The results of an industry workgroup’s examination of EMA’s guide on shared facilities are presented.
The results of an industry workgroup’s examination of EMA’s guide on shared facilities are presented.
The author reviews FDA's final Animal Rule guidance.
The author presents a method to calculate the relationship between supply air volume flow and airborne particle concentrations.
A novel method, based on differential calculus, was used to calculate the maximum potential error associated with the drug concentration in pharmaceutical mixtures composed of an infinite number of ingredients measured on an infinite number of balances with different sensitivities. The method was further applied to calculate the ingredients’ least allowable quantities. This approach ensures that the pharmaceutical formulation is prepared within a given maximum permissible error in drug dose.
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Keith Moore, vice-president of analytical services, Metrics Contract Services discusses gains use in dissolution testing.
Directors from FDA's Center for Drug Evaluation and Research summarize findings in an FDA-commissioned report on QbD and propose actions the agency can take to encourage full-scale QbD implementation.
Understanding of the basic principles of balance and scale enables a user to achieve a qualified weighing process.
There are many different approaches for assessing process parameter criticality, and assessing which process parameters have a significant impact on critical quality attributes (CQAs) is a particular challenge. Including an unimportant process parameter as a critical process parameter (CPP) in a control strategy can be detrimental. The authors present a statistical approach to determine when a statistically significant relationship between a process parameter and a CQA is large enough to make a practically meaningful impact (i.e., practical significance).
There are many different approaches for assessing process parameter criticality, and assessing which process parameters have a significant impact on critical quality attributes (CQAs) is a particular challenge. Including an unimportant process parameter as a critical process parameter (CPP) in a control strategy can be detrimental. The authors present a statistical approach to determine when a statistically significant relationship between a process parameter and a CQA is large enough to make a practically meaningful impact (i.e., practical significance).
There are many different approaches for assessing process parameter criticality, and assessing which process parameters have a significant impact on critical quality attributes (CQAs) is a particular challenge. Including an unimportant process parameter as a critical process parameter (CPP) in a control strategy can be detrimental. The authors present a statistical approach to determine when a statistically significant relationship between a process parameter and a CQA is large enough to make a practically meaningful impact (i.e., practical significance).
There are many different approaches for assessing process parameter criticality, and assessing which process parameters have a significant impact on critical quality attributes (CQAs) is a particular challenge. Including an unimportant process parameter as a critical process parameter (CPP) in a control strategy can be detrimental. The authors present a statistical approach to determine when a statistically significant relationship between a process parameter and a CQA is large enough to make a practically meaningful impact (i.e., practical significance).
There are many different approaches for assessing process parameter criticality, and assessing which process parameters have a significant impact on critical quality attributes (CQAs) is a particular challenge. Including an unimportant process parameter as a critical process parameter (CPP) in a control strategy can be detrimental. The authors present a statistical approach to determine when a statistically significant relationship between a process parameter and a CQA is large enough to make a practically meaningful impact (i.e., practical significance).
There are many different approaches for assessing process parameter criticality, and assessing which process parameters have a significant impact on critical quality attributes (CQAs) is a particular challenge. Including an unimportant process parameter as a critical process parameter (CPP) in a control strategy can be detrimental. The authors present a statistical approach to determine when a statistically significant relationship between a process parameter and a CQA is large enough to make a practically meaningful impact (i.e., practical significance).
Asking the right questions is crucial to establishing a biopharmaceutical facility design.
Asking the right questions is crucial to establishing a biopharmaceutical facility design.
In this article, the authors look at the limitations of the validation for a single-use shipping system and provide a perspective on what shipping validation means.
Increased use of single-use systems has led to a need to redefine safe, stable and integral systems for shipping biopharmaceuticals around the world. This article provides qualification data under international ASTM D4169 norms.
In this article, the authors look at the limitations of the validation for a single-use shipping system and provide a perspective on what shipping validation means.