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Scale-Up of Freeze-Drying Cycles, the Use of Process Analytical Technology (PAT), and Statistical Analysis

  • Erwan BourlèsEmail author
  • Gael de Lannoy
  • Bernadette Scutellà
  • Fernanda Fonseca
  • Ioan Cristian Trelea
  • Stephanie Passot
Protocol
Part of the Methods in Pharmacology and Toxicology book series (MIPT)

Abstract

Traditionally, the quality of pharmaceutical drugs is tested on the final freeze-dried product following a regulatory framework known as Quality-by-Testing (QbT) (Yu, Pharm Res 25: 781–91, 2008). In this system, product quality and performance are ensured by performing extensive tests on the final product, and by using a fixed formulation and manufacturing process. In contrast, the US Food and Drug Administration (FDA) proposed the Quality by Design (QbD) initiative with the idea that quality cannot be “tested into” the product, but it should be built into it (FDA, Guidance for industry, Q8(R2) pharmaceutical development. Dept. of Health and Human Services, Center for Drug Evaluation and Research. Rockville, MD, 2009). Quality by Design consists of a systematic approach to pharmaceutical product development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management (FDA, Guidance for industry, Q8(R2) pharmaceutical development. Dept. of Health and Human Services, Center for Drug Evaluation and Research. Rockville, MD, 2009; Mockus et al, Pharm Dev Technol 16: 549–76, 2011; Yu, Pharm Res 25: 781–91, 2008). In this chapter, a statistical model for the sublimation step in freeze-drying was used to construct the design space for the cycle development and to select adequate parameters for scaling up from pilot to commercial scale. Three critical operating variables of the process were tested: freezing rate, shelf temperature, and chamber pressure in primary drying. The model was used to predict the sublimation rate and the product temperature, since their selection is of paramount importance to obtain a product of high quality. The obtained results were then used to define the design space of the product at pilot scale.

Key words

Quality by design (QbD) Statistical model Scale-up Edge effects Heat transfer coefficient Process analytical technology (PAT) 

Nomenclature

A

Cross sectional area (m2)

b

Model parameters

ΔH

Latent heat of sublimation (J kg−1)

Kv

Vial heat transfer coefficient (W m−2 K−1)

L

Product layer thickness (m)

m

Mass (kg)

\( \dot{m} \)

Sublimation rate (kg s−1)

P

Pressure (Pa)

\( \dot{Q} \)

Heat flow rate (W)

Rp

Mass transfer resistance (kPa s m2 kg−1)

T

Temperature (K)

Tg

Glass transition temperature (K)

Tcoll

Collapse temperature (K)

Teu

Eutectic melt temperature (K)

y

Critical process parameters

x

Operating variable

Greek

ε

Random error assumed to follow a Gaussian distribution

λ

Thermal conductivity (W m−1 K−1)

Subscripts

b

Vial bottom

c

Chamber

ice

Ice

i

Interface

max

Maximum

s

Shelf

Notes

Acknowledgments

The authors would like to thank Yves Mayeresse and Benoît Moreau (Manufacturing Science and Technology Belgium, GSK) for reviewing this work and Vincent Ronsse, Olivier Despas and Alain Philippart (Technical Research and Development, Belgium) for all the experimental work performed for this project.

Conflict of Interest: Erwan Bourlès, Gael De Lannoy and Bernadette Scutella are employees of the GSK group of companies. Stephanie Passot, Fernanda Fonseca, and Ioan Cristian Trelea report no financial conflicts of interest.

Funding: This work was funded by GlaxoSmithKline Biologicals S.A., under a Cooperative Research and Development Agreement with INRA (Institut National de la Recherche Agronomique) via the intermediary of the UMR (Unité Mixte de Recherche) GMPA (Génie et Microbiologie des Procédés Alimentaires) at the INRA Versailles-Grignon research centre.

Author Contributions: All authors were involved in the conception of the model and design of the study. Erwan Bourlès acquired the data. Erwan Bourlès Bernadette Scutellà, Stephanie Passot, Fernanda Fonseca, and Ioan Cristian Trelea analyzed and interpreted the experimental results. Erwan Bourles, Gael de Lannoy, Bernadette Scutellà, Stephanie Passot, Fernanda Fonseca, and Ioan Cristian Trelea were involved in the model development. All authors were involved in drafting the manuscript or revising it critically for important intellectual content. All authors had full access to the data and approved the manuscript before it was submitted by the corresponding author.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Erwan Bourlès
    • 1
    Email author
  • Gael de Lannoy
    • 1
  • Bernadette Scutellà
    • 1
  • Fernanda Fonseca
    • 2
  • Ioan Cristian Trelea
    • 2
  • Stephanie Passot
    • 2
  1. 1.GSK VaccinesRixensartBelgium
  2. 2.UMR GMPA, AgroParisTech, INRAUniversité Paris SaclayThiverval-GrignonFrance

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