Utilization of risk-based predictive stability within regulatory submissions; industry’s experience

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 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.

A Method for Risk Assessment Evaluating the Safety, Stability and Efficacy in Clinical Practice of Anticancer Drug Preparations in the Centralized Compounding Unit of the Veneto Institute of Oncology-IRCCS

BACKGROUND

Preparation of injectable anticancer drugs in hospital pharmacies is a high-risk activity that requires a proper risk assessment (RA) and quality assurance system (QAS) to ensure both a decrease in risk associated with chemotherapy compounding and high quality of the final product, especially in terms of its microbiological stability.

METHODS

At the centralized compounding unit (UFA) of the Italian Hospital IOV-IRCCS, a quick and deductive method was applied to evaluate the "added value" provided by each prescribed preparation, and its RA was calculated applying a formula that integrates different pharmacological, technological and organizational aspects. According to specific RA range values, the preparations were divided into different risk levels, in order to determine the QAS to be adopted, according to the Italian Ministry of Health guidelines, whose adherence was meticulously evaluated through a specific self-assessment procedure. A review of the scientific literature was carried out to integrate the risk-based predictive extended stability (RBPES) of drugs with data concerning their physiochemical and biological stability.

RESULTS

Based on the self-assessment comprising all microbiological validations of the working area, personnel and products, the microbiological risk level within the IOV-IRCCS' UFA was defined through the creation of a transcoding matrix, conferring a microbiological stability to preparations and vial leftovers of a maximum of 7 days. The calculated RBPES were successfully integrated with stability data from the literature, leading to the drafting of a stability table of drugs and preparations in use in our UFA.

CONCLUSIONS

Our methods allowed us to perform an in-depth analysis of the highly specific and technical process of anticancer drug compounding in our UFA, ensuring a certain grade of quality and safety to preparations, especially in terms of microbiological stability. The resulting RBPES table represents an invaluable tool with positive repercussions at organizational and economic levels.

Screening Autoxidation Propensities of Drugs in the Solid-State Using PVP and in the Solution State Using N-Methyl Pyrrolidone

Oxidative degradation of drugs is one of the major routes of drug substance and drug product instability. Among the diverse routes of oxidation, autoxidation is considered to be challenging to predict and control, potentially due to the multi-step mechanism involving free radicals. C–H bond dissociation energy (C–H BDE) is evidenced to be a calculated descriptor shown to predict drug autoxidation. While computational predictions for the autoxidation propensity of drugs are both swift and possible, no literature to date has highlighted the relationship between the computed C–H BDE and the experimentally-derived autoxidation propensities of solid drugs. The objective of this study is to investigate this missing relationship. The present work is an extension to the previously reported novel autoxidation approach that involves subjecting a physical mixture of pre-milled polyvinyl pyrrolidone (PVP) K-60 and a crystalline drug under high temperature and pressurized oxygen setup. The drug degradation was measured using chromatographic methods. An improved trend between the extent of solid autoxidation and C–H BDE could be observed after normalizing the effective surface area of drugs in the crystalline state, pointing to a positive relationship. Additional studies were conducted by dissolving the drug in N-methyl pyrrolidone (NMP) and exposing the solution under a pressurized oxygen setup at diverse elevated temperatures. Chromatographic results of these samples indicated a similarity in the formed degradation products to the solid-state experiments pointing to the utility of NMP, a PVP monomer surrogate, as a stressing agent for faster and relevant autoxidation screening of drugs in formulations.

Modeling Approaches to Reimagine Stability (MARS) for Enabling Earlier Access to Critical Drugs for Patients with Unmet Medical Needs

FDA's experience to date has shown that completion of stability data requirements is one of the most observed challenges for applicants of New Drug Applications (NDAs) with an expedited review designation. Since NDAs submitted under these expedited pathways often have limited available real-time stability data from the primary batches, Modeling Approaches to Reimagine Stability (MARS) have been proposed to support establishment of tentative retest periods of the drug substance and/or expiration dating period (shelf-life) of the drug product. MARS incorporate statistical principles and available tools as a part of the predictive models. In this study, a data mining exercise has been conducted with regulatory submissions of Investigational New Drug (IND) Applications, NDAs, and Abbreviated New Drug Applications (ANDAs) containing MARS data. The case studies presented herein demonstrate how MARS data has been applied to regulatory scenarios involving prediction of retest and/or shelf-life, bridging major development changes, and confirming that no degradation has been observed or predicted. Using the assumption of a linear time trend for those cases that do not display sufficient degradation to conduct MARS for projection of an expiration date, an analysis of covariance (ANCOVA) model is developed and described herein to test the hypothesis of zero slope by a p-value method. Our results show that the application of MARS adequately supported establishment of a tentative commercially viable retest date/shelf-life, thus enabling earlier access to critical drugs for patients with unmet medical needs.

Accelerated Shelf Life Modeling of Appearance Change in Drug Products Using ASAPprime®

An accelerated stability model approach was demonstrated to accurately predict the long-term shelf life of example drug substances and drug products (indigo carmine tablets and L-ascorbic acid powder) where appearance changes were shelf life-limiting. The products were exposed outside of packaging to conditions from 50-90 °C and 0-80% relative humidity for up to one month to accelerate appearance changes. The appearance changes of stressed samples were quantitated using the CIELAB color scale (calculated ΔE*), where a visual assessment of appearance changes likely to be noticeable was used to assign a ΔE* specification limit. ASAPprime^® software was employed to create an isoconversion paradigm, modeled in packaging by the moisture-modified Arrhenius equation, that predicted the color changes of the products within the error bars of the model to nine months at 25 °C/60% RH, 30 °C/65% RH, and 40 °C/75% RH. Overall, these case studies indicate that the ASAPprime^® approach for accelerated stability studies are a fast, accurate approach to modeling appearance changes.

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.

Long-term stability predictions of therapeutic monoclonal antibodies in solution using Arrhenius-based kinetics

Long-term stability of monoclonal antibodies to be used as biologics is a key aspect in their development. Therefore, its possible early prediction from accelerated stability studies is of major interest, despite currently being regarded as not sufficiently robust. In this work, using a combination of accelerated stability studies (up to 6 months) and first order degradation kinetic model, we are able to predict the long-term stability (up to 3 years) of multiple monoclonal antibody formulations. More specifically, we can robustly predict the long-term stability behaviour of a protein at the intended storage condition (5 °C), based on up to six months of data obtained for multiple quality attributes from different temperatures, usually from intended (5 °C), accelerated (25 °C) and stress conditions (40 °C). We have performed stability studies and evaluated the stability data of several mAbs including IgG1, IgG2, and fusion proteins, and validated our model by overlaying the 95% prediction interval and experimental stability data from up to 36 months. We demonstrated improved robustness, speed and accuracy of kinetic long-term stability prediction as compared to classical linear extrapolation used today, which justifies long-term stability prediction and shelf-life extrapolation for some biologics such as monoclonal antibodies. This work aims to contribute towards further development and refinement of the regulatory landscape that could steer toward allowing extrapolation for biologics during the developmental phase, clinical phase, and also in marketing authorisation applications, as already established today for small molecules.

Science and Risked-Based Stability Testing Strategies-a Test Case on the Global Implementation and Regulatory Reception

The global regulatory implementation and acceptance of a science and risk-based stability (SRB) strategies for a stable drug product is reviewed. This stability strategy may also be referred to as "lean stability" since it includes a stability protocol reduction in the number of tests and time points than might normally be applied. A product line extension (new solid dosage form) for a well-understood product was used as a test case for this stability strategy. The drug product line extension was filed globally with a proposed reduction to analytical stability tests and frequency. This stability protocol is aligned with the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) Q1A (R2) stability guidelines (ICH: Guideline Q1A(R2), 2003), the World Health Organization (WHO) (WHO INT. [Online], 2020), and most country regulatory guidelines. Although this strategy was not accepted universally, the strategy enabled opportunities to engage in productive dialogs with regulatory authorities in several countries on how the case leveraged product understanding and development knowledge to develop a fit for purpose stability protocol. A persistent and consistent effort from industry to move toward product-specific protocols based on product knowledge and stability risk assessments should lead to further acceptance of science and risk-based stability strategies in all regions.