Workflow for Criticality Assessment Applied in Biopharmaceutical Process Validation Stage 1

Abstract

Identification of critical process parameters that impact product quality is a central task during regulatory requested process validation. Commonly, this is done via design of experiments and identification of parameters significantly impacting product quality (rejection of the null hypothesis that the effect equals 0). However, parameters which show a large uncertainty and might result in an undesirable product quality limit critical to the product, may be missed. This might occur during the evaluation of experiments since residual/un-modelled variance in the experiments is larger than expected a priori. Estimation of such a risk is the task of the presented novel retrospective power analysis permutation test. This is evaluated using a data set for two unit operations established during characterization of a biopharmaceutical process in industry. The results show that, for one unit operation, the observed variance in the experiments is much larger than expected a priori, resulting in low power levels for all non-significant parameters. Moreover, we present a workflow of how to mitigate the risk associated with overlooked parameter effects. This enables a statistically sound identification of critical process parameters. The developed workflow will substantially support industry in delivering constant product quality, reduce process variance and increase patient safety.

Integrated Process Modeling—A Process Validation Life Cycle Companion

“…Results of the MC simulation are dependent on the sampling strategy for the process parameters at each simulation. Often pseudo-random numbers are replaced by quasi-random numbers or Latin hypercube sampling [ 10 , 11 ] for better overview of possible outcomes. However, for realistic risk assessment, we want our sampling to be representative for the process, therefore classical pseudo-random numbers were used for sampling.…”

Current challenges and recent advances on the path towards continuous biomanufacturing

“…Connecting process parameters to critical quality attributes is indispensable for a robust process design that ensures product quality over time. 78 The standard approach for discovering these relationships is *On-line monitoring: measurement where the sample is diverted from the manufacturing process, and may be returned to the process stream. In-line monitoring: measurement where the sample is not removed nor diverted from the process stream and can be invasive or non-invasive.…”

“…Connecting process parameters to critical quality attributes is indispensable for a robust process design that ensures product quality over time 78 . The standard approach for discovering these relationships is the design of experiments (DoE).…”

Decision Making and Risk Management in Biopharmaceutical Engineering—Opportunities in the Age of Covid-19 and Digitalization

“… 9 Hundreds of potentially influential factors in the production process can be taken into account and many tens of them are being broadly monitored and controlled. 10 The main engineering challenges 9 , 11 − 13 are to (1) robustly control the behavior of the living organism involved in the process, (2) efficiently align the often heterogeneous data generated across different process units and scales, (3) include all available prior know-how and experience into the decision process, (4) reduce human errors and introduced inconsistency, and (5) enable an automated and adaptive procedure to assess the critical process characteristics.…”