Integrative QSPR and VIKOR Multi-Criteria Decision Analysis for Optimizing Anti-Parkinson Drug Candidates
Clicks: 1
ID: 312905
2024
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
0.0
/100
1 views
0 readers
AI Quality Assessment
Not analyzed
Readership in this journal
Ranked #322 of 705 articles by views in Journal of Computing & Biomedical Informatics
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Developing efficient anti-Parkinson medications poses a considerable challenge in the field of pharmacology, necessitating sophisticated techniques for assessing and refining potential therapeutic agents. This research presents a unified method that merges Quantitative Structure-Property Relationship (QSPR) analysis with VIKOR Multi-Criteria decision-making (MCDM) to enhance the selection and refinement of anti-Parkinson drug candidates. QSPR analysis aims to elucidate the connection between molecular descriptors and the pharmacological characteristics of different anti-Parkinson compounds. By pinpointing essential molecular elements that influence both drug efficacy and safety, QSPR models yield predictive insights that direct the design and choice of new drug candidates. Subsequently, the VIKOR method is utilized to prioritize and choose the most promising drug candidates according to their anticipated performance. This method incorporates a range of pharmacological and safety considerations, enabling a balanced evaluation that weighs therapeutic advantages against potential risks. The collaborative QSPR-VIKOR approach facilitates a thorough assessment of drug candidates, reconciling conflicting goals and offering a definitive ranking system for decision-making. By integrating the benefits of both strategies, this study seeks to identify ideal anti-Parkinson drug candidates with improved efficacy and safety profiles. The results offer a solid groundwork for the systematic assessment and enhancement of new therapeutic agents, potentially hastening the creation of more effective treatments for Parkinson’s disease and enhancing patient outcomes and their quality of life.
| Reference Key |
imported_1777057726_69ebbfbe1d829
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Fatima Saeed, Nazeran Idrees |
| Journal | Journal of Computing & Biomedical Informatics |
| Year | 2024 |
| DOI |
DOI not found
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.