| Literature DB >> 26202064 |
H Gregg Claycamp1,2, Ravikanth Kona3, Raafat Fahmy2, Stephen W Hoag4.
Abstract
Qualitative risk assessment methods are often used as the first step to determining design space boundaries; however, quantitative assessments of risk with respect to the design space, i.e., calculating the probability of failure for a given severity, are needed to fully characterize design space boundaries. Quantitative risk assessment methods in design and operational spaces are a significant aid to evaluating proposed design space boundaries. The goal of this paper is to demonstrate a relatively simple strategy for design space definition using a simplified Bayesian Monte Carlo simulation. This paper builds on a previous paper that used failure mode and effects analysis (FMEA) qualitative risk assessment and Plackett-Burman design of experiments to identity the critical quality attributes. The results show that the sequential use of qualitative and quantitative risk assessments can focus the design of experiments on a reduced set of critical material and process parameters that determine a robust design space under conditions of limited laboratory experimentation. This approach provides a strategy by which the degree of risk associated with each known parameter can be calculated and allocates resources in a manner that manages risk to an acceptable level.Entities:
Keywords: Bayesian Monte Carlo simulation; ciprofloxacin and granulation; ciprofloxacin hydrochloride; qualitative risk assessment; quality-by-design (QbD); roller compaction
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Year: 2015 PMID: 26202064 PMCID: PMC4984889 DOI: 10.1208/s12249-015-0349-2
Source DB: PubMed Journal: AAPS PharmSciTech ISSN: 1530-9932 Impact factor: 3.246