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Total was calculated using Satterthwaite approximation:
$$df_{tot}=\frac{ \left( \sigma _{T}^{2} \right) ^{2}}{\frac{ \left( \frac{ \sigma _{R}^{2}+J\ast \sigma _{L}^{2}}{J} \right) ^{2}}{ \left( I-1 \right) }+\frac{ \left( \sigma _{R}^{2} \left( 1-\frac{1}{J} \right) \right) ^{2}}{I \left( J-1 \right) }} $$
$$df_{tot}=\frac{ \left( 10.223 \right) ^{2}}{\frac{ \left( \frac{5.72+2\ast4.503}{2} \right) ^{2}}{ \left( 15-1 \right) }+\frac{ \left( 5.72 \left( 1-\frac{1}{2} \right) \right) ^{2}}{15 \left( 2-1 \right) }}=23.66 \approx 24 $$
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| Surface imperfection | p values | |||
|---|---|---|---|---|
| Gravimetric (BSA) | Gravimetric (addendum) | TOC | ||
| Micropits | Density factor | 0.917 | ||
| Scratches | Depth | 0.000A | 0.369 | 0.637 |
| Cleaning agent | 0.642 | 0.000 | ||
| Depth × cleaning agent | 0.866 | 0.859 | ||
| Roughness | Ra | 0.135 | ||
| Pits | Density factor | Dropped | Dropped | Dropped |
| Pit depth | Dropped | 0.120 | Dropped | |
| Pit aspect ratio | 0.007 | Dropped | Dropped | |
| Density factor × pit depth | Dropped | Dropped | Dropped | |
| Density factor × pit aspect ratio | 0.000 | Dropped | Dropped | |
| Pit depth × pit aspect ratio | 0.000B | Dropped | Dropped | |
| Cleaning agent | 0.014C | 0.000D | ||
| Soil | Dropped | Dropped | ||
| R2 adjusted | 0.900 | 0.130 | 0.900 | |
| A Depth > 1.0 mm will trap residue B Diameter > 4.0 mm with depth > 2.6 mm will trap residue |
C Dominant variable D Dominant variable, CIP 100 had the lowest TOC |
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Save the date for the 2020 ISPE Europe Annual Conference in Madrid, Spain, 30 March – 1 April. Visit the conference website to get a sneak peak of what to expect at the 2020 ISPE Europe Annual Conference.
Other Mathjax Samples
The within-location variance (\(ô_{ε}^{2}\)) can be estimated as the mean, (\(Σ_{1}^{B} s_{i}^{2}\))/B, of variances at each location. The between location variance (\(ô_{B}^{2}\)) can be estimated as the variance (\(s_{x}^{2}\)) of location means minus the within-location variance divided by n, (\(ô_{ε}^{2}/n\)). In summary:
Within-location variance: \(ô_{ε}^{2}\) = (\(Σ_{1}^{B} s_{i}^{2}\))/B
Between-location variance: \(ô_{B}^{2}\) = s\(_{x̄}^{2}\) - \(ô_{ε}^{2}/n\)
Total variance = \(ô_{B}^{2}\) + \(ô_{ε}^{2}\)
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Digitization, Technologies, and More at 2019 ISPE Europe Annual Conference
More than 800 attendees met in Dublin, Ireland, on 1–4 April for the 2019 ISPE Europe Annual Conference—a new record attendance for this conference! Participants at ISPE’s sixth Europe conference learned about how manufacturers, key suppliers, functional peer groups, and regulators expect the pharmaceutical industry to be affected by digitization, new products, changing portfolios, disruptive technologies, and other factors.
