REVIEW OF RECENT STUDIES ON STATISTICAL OPTIMIZATION IN DRUG DELIVERY TECHNOLOGIES
AbstractStatistical modeling and experimental design are essential tools in field of drug delivery during product development and can be divided into formula and process optimization. Experimental design allows efficient experimentation in which all or a large subset of factors are together varied over a set of experiments, in contrast to the traditional approach of varying only one variable at time (OVAT). Good estimates for the required composition, geometry, dimensions and preparation procedure of various types of delivery systems will be available, taking into account the desired administration route, drug dose and release profile. Thus, the number of required experimental studies during product development can be significantly reduced, saving time and reducing costs. The present review discusses types of designs and methodologies used recently in academic as well as industrial research for optimization of novel drug delivery systems.
Download data is not yet available.
175 Views | 380 Downloads
How to Cite
Patil S, Yeramwar S, Sharma P, Bhargava A. REVIEW OF RECENT STUDIES ON STATISTICAL OPTIMIZATION IN DRUG DELIVERY TECHNOLOGIES. JDDT [Internet]. 14Sep.2014 [cited 24Jan.2021];4(5):58-. Available from: http://jddtonline.info/index.php/jddt/article/view/954
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).