cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
I Wayan Sudarsa
Contact Email
sudarsa@unud.ac.id
Phone
-
Journal Mail Official
globalpharmatechnology@gmail.com
Editorial Address
India
Location
Kota denpasar,
Bali
INDONESIA
Journal of Global Pharma Technology
Published by Universitas Udayana
ISSN : 09758542     EISSN : -     DOI : -
Core Subject : Health,
Medicine & Pharmacology
ournal of Global Pharma Technology is a monthly, open access, Peer review journal of Pharmacy published by JGPT Journal publishes peer-reviewed original research papers, case reports and systematic reviews. The journal allows free access to its contents, which is likely to attract more readers and citations to articles published in JGPT. JGPT publishes original research work that contributes significantly to the scientific knowledge in pharmacy and pharmaceutical sciences- Pharmaceutics, Novel Drug Delivery, Pharmaceutical Technology, Cosmeticology, Biopharmaceutics and Pharmacokinetics, Pharmacognosy, Natural Product Research, Medicinal Chemistry, Computational Chemistry and Molecular Drug Design, Pharmaceutical Analysis, Pharmacology, Pharmacy Practice, Clinical and Hospital Pharmacy, Cell Biology, Genomics and Proteomics, Pharmacogenomics, Bioinformatics, Biotechnology and Applied Computer Technology. For this purpose we would like to ask you to contribute your excellent papers in pharmaceutical sciences.
Arjuna Subject : Kedokteran - Onkologi
Articles 3 Documents
 1 
Search results for , issue "Volume 10 Issue 11 (2018) November 2018" : 3 Documents clear
Natural Bio-Enhancers: Scope for Newer Combinations- A Short Review Nabarun Mukhopadhyay; Saleemulla Khan; Aswatha Ram H N
Journal of Global Pharma Technology Volume 10 Issue 11 (2018) November 2018
Publisher : Journal of Global Pharma Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Bio-enhancers are those chemical entities which promote absorption and augment the bioavailability of accompanyingdrugs and do not exhibit synergy. Natural bio-enhancers are the agents which are obtained naturally and can be used to promote and augment bioavailability of the poorly absorbed drugs, which are administered for long periods, expensive and exert toxic reactions. This approach of using natural bio-enhancer improves the bioavailability, efficacy, thereby reduces the dose and therefore, cost, toxicity and adverse effects. A number of medicinal plants have shown this property of enhancing bioavailability of other drugs. This review work was carried out by thorough searching of different research articles from different online journals from Pubmed, Google scholar, Science direct. We also searched the theories related to the topic from different books obtained from Manipal Health Sciences Library.  In this review we have collected literature of scientifically validated plants having bio-enhancing property. It also describes the scopes of using newer combinations of natural and synthetic productsalongside natural bio-enhancers such as piperine, ginger, and aloes to name a few.For instance, the combination of curcumin with piperine enhances the bioavailability of the former, similarly, bioavailability of paclitaxel, a cytotoxic drug canbe improved by using quercetin combination. Thebio-enhancing effect of trikatu (a traditional Ayurvedic preparation) on cefquinome and tolfenamic acid has also been documented.  
Comparative Study of Phytochemical and Phytomineral Analysis of Selected Peel Powders Gana Manjusha Kondepudi
Journal of Global Pharma Technology Volume 10 Issue 11 (2018) November 2018
Publisher : Journal of Global Pharma Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

 ABSTRACTObjectives: The present study was conducted to evaluate the presence of phytochemicals and mineral elements composition of selected peel powders of Annona sqaumosa, Actinidia deliciosa, Cucumis melo and Mallus pumila. Methods: The phytochemical screening was conducted for the presence of alkaloids, glycosides, phenolics, carbohydrates, aminoacids, saponins, tannins, terpenoids and phytosterols in the selected peel powders. Among all the phytochemicals, phenolics were common in all selected peel powders. The mineral analysis was conducted for both trace elements (Copper, Zinc, Iron, Manganese and Potassium) and toxic elements (Cadmium and Lead). Results: The results of the study indicated that all the selected peel powders showed notable trace elements and negligible amount of toxic elements. Conclusion: Based on the results it was concluded that the fruit peels are no more waste but excellent source of phytoconstituents  and minerals. Hence they can be used in the treatment of many diseases.
Computational Analysis of MK2 Protein for HT Carcinoma Cells using Pre-Processing and Characterization Techniques for Cell Death/ Survival Shruti Jain
Journal of Global Pharma Technology Volume 10 Issue 11 (2018) November 2018
Publisher : Journal of Global Pharma Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This paper presents the computational analysis using pre-processing and different characterization of MK2 proteins for cell death/ survival for HT carcinoma cells. Initially data is collected which than pre processed by completing the missing data, removing various outliers, checking whether the data is normal or non- normal. Later various characterisation steps were applied which includes: classification, regression, clustering, association rules etc. Different data variables use different approaches of pre processing and characterisation. In this paper we have collected the different data of MK2 proteins where we have cleaned the data by using various clustering approaches, than regression analysis, correlation matrix and covariance matrixes are calculated. In last we have classified the data by using different machine learning approaches (k-NN, SVM and Neural network). For k-NN we have compared the results of different techniques like chebyshev, city block and Euclidean. For SVM we have used linear, polynomial, RBF and sigmoid function for both types (Type 1 and Type 2) and for neural network we have calculated training, test and validation perfection using different hidden, and output activation function. This paper shows best 10 network using MLP and RBF approach. 

Page 1 of 1 | Total Record : 3

 1 

Filter by Year

2018 2018


Reset
Filter By Issues
All Issue Volume 17 Issue 12 (2025) Dec. 2025 Volume 17 Issue 11 (2025) Nov.2025 Volume 17 Issue 10 (2025) Oct. 2025 Volume 17 Issue 04 (2025) April 2025 Volume 17 Issue 03 (2025) March 2025 Volume 17 Issue 02 (2025) Feb. 2025 Volume 17 Issue 01 (2025) Jan 2025 Volume 16 Issue 12 (2024) Dec. 2024 Volume 16 Issue 11 (2024) November 2024 Volume 16 Issue 10 (2024) October 2024 Volume 16 Issue 09 (2024) September 2024 Volume 16 Issue 08 (2024) August 2024 Volume 16 Issue 07 (2024) July 2024 Volume 16 Issue 06 (2024) June 2024 Volume 16 Issue 05 (2024) May 2024 Volume 16 Issue 04 (2024) April 2024 Volume 16 Issue 03 (2024) March 2024 Volume 16 Issue 02 (2024) February 2024 Volume 16 Issue 01 (2024) January 2024 Volume 14 Issue 05 (2022) May 2022 Volume 13 Issue 05 (2021) May 2021 Volume 13 Issue 04 (2021) April 2021 Volume 13 Issue 03 (2021) March 2021 Volume 13 Issue 02 (2021) Feb. 2021 Volume 13 Issue 01 (2021) Jan. 2021 Volume 12 Issue 12 (2020) Dec. 2020 Volume 12 Issue 11 (2020) Nov. 2020 Volume 12 Issue 10 (2020) Oct. 2020 Volume 12 Issue 09 (2020) Sept. 2020 Volume 12 Issue 08 (2020) Aug. 2020 Volume 12 Issue 07 (2020) July 2020 Volume 12 Issue 06 (2020) June 2020 Volume 12 Issue 05 (2020) May 2020 Volume 12 Issue 04 (2020) April 2020 Volume 12 Issue 03 (2020) March 2020 Volume 12 Issue 02 (2020) Feb. 2020 Volume 12 Issue 01 (2020) Jan. 2020 Volume 12 Issue 08 Volume 11 Issue 12 (2019) December 2019 Volume 11 Issue 11 (2019) November 2019 Volume 11 Issue 10 (2019) October 2019 Volume 11 Issue 09: (2019) September 2019 Volume 11 Issue 09 (2019) September 2019 Volume 11 Issue 08 (2019) Aug. 2019 Volume 11 Issue 07 (2019) July 2019 Volume 11 Issue 06 (2019) June 2019 Volume 11 Issue 05 (2019) May 2019 Volume 11 Issue 04 (2019) April 2019 Volume 11 Issue 03 (2019) March. 2019 Volume 11 Issue 02 (2019) Feb. 2019 Volume 11 Issue 01 (2019) Jan. 2019 Volume 11 Issue 2: 2019 Volume 10 Issue 12. Volume 11 Issue 6. Volume 10 Issue 12 (2018) December 2018 Volume 10 Issue 11 (2018) November 2018 Volume 10 Issue 10 (2018) October 2018 Volume 10 Issue 09: (2018) September 2018 Volume 10 Issue 08: (2018) August 2018 Volume 10 Issue 07: (2018) July 2018 Volume 10 Issue 06: (2018) June 2018 Volume 10 Issue 05: (2018) May2018 Volume 10 Issue 04: (2018) April 2018 Volume 10 Issue 02: (2018) Feb 2018 Volume 10 Issue 01: (2018) Jan. 2018 Volume 10 Issue 10: 2018 Volume 10 Issue 01 Volume 09 Issue 12 Volume 09 Issue 11 Volume 9 Issue 11 . Vol. 9 Issue 7 : 2017 Volume 9 Issue 10 Volume 09 Issue 09 Volume 09 Issue 08 Volume 9 Issue 07 Volume 09 Issue 05 Volume 09 Issue 04 Volume 09 Issue 03 Volume 09 Issue 02 Volume 08 Issue 11 Volume 08 Issue 07 Volume 08 Issue 06 Volume 08 Issue 05 Volume 08 Issue 04 Volume 08 Issue 03 Volume 08 Issue 02 Volume 08 Issue 01 Volume. 9 Issue 6 Volume 08 Issue 10: (2016) October 2016 Volume 08 Issue 09: (2016) September 2016 Volume 12 Issue 01 Volume 11 Issue 07 Volume 11 Issue 05. Volume 11 Issue 04. Volume 11 Issue 03 Volume 11 Issue 01. Volume 08 Issue 08 Volume 04 Issue 02: (2012) February 2012 Volume 03 Issue 06: (2011) June 2011 Volume 03 Issue 04: (2011) April 2011 Volume 02 Issue 10: (2010) Oct.2010 Volume 02 Issue 07: (2010) July 2010 Volume 02 Issue 05: (2010) May 2010 Volume 02 Issue 03: (2010) March 2010 More Issue