Monitoring of product variants in biopharmaceutical downstream processing : Mechanistic and data-driven modeling approaches

During the manufacturing of biopharmaceuticals, a multistep purification strategy is employed to remove process-related impurities and product variants, to achieve high product quality, assuring patients’ safety. To guarantee that biopharmaceuticals are safe and to accomplish quality, strict policies were established by regulatory agencies as well as guiding principles, such as Quality by Design and process analytical technology. To make the manufacturing process economical, relatively high product yield and productivity are also desirable. The removal of product variants often poses a challenge in downstream processing due to their structural similarity to the product resulting in similar behavior. One way of overcoming this issue is to employ additional monitoring tools capable to distinguish between the product and product variants. This thesis demonstrates the development of novel monitoring tools, based on existing monitoring and modeling approaches, to facilitate downstream processing. Existing techniques are evaluated and critically compared toward meeting the requirements on monitoring quality attributes in downstream processing. A mechanistic model-based monitoring tool was established for a reversed phase chromatography polishing step of insulin to predict the elution profile of insulin and two insulin variants. By relying on model-based monitoring a significant increase in product yield was achieved. Further, multi-wavelength fluorescence spectroscopy coupled with the multi-way algorithm parallel factor analysis was utilized to monitor product variants of biopharmaceuticals in downstream processing. This monitoring tool capitalizes on a shift in fluorescence emission between the product and its variant. Developed for monitoring aggregates during antibody purification, the transferability of the approach to other relevant biopharmaceuticals, such as factor VIII and erythropoietin, has been confirmed. The monitoring tools developed in this thesis, extend existing monitoring tools for downstream processing of biopharmaceuticals. When implementing these monitoring tools into the different phases of biopharmaceuticals’ lifespan, their potential could range from optimizing downstream processes during purification strategy development to supporting manufacturing by facilitating process decisions