Accelerating the Development and Transfer of Freeze-Drying Operations for the Manufacturing of Biopharmaceuticals by Model-Based Design of Experiments

In the pharmaceutical industry, freeze-drying (also known as lyophilization) is often used to increase the shelf life of heat-sensitive biopharmaceuticals such as protein-based therapeutic drugs an..

Improved formulation of the latent variable model inversion¿based optimization problem for quality by design applications

[EN] Latent variable regression model (LVRM) inversion is a relevant tool for finding, if they exist, different combinations of manufacturing conditions that yield the desired process outputs. Finding the best manufacturing conditions can be done by optimizing an appropriately formulated objective function using nonlinear programming. To this end, different formulations of the optimization problem based on LVRM inversion have been proposed in the literatura that allow the use of happenstance data (eg, historical data) for this purpose, present lower computational costs than optimizing in the space of the original variables, and guarantee that the solution will conform to the correlation structure of available data from the past. However, these approaches, as presented, suffer from some limitations, such as having to actively modify the constraints imposed on the solution to achieve different sets of conditions to those available in the LVRM calibration dataset, or the lack of a standardized approach for optimizing a linear combination of variables. Furthermore, when minimizing or maximizing one or more outputs, a severe handicap is also present related to the definition of arbitrarily low or high "desired" values. This paper aims at tackling all of these issues. The resulting proposed formulation of the optimization problem is illustrated with three case studies.Agencia Estatal de Investigacion, Grant/Award Number: DPI2017-82896-C2-1-R; European Regional Development Fund; Ministerio de Economia, Industria y Competitividad, Gobierno de Espana; Universitat Politecnica de Valencia, Grant/Award Number: Erasmus 2014.93231Palací-López, D.; Villalba-Torán, PM.; Facco, P.; Barolo, M.; Ferrer, A. (2020). 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General Framework for Latent Variable Model Inversion for the Design and Manufacturing of New Products. Industrial & Engineering Chemistry Research, 51(39), 12886-12900. doi:10.1021/ie301214cFacco, P., Dal Pastro, F., Meneghetti, N., Bezzo, F., & Barolo, M. (2015). Bracketing the Design Space within the Knowledge Space in Pharmaceutical Product Development. Industrial & Engineering Chemistry Research, 54(18), 5128-5138. doi:10.1021/acs.iecr.5b00863Bano, G., Facco, P., Bezzo, F., & Barolo, M. (2018). Probabilistic Design space determination in pharmaceutical product development: A Bayesian/latent variable approach. AIChE Journal, 64(7), 2438-2449. doi:10.1002/aic.16133Palací-López, D., Facco, P., Barolo, M., & Ferrer, A. (2019). New tools for the design and manufacturing of new products based on Latent Variable Model Inversion. Chemometrics and Intelligent Laboratory Systems, 194, 103848. doi:10.1016/j.chemolab.2019.103848MacGregor, J. F., & Bruwer, M.-J. (2008). 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Primary Drying Optimization in Pharmaceutical Freeze-Drying: A Multivial Stochastic Modeling Framework

Primary drying is the most time-consuming and energy-intensive step in pharmaceutical freeze-drying. Minimizing the duration of this stage is of paramount importance to speed up process development..

Optimization of the Appearance Quality in CO2 Processed Ready-to-Eat Carrots through Image Analysis

A high-pressure CO2 process applied to ready-to-eat food products guarantees an increase of both their microbial safety and shelf-life. However, the treatment often produces unwanted changes in the visual appearance of products depending on the adopted process conditions. Accordingly, the alteration of the visual appearance influences consumers’ perception and acceptability. This study aims at identifying the optimal treatment conditions in terms of visual appearance by using an artificial vision system. The developed methodology was applied to fresh-cut carrots (Daucus carota) as the test product. The results showed that carrots packaged in 100% CO2 and subsequently treated at 6 MPa and 40 ◦C for 15 min maintained an appearance similar to the fresh product for up to 7 days of storage at 4 ◦C. Mild appearance changes were identified at 7 and 14 days of storage in the processed products. Microbiological analysis performed on the optimal treatment condition showed the microbiological stability of the samples up to 14 days of storage at 4 ◦C. The artificial vision system, successfully applied to the CO2 pasteurization process, can easily be applied to any food process involving changes in the appearance of any food product