Author(s):
D. Mamatha, Hindustan Abdul Ahad, G. Ushasree, K. Vinod, C. Haranath, P. Kiran
Email(s):
abdulhindustan@gmail.com
DOI:
10.52711/0974-4150.2023.00069 
Address:
D. Mamatha1*, Hindustan Abdul Ahad2, G. Ushasree3, K. Vinod3, C. Haranath2, P. Kiran4
1Department of Pharmaceutical Quality Assurance, Raghavendra Institute of Pharmaceutical Education and Research (RIPER) - Autonomous, Ananthapuramu - 515721, Andhra Pradesh, India.
2Department of Pharmaceutics, RR College of Pharmacy, Chikkabanavara, Bengaluru - 90, Karnataka, India.
3Department of Pharmaceutical Analysis, Raghavendra Institute of Pharmaceutical Education and Research (RIPER) - Autonomous, Ananthapuramu - 515721, Andhra Pradesh, India.
4Department of Pharmacology, Raghavendra Institute of Pharmaceutical Education and Research (RIPER)-Autonomous, Ananthapuramu - 515721, Andhra Pradesh, India.
*Corresponding Author
Published In:
Volume - 16,
Issue - 6,
Year - 2023
ABSTRACT:
The primary goal of the evaluation is to ensure the product's quality by locating and managing "out of trend" (OOT) areas, utilising various techniques in the pharmaceutical sector. Regression control charts, time points, and slope control charts can all be used to identify or detect OOT. At the time of handling, OOT is divided into three categories: analytical alert, process control alert, and compliance alert. The electrical OOT Tracking Software from Ample Logic, created using low-code technology, is used to manage OOT. Identification of OOT stability results is an increasingly important topic in the pharmaceutical industry. In a perfect world, finding or detecting an OOT would be easy. However, an oversimplified system might not be sensitive enough to detect a genuine OOT. It should be chosen based on how the approach would impact the parameter being evaluated. This article outlines several tactics, such as how to recognise an unexpected single result or unusual variance. When numerous tests and time points call for OOT constraints, OOT detection can be a difficult problem. Additionally, it includes components and software that help manage OOT discoveries.
Cite this article:
D. Mamatha, Hindustan Abdul Ahad, G. Ushasree, K. Vinod, C. Haranath, P. Kiran. Out-of-Trend Statistics in The Pharmaceutical Industry: A Gain Leap in Assuring the Quality of The product. Asian Journal of Research in Chemistry. 2023; 16(6):423-8. doi: 10.52711/0974-4150.2023.00069
Cite(Electronic):
D. Mamatha, Hindustan Abdul Ahad, G. Ushasree, K. Vinod, C. Haranath, P. Kiran. Out-of-Trend Statistics in The Pharmaceutical Industry: A Gain Leap in Assuring the Quality of The product. Asian Journal of Research in Chemistry. 2023; 16(6):423-8. doi: 10.52711/0974-4150.2023.00069 Available on: https://ajrconline.org/AbstractView.aspx?PID=2023-16-6-5
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