Predictive modeling for assessing the long-term thermal stability of a new fully-liquid quadrivalent meningococcal tetanus toxoid conjugated vaccine

Science- and Risk-Based Stability Strategies to Support Product Lifecycle Changes

ICH Q12 asserts that science- and risk-based approaches are applicable to stability studies supporting Chemistry, Manufacturing and Controls (CMC) post-approval changes (PAC) to enable more timely implementation; however, no guidance or specific examples are provided to demonstrate how prior knowledge of the product can inform the risk assessment for the proposed change(s). Ten diverse case studies are presented in this manuscript to demonstrate how science- and risk-based stability strategies were used to support drug substance and product CMC PAC and lifecycle management activities. The accumulated stability knowledge held by original manufacturers of marketed products is substantial, and different elements of this knowledge base were used to assess the risks and impact of the proposed changes for confident change management. This paper provides ways to leverage science- and risk-based stability strategies as part of the post-approval change-management risk-mitigation strategy, which may enable a reduced stability data commitment and/or a reduced reporting category for change implementation.

A Bayesian Approach to Kinetic Modeling of Accelerated Stability Studies and Shelf Life Determination

Kinetic modeling of accelerated stability data serves an important purpose in the development of pharmaceutical products, providing support for shelf life claims and expediting the path to clinical implementation. In this context, a Bayesian kinetic modeling framework is considered, accommodating different types of nonlinear kinetics with temperature and humidity dependent rates of degradation and accounting for the humidity conditions within the packaging to predict the shelf life. In comparison to kinetic modeling based on nonlinear least-squares regression, the Bayesian approach allows for interpretable posterior inference, flexible error modeling and the opportunity to include prior information based on historical data or expert knowledge. While both frameworks perform comparably for high-quality data from well-designed studies, the Bayesian approach provides additional robustness when the data are sparse or of limited quality. This is illustrated by modeling accelerated stability data from two solid dosage forms and is further examined by means of artificial data subsets and simulated data.

A universal tool for stability predictions of biotherapeutics, vaccines and in vitro diagnostic products

It is of particular interest for biopharmaceutical companies developing and distributing fragile biomolecules to warrant the stability and activity of their products during long-term storage and shipment. In accordance with quality by design principles, advanced kinetic modeling (AKM) has been successfully used to predict long-term product shelf-life and relies on data from short-term accelerated stability studies that are used to generate Arrhenius-based kinetic models that can, in turn, be exploited for stability forecasts. The AKM methodology was evaluated through a cross-company perspective on stability modeling for key stability indicating attributes of different types of biotherapeutics, vaccines and biomolecules combined in in vitro diagnostic kits. It is demonstrated that stability predictions up to 3 years for products maintained under recommended storage conditions (2-8 °C) or for products that have experienced temperature excursions outside the cold-chain show excellent agreement with experimental real-time data, thus confirming AKM as a universal and reliable tool for stability predictions for a wide range of product types.

Genetically detoxified tetanus toxin as a vaccine and conjugate carrier protein

Tetanus toxoid (TTxd), developed over 100 years ago, is a clinically effective, legacy vaccine against tetanus. Due to the extreme potency of native tetanus toxin, manufacturing and regulatory efforts often focus on TTxd production, standardization, and safety, rather than product modernization. Recently, a genetically detoxified, full-length tetanus toxin protein (8MTT) was reported as a tetanus vaccine alternative to TTxd (Przedpelski et al. mBio, 2020). Here we describe the production of 8MTT in Gor/Met^TM E. coli, a strain engineered to have an oxidative cytoplasm, allowing for the expression of soluble, disulfide-bonded proteins. The strain was also designed to efficiently cleave N-terminal methionine, the obligatory start amino acid for E. coli expressed proteins. 8MTT was purified as a soluble protein from the cytoplasm in a two-column protocol to > 99 % purity, yielding 0.5 g of purified 8MTT/liter of fermentation broth with low endotoxin contamination, and antigenic purity of 3500 Lf/mg protein nitrogen. Mouse immunizations showed 8MTT to be an immunogenic vaccine and effective as a carrier protein for peptide and polysaccharide conjugates. These studies validate 8MTT as commercially viable and, unlike the heterogenous tetanus toxoid, a uniform carrier protein for conjugate vaccines. The development of a recombinant, genetically detoxified toxin produced in E. coli aligns the tetanus vaccine with modern manufacturing, regulatory, standardization, and safety requirements.

Preclinical development of the quadrivalent meningococcal (ACYW) tetanus toxoid conjugate vaccine, MenQuadfi®

Bacterial capsular polysaccharide vaccines are generally poorly immunogenic in infants and older adults. The immunogenicity of capsular polysaccharide vaccines can be improved by conjugating them to immunogenic carrier proteins. One of the most recently licensed conjugate vaccines is the quadrivalent meningococcal vaccine with serogroups A, C, Y, and W conjugated to a tetanus toxoid protein carrier (MenACYW-TT; MenQuadfi, Sanofi Pasteur, Swiftwater, PA, USA). MenACYW-TT was developed to induce optimal immune responses against each of the meningococcal serogroups A, C, W, and Y, and across all age groups, especially infants and older adults (those aged ≥ 50 years). Here, we detail the early iterative vaccine development approach taken, whereby many different ‘small-scale’ conjugate vaccine candidates were prepared and examined for immunogenicity in a mouse model to identify the most immunogenic vaccine. Additional insights from phase I clinical studies informed further optimization of the vaccine candidates by tailoring their conjugation parameter attributes for the optimal immune response in humans. The parameters studied included: different carrier proteins [PR]; polysaccharide [PS] sizes; conjugation chemistries [linker vs. no-linker; lattice vs. neoglycoprotein; activation/derivatization levels]; conjugate size; PS:PR loading ratio; percent free PS; percent free PR; and O-acetylation content. The lead quadrivalent conjugate vaccine (polysaccharides of > 50 kDa size conjugated to TT at a high PS:PR ratio via reductive amination for serogroups C, W and Y, and carbonyldiimidazole/adipic acid dihydrazide linker chemistry for serogroup A) empirically identified from the extensive preclinical studies, was ultimately confirmed by the robust antibody responses observed in all age groups in the various clinical studies, including in the most challenging infant and older adult age groups, and subsequently led to the licensed formulation.

Long-Term Stability Prediction for Developability Assessment of Biopharmaceutics Using Advanced Kinetic Modeling

A crucial aspect of pharmaceutical development is the demonstration of long-term stability of the drug product. Biopharmaceuticals, such as proteins or peptides in liquid formulation, are typically administered via parental routes and should be stable over the shelf life, which generally includes a storing period (e.g., two years at 5 °C) and optionally an in-use period (e.g., 28 days at 30 °C). Herein, we present a case study where chemical degradation of SAR441255, a therapeutic peptide, in different formulations in combination with primary packaging materials was analyzed under accelerated conditions to derive long-term stability predictions for the recommended storing conditions (two years at 5 °C plus 28 days at 30 °C) using advanced kinetic modeling. These predictions served as a crucial decision parameter for the entry into clinical development. Comparison with analytical data measured under long-term conditions during the subsequent development phase demonstrated a high prediction accuracy. These predictions provided stability insights within weeks that would otherwise take years using measurements under long-term stability conditions only. To our knowledge, such in silico studies on stability predictions of a therapeutic peptide using accelerated chemical degradation data and advanced kinetic modeling with comparisons to subsequently measured real-life long-term stability data have not been described in literature before.