Title:Applications of QbD-based Software’s in Analytical Research and Development
VOLUME: 17 ISSUE: 4
Author(s):Bikash Ranjan Jena*, Siva Prasad Panda, Kulandaivelu Umasankar, Suryakanta Swain, Gudhanti Siva Naga Koteswara Rao, Dalu Damayanthi, Debashish Ghose and Debi Prasad Pradhan
Affiliation:Southern Institute of Medical Sciences, College of Pharmacy, Guntur 522001, Andhra Pradesh, KL College of Pharmacy, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, KL College of Pharmacy, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, Southern Institute of Medical Sciences, College of Pharmacy, Guntur 522001, Andhra Pradesh, KL College of Pharmacy, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, KL College of Pharmacy, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, Department of Pharmaceutics, Roland Institute of Pharmaceutical Sciences, Berhampur 760 010, Odisha, GITAM Institute of Pharmacy, GITAM Deemed to be University, Visakhapatnam- 530045, Andhra Pradesh
Keywords:Auto-chrome MDS, minitab, design expert, fusion product development, DoE wisdom, ellistat.
Abstract:
Background: Quality by design-based software’s in analytical research and development
normally encompasses multiple objectives. For decades, this task has been attempted through trial and
error, supplemented with the previous experience, knowledge, and wisdom of analytical researchers.
Objective: The study analyzes the current QbD-assisted software’s, such as design-experts, minitab, fusion
product development, etc., and its broad implementations in an analytical research and development.
Methods: The traditional approach may fails to meet the intended purpose by trial and error procedure
during analytical research and development. However, modern scientific technology is equipped with
highly advanced features associated with the software of the QbD paradigm. The impact and interactions
between the critical process variables and critical method attributes such as resolution, tailing, etc.
can be well understood by the screening, optimization, and robustness studies based on the principles
of experimental design.
Results: The design of experiments assimilate statistical multi-variate analysis instead of one factor at
a time approach. This also provides a prominent, most reliable quality output, which is also essential
for getting highly robust method as well as to obtain homogenous product development.
Conclusion: The present review, critically discussed about the various QbD based multivariate software
and their applications in drug development and analytical research.
