Closed System Transfer Devices (CSTDs): Understanding Potential Over- and Under- Dosing of Liquid Vial Drug Products and How to Generally Mitigate.

Closed system transfer devices (CSTDs) are a major challenge for drug manufacturers to assess and assure drug compatibility and acceptable dosing accuracy for a range of clinical administration strategies. In this article, we systematically investigate parameters affecting the loss of product during transfer by CSTDs from vials to infusion bags. We show that liquid volume loss increases with vial size, vial neck diameter, and solution viscosity - while dependent on stopper design. We further compared CSTDs' performance with a traditional syringe transfer and learned that loss is larger for CSTDs than for syringe transfer. Based on experimental data, a statistical model was developed to predict drug loss upon transfer by CSTDs. The model predicted that, for single dose vials with USP<1151> conforming overfill, a complete extraction and transfer of the full dose can be assured for a broad range of CSTDs, product viscosities, and vial types (2R, 6R, 10R, 20R) if a flush (of syringe, syringe adaptor, bag spike) is performed. The model also predicted that complete transfer cannot be achieved for fill volumes ≤ 2.0 mL. For multi-dose vials and pooling of several vials, respectively, the effective dose transfer (i.e., ≥ 95%) for all CSTDs tested was predicted to be achieved if a minimum of 5.0 mL is transferred.

An Intra-Company Analysis of Inherent Particles in Biologicals Shapes the Protein Particle Mitigation Strategy Across Development Stages.

To better understand protein aggregation and inherent particle formation in the biologics pipeline at Novartis, a cross-functional team collected and analyzed historical protein particle issues. Inherent particle occurrences from the past 10 years were systematically captured in a protein particle database. Where the root cause was identified, a number of product attributes (such as development stage, process step, or protein format) were trended. Several key themes were revealed: 1) there was a higher propensity for inherent particle formation with non-mAbs than with mAbs; 2) the majority of particles were detected following manufacturing at scale, and were not predicted by the small-scale studies; 3) most issues were related to visible particles, followed by subvisible particles; 4) 50% of the issues were manufacturing related. These learnings became the foundation of a particle mitigation strategy across development and technical transfer, and resulted in a set of preventive actions. Overall, this study provides further insight into a recognized industry challenge and hopes to inspire the biopharmaceutical industry to transparently share their experiences with inherent particles formation.

Tolerance Interval Approach for the Determination of Overfill of Liquid Parenteral Drug Products.

Liquid parenteral products contain an overfill to ensure withdrawal of the declared volume. The overfill must be sufficiently high to compensate for the expected loss during product preparation and administration, but it should also be minimized to prevent accidental overdosing and unforeseen dose splitting of single-dose products. Finding the right balance between too much and too little overfill with an acceptable risk of product failure is challenging and requires consideration of the relevant sources of variability of the extractable volume. This article provides a novel approach for the calculation of the required overfill based on tolerance interval methodology. In a first step, a tolerance interval multiplier from the literature is proposed, and a simulation study is conducted to assess the appropriateness of its use for overfill determination. In a second step, this multiplier is adapted to cover operator-to-operator variability in the loss data and compared with other multipliers via a second simulation study. Use of a tolerance interval multiplier enables adaptation of the overfill such that the risk of not reaching the minimum extractable volume fulfills predefined acceptance criteria. By this, the scientific justification of the selected overfill is strengthened and control over a critical quality attribute is improved.

Statistical Quality and Process Control in Biopharmaceutical Manufacturing-Practical Issues and Remedies.

Statistical quality and process controls (SQC and SPC) are used for monitoring, trending, and ultimately improving biopharmaceutical manufacturing processes and operations. The purpose of this paper is to highlight characteristic features of bioprocess data and their impact on typical SQC and SPC applications, specifically control charts for individual observations (I-chart) and estimation of process performance index (Ppk). Simulated data were used in an attempt to mimic bioprocess data by inducing inhomogeneity, nonstationarity, autocorrelation, and outliers. The first specific part highlights the roles of within and overall standard deviation (SD) estimates for 3σ limits and their impacts on frequently applied sensitizing rules for control charts, i.e. Nelson's rules 1-4. The second part deals with the often-asked question of how many observations are required for estimation of robust 3σ limits. In the third part, five popular approaches for treating censored data (results below or equal to limit of quantification, ≤LOQ) were compared and their impact on 3σ limits and Ppk estimates were assessed. The final section summarizes the typical issues faced by the practitioner in the application of SQC and SPC and provides remedies for setting up robust and efficient control charts for biopharmaceutical process monitoring. Overall, this study shows that process monitoring and subsequent assessment without taking into consideration this atypical nature of biopharmaceutical process can lead to increased false alarm rates, thus impacting the batch release or even possibility of rejecting good batches.

Statistically Significant versus Practically Relevant Trend in Stability Data.

How to decide whether a statistically significant trend is of practical relevance? In the context of stability data of pharmaceuticals, this publication provides a way forward to use different measures of (method) variability to compare to the observed changes over time. A panel of analytical experts assessed whether statistically significant trends were of practical relevance or not. For different types of assessing variability, recommendations for decision criteria were derived that best matched these assessments, i.e., finding a suited balance between not detecting a relevant trend and between flagging a trend wrongly as relevant. For this purpose, more than 60 data sets from Biosimilar projects of Sandoz/Novartis were leveraged. Hence, this article provides a scientific way to assess whether a statistically significant trend is of practical relevance or not, and a case study is presented and discussed.

Microscale Perfusion-Based Cultivation for Pichia pastoris Clone Screening Enables Accelerated and Optimized Recombinant Protein Production Processes.

Pichia pastoris has emerged in the past years as a promising host for recombinant protein and biopharmaceutical production. In the establishment of high cell density fed-batch biomanufacturing, screening phase and early bioprocess development (based on microplates and shake flasks) still represent a bottleneck due to high-cost and time-consuming procedures as well as low experiment complexity. In the present work, a screening protocol developed for P. pastoris clone selection is implemented in a multiplexed microfluidic device with 15 µL cultivation chambers able to operate in perfusion mode and monitor dissolved oxygen content in the culture in a non-invasive way. The setup allowed us to establish carbon-limited conditions and evaluate strain responses to different input variables. Results from micro-scale perfusion cultures are then compared with 1L fed-batch fermentation. The best producer in terms of titer and productivity is rapidly identified after 12 h from inoculation and the results confirmed by lab-scale fermentation. Moreover, the physiological analyses of the strains under different conditions suggested how more complex experimental conditions are achievable despite the relatively easy, straight-forward, and cost-effective experimental setup. Implementation and standardization of these micro-scale protocols could reduce the demand for lab-scale bioreactor cultivations thus accelerating the development of protein production processes.

The Degree and Length of O-Glycosylation of Recombinant Proteins Produced in Pichia pastoris Depends on the Nature of the Protein and the Process Type.

The methylotrophic yeast Pichia pastoris is known as an efficient host for the production of heterologous proteins. While N-linked protein glycosylation is well characterized in P. pastoris there is less knowledge of the patterns of O-glycosylation. O-glycans produced by P. pastoris consist of short linear mannose chains, which in the case of recombinant biopharmaceuticals can trigger an immune response in humans. This study aims to reveal the influence of different cultivation strategies on O-mannosylation profiles in P. pastoris. Sixteen different model proteins, produced by different P. pastoris strains, are analyzed for their O-glycosylation profile. Based on the obtained data, human serum albumin (HSA) is chosen to be produced in fast and slow growth fed batch fermentations by using common promoters, PGAP and PAOX1 . After purification and protein digestion, glycopeptides are analyzed by LC/ESI-MS. In the samples expressed with PGAP it is found that the degree of glycosylation is slightly higher when a slow growth rate is used, regardless of the efficiency of the producing strain. The highest glycosylation intensity is observed in HSA produced with PAOX1 . The results indicate that the O-glycosylation level is markedly higher when the protein is produced in a methanol-based expression system.