Abstract
Biological products are increasingly important, and therefore the industry has begun to adopt quality by design, as recommended by the ICH and the U.S. FDA. Smaller companies, however, have faced difficulties in employing full-scale experiments or the quality by design strategy. Thus, this study provides an alternative way to build a model from existing data with experimental software that does not require full-scale experiments. This empirical study hopes to provide a practical way to improve the efficiency of smaller biopharmaceutical companies and researchers. Moreover, the models provided here can be applied to process characterization in recombinant protein production.
Highlights
Fermentation ProcessRecently, the pharmaceutical industry has been advised by the ICH [1] and U.S FDA to adopt a new quality control strategy
On the basis of the initial search of eight points, we found that the preliminary models suffered from noise and the volumetric yield model was slightly better
On the basis of the preliminary data, we found that condition 2 returned a higher quantity than condition 1 on the lab scale
Summary
The pharmaceutical industry has been advised by the ICH [1] and U.S FDA to adopt a new quality control strategy. A central concept of the principle is to systematically correlate the relationships between the process parameters and the quality attributes [8] This implies that the empirical relationships and formulas can be built to assist researchers throughout the process development stages [2,8,9]. DOE researchers can only develop as few as three additional datasets to optimize (at least locally) the volumetric yield and total yield This approach helps the entire pharmaceutical industry to make more drugs, which have been eagerly requested by patients. In lab-scale studies (presented below), the research and development studies on quality attributes followed ICH Q8 (R2) guidelines, and the analytical methods for determining purity and activity in the final lot-release specification were pre-validated for at least linearity, specificity, and repeatability. The analytical methods for the lot-release specification were validated
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