Process validation encompasses a lifecycle approach which includes three stages: Process Design or Development (Stage 1), Process Performance Qualification (Stage 2) and Continued/On-going Process Verification (CPV, Stage 3). The 3 stages are typically a long manufacturing journey where extensive data is accumulated, trended, and analyzed. Thus, CPV highly recommends process automation, PAT (Process Analytical Technologies) and a deep knowledge of the manufacturing process and drug product. Continued process verification enables concepts like real time release (RTR), use of continuous manufacturing or Golden Batch, but it is still not adopted in Pharma.
The established conditions (EC), critical quality attributes (CQA), and critical process parameters (CPP) are not enough to describe a real, complete picture and history of the process. Manual operations, environmental variables, seasonality components and many other factors are affecting the process inducing a permanent variability. Statistics and Multivariable Analysis can be complemented with artificial intelligence (AI) to boost the stage 3 towards a reality and a continuous state of the art in biopharma manufacturing.
During the webinar, panelists will explain how Artificial Intelligence allows predicting, classifying, recognizing and recommending improvements to the process which leads to enhanced product quality and process performance (2 sides of the same coin) in CPV.