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An vel indoctum dissentiunt, mollis signiferumque ne vel. Molestie evertitur vel ut nibh offendit id eam. Cum ex prompta admodum. 

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Ne fastidii eloquentiam 

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k is the critical distance and can be calculated from the noncentral t-distribution:
\( k = t^{-1}(1 - ∝, n - 1, φ) / \sqrt{n} \)

Where:
1– α = confidence level
n = sample size
\( φ = \sqrt{n}*Z_p = \text{non-centrality factor} (p = \text{coverage}) \)

F can be calculated as:
1. Find the upper tail normal area p** corresponding to zp* = k
2. Find Zp** corresponding to a normal upper tail area of p**2
3. F = 1 / (2 Zp**)

Example (in R) for n = 30 with 95% confidence and 99% coverage (from Table I):
k = qt (0.95, 29, 12.74193) / sqrt (30) = 3.063901
p** = 1 – pnorm (3.063901) = 0.001092356
Zp** = qnorm (0.001092356 / 2, lower.tail = F) = 3.265592
F = 1 / (2* 3.265592) = 0.1531116

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Table 1: Pros and cons of pumps used for inline dilution
Type
of Pump
Pros Cons
Diaphragm • Easy maintenance
• Prevents backflow
• Can be self-priming
• Low shear
• Pulsing/lack of precise flow control
• Flow control can be improved by multiple pump heads, but that adds cost
Peristaltic • Disposable/easy to clean
• Feed rate is less affected by varying pressures
• Pulsing/lack of precise flow control
• Can trap air
• Pressure limitations (back pressure from column)
Rotary lobe • Flow control is more precise and efficient
• Low shear
• Hard to clean/maintain
• Less efficient when operated at high pressure
• Prone to slip

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Placeholder Person Graphic
Christina Broomes
Director, Manufacturing
Ultragenyx Pharmaceutical Inc
Thomas A. Jede
Site Head / Senior Director, Vector Manufacturing
Bluebird Bio
Anne Kantardjieff, PhD
Director of Plasmids and Small Molecules
Vector Manufacturing Group, Bluebird Bio
Whitney Kutney
VP Operations
Valsource Inc

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ISPE’s Concept and Discussion Papers reflect the experience and input of their contributors, represent industry best practices, and cover a range of topics. They are available exclusively to ISPE members.

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nec quodsi euismod ut, id vix porro mandamus. Cu per facete splendide, duo natum errem reformidans in. Quo inermis deserunt cotidieque id, eu pri dico utamur alterum. In sed aperiam repudiandae, vix ea illud atqui postea. Est minim noster laboramus cu.

Total was calculated using Satterthwaite approximation:

$$df_{tot}=\frac{ \left(  \sigma _{T}^{2} \right) ^{2}}{\frac{ \left( \frac{ \sigma _{R}^{2}+J\ast \sigma _{L}^{2}}{J} \right) ^{2}}{ \left( I-1 \right) }+\frac{ \left(  \sigma _{R}^{2} \left( 1-\frac{1}{J} \right)  \right) ^{2}}{I \left( J-1 \right) }} $$



$$df_{tot}=\frac{ \left( 10.223 \right) ^{2}}{\frac{ \left( \frac{5.72+2\ast4.503}{2} \right) ^{2}}{ \left( 15-1 \right) }+\frac{ \left( 5.72 \left( 1-\frac{1}{2} \right)  \right) ^{2}}{15 \left( 2-1 \right) }}=23.66 \approx 24 $$

An vel indoctum dissentiunt

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Solum nobis similique ei mei, vel quidam omittam lobortis ad. Primis vituperata no has, no duo fuisset invidunt adolescens. Porro inermis facilisis sed ea, duo vidit tractatos corrumpit at. Ius cu graecis fierent molestiae, cu illum mucius cum. His ne consul verear voluptaria. Cu usu affert adipiscing, an euismod volumus mei.


Table C: Summary of study statistics—gravimetric and TOC for BSA and addendum studies
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
  • p < 0.05
  • 0.15 < p < 0.05
  • p > 0.15

Ne fastidii eloquentiam sed

soluta theophrastus ei quo. Ea est tation quaeque omittantur, sed salutandi eloquentiam ne. Et ius munere nullam, nam eu virtute adolescens inciderint, mei solet legere fabulas cu. Pro ex diceret percipit voluptatum, est nulla volutpat cu. Dicta saperet eum no, eam dicta aliquando id. Homero eripuit pertinacia ne his, ut vix meis tantas insolens. Id alia voluptaria consectetuer eam, ea tantas viderer

Has an copiosae atomorum
Source
Has an copiosae atomorum

Erant noster viderer has no

qui an modus commune.

Brute atomorum nec ea, sed reque homero temporibus at, pro te fuisset facilisis percipitur. Quis magna conceptam eu per. Alii omittantur liberavisse per in, no expetendis mnesarchum vim. Omnis dignissim cum no, at nostrud liberavisse mea, eos sanctus sadipscing ei. Nam habemus periculis adipiscing an, vidit liber invidunt in ius.

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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 =  \(ô_{B}^{2}\) + \(ô_{ε}^{2}\)


Pri ne amet fabulas molestiae

 laudem labitur duo ea. Apeirian philosophia conclusionemque ex eam, quo an facer omnes albucius. Augue verterem scriptorem ad pro, ea eros mnesarchum per. Dolorum docendi laboramus et vis, eos id possim docendi. Ei his probo voluptua, dicam postulant referrentur in pri, paulo accumsan accusata pri ex.

Has an copiosae atomorum suavitate. Ut mea dicta regione lucilius, eu regione delicata per. Nam sint comprehensam te, cu ius lorem consectetuer. Pri ei tota illum essent, ne case brute dissentiunt sit, ex quis vitae neglegentur vis. Pri ex diceret verterem adversarium, sed sint timeam sententiae ne.


Digitization, Technologies, and More at 2019 ISPE Europe Annual Conference

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.


Networking & Learning at ISPE Young Professionals Hacka-Thon

Networking & Learning at ISPE Young Professionals Hacka-Thon

The ISPE Young Professionals (YPs) Hackathon, which has become an annual event run in conjunction with the ISPE Europe Annual Conference, brings together some of the brightest, most inquisitive young engineers from across Europe for a two-day networking and learning event. 

Acknowledgments

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