Current biopharmaceutical potency testing methods are time consuming, labor intensive, and—on a sterile manufacturing line—a potential source of contamination, says the team behind a new software-based alternative. Drug potency is a critical quality attribute (CQA). Medicines that are too weak or too strong are at best ineffective and at worst dangerous.
In theory, biopharmaceutical manufacturing processes are designed to address this by ensuring products are consistent and meet defined potency specifications. In practice, however, inherent variability in raw materials and culturing means there is always a risk that products will be outside the desired potency range. To try and mitigate this risk, biopharmaceutical manufacturers regularly test the potency of samples taken from the production line and—if an out-of-spec (OOS) result is detected—adjust the process accordingly.
Unfortunately, while effective, current potency testing methods can be challenging to carry out, according to researchers at Bayer Pharmaceuticals in California. “Traditionally, the evaluations regarding potential process setting adjustments are made through manual, ad hoc calculations that can be error-prone, and inefficient, often requiring the valuable time of subject matter experts (SMEs). “Therefore,” the authors write in a , “there is a need to streamline these adjustments leveraging statistical modeling workflow and software tools, allowing for more accurate and efficient decision-ma.
