PharmaLex Statistics and Data Science team is joining the Inno4vac interdisciplinary partnership.
Funded by the Innovative Medicines Initiative 2 (IMI2), the partnership aims to “foster health innovation by incorporating scientific and technological breakthrough from the academic and biotech sectors into industry”. It’s coordinated by the European Vaccine Initiative (based in Germany), with the support from the Sclavo Vaccines Association (based in Italy), for the scientific coordination, and involves 41 partners from 11 different European countries, including 37 academic institutions and SMEs, as well as GSK, Sanofi Pasteur, CureVac and Takeda as industry partners.
Under PharmaLex guidance, mathematical and statistical models will be developed, designed to accelerate the development and improve the quality of vaccines. The company’s team will share its 10-year experience in bioprocesses with a consortium of experts.
The ultimate goal of the combined effort pursued by Inno4vac is to develop more predictive biological and mathematical models of vaccine performance, and thereby to accelerate the development of vaccines. A sustainability plan will also be carried out by the project partners to ensure the long-term access to the results, including models, beyond the duration of the project.
The PharmaLex team will contribute to develop and qualify mathematical and statistical models that will be made available on the computational platform. It will also deliver in silico modelling of vaccine bio-manufacturing and stability testing. The expertise of the PharmaLex team in applied Bayesian statistics, Machine Learning and Artificial Intelligence will be used for three main purposes, it says:
Multivariate Bayesian models to assist Design Space determination for the development of vaccine product guaranteeing product quality and stability by assessing the impact of CPPs on CQAs and stability.
Models to predict vaccine stability, including accelerated testing. It implies assessing stability within a reduced amount of time in the framework of development studies, evaluating the risk of temperature excursions, support shelf-life approval and comparability in case of change of bioprocess.
Models to evaluate and guarantee the robustness of the process and the product.
All those mathematical models will be implemented in the cloud-based bio-manufacturing platform.
