Next Generation Sequencing for the Detection of Adventitious Contaminants in Biotechnological Products

Adventitious biological contaminants may be unintentionally introduced during biomanufacturing of pharmaceutical products via cell banks, raw materials, or the environment. To ensure the biotechnological product safety and preserve patients’ health, different tests must be performed, as required by health authorities. The aim of my PhD project was to develop methods to rapidly detect different types of biological contaminants, utilizing next-generation sequencing (NGS) technologies for broad-range virus detection and identification. In this thesis, two NGS-based viral safety methods for the detection of viruses in unprocessed bulk harvests (UBH) and cell banks (CB) samples were developed and validated. The method designed for UBH samples aims to mitigate the risk of viral contamination in manufacturing site, while the method for CB samples is intended to replace the current mandatory in-vivo safety tests in alignment with the 3Rs principles (Replacement, Reduction, Refinement). Both these NGS-based methods were successfully validated by assessing the robustness, the specificity and the limit of detection (LOD) according to ICH Q2 (R2) guideline. Finally, a feasibility study for the detection of bacterial contaminants using a dedicated NGS-based workflow was developed. Using this approach, different bioinformatic strategies for data analysis were tested, enabling a preliminary workflow definition for bacterial identification. Overall, two comprehensive NGS-based methods for virus detection were fully developed and validated, starting from two different manufacturing sample types. These findings allowed us to assess the applicability of the NGS technologies for viral safety testing in a regulated and controlled environment. In addition, the feasibility study performed on bacteria detection gave us new insights about the NGS technologies, possibly by broadening its scope for future product safety studies.