Correlating Product Lifecycle and Manufacturing Site Characteristics with Critical-to-Quality Product Deviations - Pharmaceutical Technology

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Correlating Product Lifecycle and Manufacturing Site Characteristics with Critical-to-Quality Product Deviations
MIT survey results address product and site characteristics that statistically correlate with quality performance.


Pharmaceutical Technology
Volume 36, Issue 9, pp. 72-75


Table I: Variables that were found to be statistically different in likelihood of correlating with a critical-to-quality defect.
Correlations with critical-to-quality product deviations. Using critical-to-quality defects at the commercial scale as the dependent variable, 56 other variables were compared based on likelihood ratios for each of the 34 commercial products. Of these 56 variables, 11 were found to have statistically significant different likelihoods depending upon whether a critical-to-quality defect was experienced for that product. These 11 variables of significance are shown in Figure 4 and grouped based on confidence level of statistical significance (the top row contains variables for which the difference in likelihood ratio demonstrated greatest confidence) and grouped based on whether the correlation was negatively or positively correlated with a critical-to-quality defect at the commercial scale. If the variable is in the negatively correlated section of Figure 4, then presence of that variable is more likely to occur for a product without a reported critical defect.

For example, a product manufactured at commercial scale in a site having an above-median fraction of technical personnel working in QA was statistically less likely to have experienced a critical-to-quality defect at the commercial scale. On the other hand, a positively correlated variable is more likely to be present for a product that has experienced a critical defect. For example, a product manufactured in Asia is more likely to have experienced such a defect.

Consistent with prior preliminary discussion regarding variables correlated with product defects, many of the statistically significant variables presented in Figure 4 fall into the categories of history of quality issues in the product lifecycle, geographic region of manufacture, and manufacture in a contract manufacturing site (2). Of note is the dependence upon fraction of technical personnel employed in QA and employed in manufacturing. More generally, this dependence is related to the discussion of the distribution of technical personnel across a site as described above, where the lack of consistency and, perhaps, understanding of an optimal distribution was highlighted. The data presented in Figure 4 demonstrates that above median level of the fraction of technical personnel in QA and below median level of the fraction of technical personnel in manufacturing are both correlated with lower likelihood of a critical-to-quality defect at the commercial scale.

It is possible that greater emphasis on quality is demonstrated by fraction of personnel in QA compared with an emphasis on execution demonstrated by fraction of personnel in manufacturing. Further investigation in this area and clarity regarding the expectations of technical personnel roles could provide greater insight into this observation.

Although there were 11 variables significantly correlated with likelihood of a critical-to-quality defect at the commercial scale, there were also 45 variables found not to be so. Several of these variables are notable as not having been found to correlate with critical-to-quality defects at the commercial scale, including:

  • Type of product (e.g., protein, antibody).
  • Mode of production (e.g., mammalian, microbial).
  • Level of production complexity perceived by the site: The first three variables are related to perceived manufacturing complexity and logic could suggest that a dependence is expected, but has not been found in the current data.
  • Use of QbD: QbD can take on many forms and has a complex impact on measured quality performance metrics. Generally, this lack of correlation is notable as quality by design is expected to increase the likelihood of product with consistent quality over time (3).
  • Number of product batches manufactured in the past five years: More batches would be expected to increase probability of a single defect occurring but is logically counteracted by familiarity with the product and the possibility of increased learning from completed batches (4).


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