Monitoring the production of AAV vectors in insect cells by fluorescence spectroscopy

Adeno-associated viruses (AAV) are among the most promising viral vectors for gene therapy, since they can transduce non-dividing cells from several tissues while maintaining a long-term gene expression. Besides, AAVs possess low immunogenicity compared to other viral vectors, and are physically resistant, which makes them resilient to industrial manufacturing conditions, long-term storage, and in vivo administration. One of the systems available for large scale production of AAVs is the insect cell-baculovirus expression vector system (IC-BEVS). Insect cells grow in suspension to high cell densities with modest growth requirements and without the need of serum supplementation. Consequently, scaling up the production in order to achieve the large number of AAV needed for clinical trials is more straight‑forward than with transfection-based systems. However, methods for online monitoring of AAV production are still lacking. Such methods would allow determination of the best time of harvest in real-time, thus allowing recovery of AAV as soon as its concentration medium was higher. Here we apply Fluorescence Spectroscopy to baculovirus-infected insect cell cultures producing adeno‑associated virus vectors, correlating the spectra to critical process parameters like cell concentration, viability and AAV concentration. Sf9 cells were co-infected with two baculovirus (expressing AAV rep and cap and a CMV-GFP transgene) at low or high multiplicities of infection (MOI), and the culture was followed by Fluorescence Spectroscopy in situ through a bioreactor probe. After an exploratory calibration using data from only one bioreactor, we attested the aptitude of this technique to capture overall data trend: using a 3 component PLS model, we have obtained a calibration NRMSE of 2.9% for total AAV particles per cell, 5.9% for viable cell density and 0.9% for viability). Additional bioreactor productions using different infection parameters (CCI, MOI, time of infection) allowed testing the robustness of fluorescence monitoring to process variability. With this dataset, we tested several pre-treatment methods for the raw spectra, as well as different regression algorithms in order to establish a good predictive model. Ultimately, fluorescence spectroscopy provides a simple tool for online monitoring of key process variables in baculovirus-infected insect cell cultures. Acknowledgments: Funding from Fundação para a Ciência e a Tecnologia, projects EXPL/BBBBIO/1129/2013 and Daniel Pais’ PhD research grant PD/BD/105873/2014

Enabling PAT in insect cell bioprocesses: A monitoring toolbox for rAAV production

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A prediction rule to stratify mortality risk of patients with pulmonary tuberculosis

Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8-7.9), age >= 50 years (OR 2.9, 95% CI 1.7-4.8), bilateral lung involvement (OR 2.5, 95% CI 1.44.4), >= 1 significant comorbidity-HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease-(OR 2.3, 95% CI 1.3-3.8), and hemoglobin = 6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment.This work was supported by Fundacao Amelia de Mello/Jose de Mello Saude and Sociedade Portuguesa de Pneumologia (SPP). This work was developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). NSO is a FCT (Fundacao para a Ciencia e Tecnologia) investigator. MS is an Associate FCT Investigator. The fundershad no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript