Quality by design modelling to support rapid RNA vaccine production against emerging infectious diseases

Abstract

Rapid-response vaccine production platform technologies, including RNA vaccines, are being developed to combat viral epidemics and pandemics. A key enabler of rapid response is having quality-oriented disease-agnostic manufacturing protocols ready ahead of outbreaks. We are the first to apply the Quality by Design (QbD) framework to enhance rapid-response RNA vaccine manufacturing against known and future viral pathogens. This QbD framework aims to support the development and consistent production of safe and efficacious RNA vaccines, integrating a novel qualitative methodology and a quantitative bioprocess model. The qualitative methodology identifies and assesses the direction, magnitude and shape of the impact of critical process parameters (CPPs) on critical quality attributes (CQAs). The mechanistic bioprocess model quantifies and maps the effect of four CPPs on the CQA of effective yield of RNA drug substance. Consequently, the first design space of an RNA vaccine synthesis bioreactor is obtained. The cost-yield optimization together with the probabilistic design space contribute towards automation of rapid-response, high-quality RNA vaccine production.

Damien van de Berg

Data-Driven Optimization for the Integration of Interconnected Process Systems

Final-year PhD candidate working at the intersection of optimization and Machine Learning. I investigate how data-driven techniques can aid the optimization of integrated manufacturing and supply chain systems, with a focus on black-box optimization, optimization with embedded neural networks, and Reinforcement Learning for combinatorial optimization. By collaborating with industry, I ensure my case studies are industrially relevant and that my algorithms respect the organizational and business considerations of the process industries.