RESUMO
The global COVID-19 pandemic ignited an unprecedented race to develop vaccines and antibody therapeutics. AstraZeneca's pursuit to provide AZD7442 (EVUSHELD), two long-acting, SARS-CoV-2 spike receptor binding domain-specific neutralizing monoclonal antibodies, to individuals at risk on highly accelerated timelines challenged our traditional ways of process development and spurred the rapid adoption of novel approaches. Conventional upstream development processes were replaced by agile strategies that combined technological advances and highly accelerated workflows. With calculated business risks and close cross-functional collaborations, this process paved the way for hyper accelerated antibody development from discovery through manufacturing, process validation, emergency use authorization filing, and global regulatory approvals. The result was initiation of commercial manufacturing at a contract manufacturing organization less than 6 months from the selection of cilgavimab and tixagevimab-a process that historically has taken close to 10 years.
RESUMO
During manufacturing and storage process, therapeutic proteins are subject to various post-translational modifications (PTMs), such as isomerization, deamidation, oxidation, disulfide bond modifications and glycosylation. Certain PTMs may affect bioactivity, stability or pharmacokinetics and pharmacodynamics profile and are therefore classified as potential critical quality attributes (pCQAs). Identifying, monitoring and controlling these PTMs are usually key elements of the Quality by Design (QbD) approach. Traditionally, multiple analytical methods are utilized for these purposes, which is time consuming and costly. In recent years, multi-attribute monitoring methods have been developed in the biopharmaceutical industry. However, these methods combine high-end mass spectrometry with complicated data analysis software, which could pose difficulty when implementing in a quality control (QC) environment. Here we report a multi-attribute method (MAM) using a Quadrupole Dalton (QDa) mass detector to selectively monitor and quantitate PTMs in a therapeutic monoclonal antibody. The result output from the QDa-based MAM is straightforward and automatic. Evaluation results indicate this method provides comparable results to the traditional assays. To ensure future application in the QC environment, this method was qualified according to the International Conference on Harmonization (ICH) guideline and applied in the characterization of drug substance and stability samples. The QDa-based MAM is shown to be an extremely useful tool for product and process characterization studies that facilitates facile understanding of process impact on multiple quality attributes, while being QC friendly and cost-effective.