrading severely their stability and repeatability in electrochemical sensing applications. Herein, we analyse for the first time such critical technological considerations, allowing the exploitation of commercial PCB platforms as reliable electrochemical sensing platforms. The presented electrochemical and physical characterisation data reveal clear evidence of both organic and inorganic sensing electrode surface contaminants, which can be removed using various pre-cleaning techniques. We demonstrate that, following such pre-treatment rules, PCB-based electrodes can be reliably fabricated for sensitive electrochemical biosensors. Herein, we demonstrate the applicability of the methodology both for labelled protein (procalcitonin) and label-free nucleic acid (E. coli-specific DNA) biomarker quantification, with observed limits of detection (LoD) of 2 pM and 110 pM, respectively. The proposed optimisation of surface pre-treatment is critical in the development of robust and sensitive PCB-based electrochemical sensors for both clinical and environmental diagnostics and monitoring applications.

Highly regioselective and stereoselective synthesis of C-Aryl glycosides via Nickel-catalyzed ortho-C-H glycosylation of 8-aminoquinoline benzamides

2021 ◽  
Author(s):  
Wei-Yu Shi ◽  
Ya-Nan Ding ◽  
Nian Zheng ◽  
Xue-Ya Gou ◽  
Zhe Zhang ◽  
...  
Keyword(s):  
Stereoselective Synthesis ◽  
Cost Effective ◽  
Drug Candidates ◽  
Aryl Glycosides ◽  
Glycosylation Reaction

C-Aryl glycosides are of high value as drug candidates. Here a novel and cost-effective nickel catalyzed ortho-CAr-H glycosylation reaction with high regioselectivity and excellent α-selectivity is described. This method shows...

Plasma enhanced label-free immunoassay for alpha-fetoprotein based on a U-bend fiber-optic LSPR biosensor

RSC Advances ◽  
2015 ◽  
Vol 5 (31) ◽  
pp. 23990-23998 ◽  
Author(s):  
Gaoling Liang ◽  
Zhongjun Zhao ◽  
Yin Wei ◽  
Kunping Liu ◽  
Wenqian Hou ◽  
...  
Keyword(s):  
Surface Plasmon Resonance ◽  
Surface Plasmon ◽  
Plasmon Resonance ◽  
Localized Surface Plasmon Resonance ◽  
Fiber Optic ◽  
Cost Effective ◽  
Alpha Fetoprotein ◽  
Localized Surface Plasmon ◽  
Label Free

A simple, label-free and cost-effective localized surface plasmon resonance (LSPR) immunosensing method was developed for detection of alpha-fetoprotein (AFP).

scholarly journals Missing Novelty in Drug Development

2021 ◽  
Author(s):  
Joshua Krieger ◽  
Danielle Li ◽  
Dimitris Papanikolaou
Keyword(s):  
Radical Innovation ◽  
Chemical Similarity ◽  
Net Worth ◽  
Drug Candidates ◽  
Pharmaceutical Firms ◽  
External Finance ◽  
Fda Approval ◽  
Novel Drugs ◽  
Positive Shock ◽  
Novel Drug

Abstract We provide evidence that risk aversion leads pharmaceutical firms to underinvest in radical innovation. We introduce a new measure of drug novelty based on chemical similarity and show that firms face a risk-reward trade-off: novel drug candidates are less likely to obtain FDA approval but are based on more valuable patents. Consistent with a simple model of costly external finance, we show that a positive shock to firms’ net worth leads firms to develop more novel drugs. This suggests that even large firms may behave as though they are risk averse, reducing their willingness to investment in potentially valuable radical innovation.

Developing novel chemical entities for the treatment of lysosomal storage disorders: an academic perspective

2015 ◽  
Vol 309 (12) ◽  
pp. F996-F999 ◽  
Author(s):  
James A. Shayman
Keyword(s):  
Drug Targets ◽  
Lysosomal Storage ◽  
Federal Drug Administration ◽  
Drug Candidates ◽  
Gaucher Disease Type 1 ◽  
Biotechnology Companies ◽  
Approved Drugs ◽  
Novel Drug ◽  
Early Drug

Historically, most Federal Drug Administration-approved drugs were the result of “in-house” efforts within large pharmaceutical companies. Over the last two decades, this paradigm has steadily shifted as the drug industry turned to startups, small biotechnology companies, and academia for the identification of novel drug targets and early drug candidates. This strategic pivot has created new opportunities for groups less traditionally associated with the creation of novel therapeutics, including small academic laboratories, for engagement in the drug discovery process. A recent example of the successful development of a drug that had its origins in academia is eliglustat tartrate, an oral agent for Gaucher disease type 1.

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