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Cited by 8
A Bayesian Approach to Pharmaceutical Product Quality Risk Quantification

Assessment of Accuracy and Computational Efficiency of Different Strategies for Estimation of Probability Distributions Applied to ODE/DAE Systems
Francesco Rossi, Linas Mockus, Flavio Manenti, Gintaras Reklaitis
https://doi.org/10.1016/B978-0-444-64241-7.50252-4
Book  Computer Aided Chemical Engineering (13th International Symposium on Process Systems Engineering (PSE 2018)) Volume 44 (2018), p. 1543
Knowledge Management in Support of QbD
G. Joglekar, Gintaras V. Reklaitis, A. Giridhar, Linas Mockus
https://doi.org/10.1002/9781119356189.ch14
Book  (2017), p. 361
Leveraging Bayesian Approach to Predict Drug Manufacturing Performance
Ying Fei Li, Venkat Venkatasubramanian
https://doi.org/10.1007/s12247-016-9261-x
Journal  Journal of Pharmaceutical Innovation Volume 11, Issue 4 (2016), p. 331
Modeling for Process Risk Assessment in Industrial Bioprocesses
Robert Spann, Anna Eliasson Lantz, Krist V. Gernaey, Gürkan Sin
https://doi.org/10.1016/B978-0-12-409547-2.14356-2
Book  (2018)
Probabilistic modeling of an injectable aqueous crystalline suspension using influence networks
Andrea Sekulović, Marion Petit, Ruud Verrijk, Thomas Rades, Jukka Rantanen
https://doi.org/10.1016/j.ijpharm.2021.120283
Journal  International Journal of Pharmaceutics Volume 596 (2021), p. 120283
Rigorous Bayesian Inference VS New Approximate Strategies for Estimation of the Probability Distribution of the Parameters of DAE Models
Francesco Rossi, Linas Mockus, Gintaras Reklaitis
https://doi.org/10.1016/B978-0-12-818634-3.50156-9
Book  Computer Aided Chemical Engineering (29th European Symposium on Computer Aided Process Engineering) Volume 46 (2019), p. 931
The Unreasonable Effectiveness of Equations: Advanced Modeling For Biopharmaceutical Process Development
Pablo A. Rolandi
https://doi.org/10.1016/B978-0-12-818597-1.50023-0
Book  Computer Aided Chemical Engineering (Proceedings of the 9th International Conference on Foundations of Computer-Aided Process Design) Volume 47 (2019), p. 137
The current state of Bayesian methods in nonclinical pharmaceutical statistics: Survey results and recommendations from the DIA/ASA‐BIOP Nonclinical Bayesian Working Group
Paul Faya, Perceval Sondag, Steven Novick, Dwaine Banton, John W. Seaman, Jr, James D. Stamey, Bruno Boulanger
https://doi.org/10.1002/pst.2072
Journal  Pharmaceutical Statistics Volume 20, Issue 2 (2021), p. 245


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