Cell and Gene Therapies: Challenges in Designing Extractables and Leachables Studies and Conducting Safety Assessments.

Over the past decade, Cell and Gene Therapies (C>) have been an emerging therapeutic area with more than twenty C> drug products approved and over 1000 registered trials. The remarkable progress in these modalities brings new challenges for scientists who evaluate manufacturing and storage materials, including risk assessments for extractables and leachables (E&L). Establishing a business process to qualify materials for these applications is an important risk mitigation strategy in support of these assessments. Process validation verifying process performance and product quality requirements using qualified materials also ensures that leachables from the materials do not result in an impact to process and product. The authors provide an overview of available guidelines and publications relevant to E&L risk assessments that can be used to support ex vivo C> products, highlighting gaps and standardization needs in the areas of biocompatibility and extractables conditions. Finally, the authors present leachable testing strategies, relevant to the specific manufacturing and storage conditions of C> products, and safety assessment considerations for organic and inorganic chemical entities.

Determining the Clearance of Degraded Protein via a Monoclonal Antibody Purification Process in Support of Cleaning Carryover Limits in Multiproduct Facilities.

Cleaning validation acceptance criteria in multiproduct facilities are established using maximum allowable carryover calculations. Carryover calculations incorporate the shared equipment surface area between two products to ensure that an acceptable limit for residue from the previously manufactured product to the subsequent product is determined. The shared surface area can be limited to areas where carryover presents the highest risk to product quality or patient safety. In these cases, specifically for biologic drug substance manufacturing, the shared surface area is limited to equipment after the purification process based on the assumption that the purification process would remove potential product fragment residues from the previous product. Until now, this assumption has been based on empirical knowledge without experimental data quantifying the clearance or removal of potential residues. We present a three-part study that determined the effects of cleaning conditions on selected monoclonal antibodies (mAbs) and the generation of degraded fragments and evaluated the clearance of both the degraded mAb1 in a laboratory setting and the degraded fragments in the presence of a subsequent product, assessing the risk of co-purification. Several analytical techniques were used, including gel electrophoresis, capillary zone electrophoresis/laser-induced florescence detection, and liquid chromatography-mass spectrometry. Protein fragment generation was demonstrated for five different mAbs from different immunoglobulin G subclasses. The clearance of the degraded fragments in the absence and presence of the subsequent product was demonstrated by calculating fold clearance and log reduction value (LRV) for each chromatography step. The data showed that the fragments generated during cleaning could be removed by the purification process. The fold clearances were determined to be values of 5400 (3.7 LRV) in the absence of subsequent product and 4428 (3.6 LRV) in the presence of subsequent product. The results supported the removal of product residues from shared surface areas by the purification process in multiproduct biologic drug substance manufacturing facilities.

Semisynthetic model calibration for monitoring glucose in mammalian cell culture with in situ near infrared spectroscopy.

Near infrared (NIR) spectroscopy has the capability of providing real-time, multi-analyte monitoring of the complex reaction mixture associated with cell culture processes. However, the development of robust models to predict the concentration of key analytes has proven difficult. In this study, a modeling methodology using semisynthetic process samples was used to predict glucose concentrations in Chinese Hamster Ovary (CHO) cell culture processes. Partial Least Squares (PLS) regression models were built from in situ NIR spectra, and glucose levels between 4.0 and 14.0 g/L. Two models were constructed. The "standard model" used data provided by cell culture production process samples. The "full model" included the data provided from both cell culture production process samples and semisynthetic samples. The semisynthetic samples were generated by titrating cell culture samples with target viable cell density (VCD) and lactate levels to defined glucose concentrations. The robustness of each model was gauged by predicting glucose in a subsequent cell culture process utilizing a media formulation and cell line not contained in the calibration data sets. The "full model" generated glucose predictions with a root mean square error of prediction (RMSEP) of 0.99 g/L while the "standard model" provided glucose predictions with a RMSEP of 2.26 g/L. The modeling approach utilizing semisynthetic samples proved to be faster development and more effective than using just standard cell culture processes.