Abstract:
:The concept of quality by design (QbD) as published in ICH-Q8 is currently one of the most recurrent topics in the pharmaceutical literature. This guideline recommends the use of information and prior knowledge gathered during pharmaceutical development studies to provide a scientific rationale for the manufacturing process of a product and provide guarantee of future quality. This poses several challenges from a statistical standpoint and requires a shift in paradigm from traditional statistical practices. First, to provide "assurance of quality" of future lots implies the need to make predictions regarding the quality given past evidence and data. Second, the quality attributes described in the Q8 guidelines are not always a set of unique, independent measurements. In many cases, these criteria are complicated longitudinal data with successive acceptance criteria over a defined period of time. A common example is a dissolution profile for a modified or extended-release solid dosage form that must fall within acceptance limits at several time points. A Bayesian approach for longitudinal data obtained in various conditions of a design of experiment is provided to elegantly address the ICH-Q8 recommendation to provide assurance of quality and derive a scientifically sound design space.
journal_name
J Biopharm Statjournal_title
Journal of biopharmaceutical statisticsauthors
Lebrun P,Giacoletti K,Scherder T,Rozet E,Boulanger Bdoi
10.1080/10543406.2014.979197subject
Has Abstractpub_date
2015-01-01 00:00:00pages
247-59issue
2eissn
1054-3406issn
1520-5711journal_volume
25pub_type
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