Researchers from the Universidade de São Paulo have demonstrated the effectiveness of near-infrared spectroscopy combined with chemometric models for real-time, precise monitoring of Zika virus-like particle vaccine production.
The Zika virus has led to numerous, ongoing public health challenges that scientists are trying to solve. In a recent study, a team of researchers from the Universidade de São Paulo examined how to improve the optimization of upstream production monitoring for Zika virus-like particles (VLP) vaccines using near-infrared (NIR) spectroscopy (1). This study aimed to help spur advancements in monitoring biopharmaceutical production processes, and it has potential implications for future real-time monitoring of vaccine production.
The Zika virus was declared a public health emergency by the World Health Organization (WHO) (1). It is spread largely by the Aedes species of mosquitos (2). If infected with the virus, people can experience a range of symptoms, some mild and some quite serious. For mild symptoms, people can feel feverish, develop rashes and headaches, and experience joint and muscle pain (2). However, on the more serious end of symptoms, microcephaly and other birth defects can develop for infants as a consequence of infection during pregnancy (1,2).
Zika virus aedes aegypti mosquito on human skin - Dengue, Chikungunya, Mayaro, Yellow fever. Generated by AI. | Image Credit: © farah - stock.adobe.com
Currently, scientists know that the Zika virus is most prevalent in tropical and subtropical areas were Aedes mosquitos generally reside. Some of these regions include southern Asia and the subtropical region of Africa (2).
To help contain the spread of the Zika virus, scientists have and continue to improve on VLP-based vaccines. These vaccines have gained prominence because they lack genetic material, making them hypoallergenic, non-infectious, and non-mutant (1).
Producing VLP vaccines requires meticulous bioprocess monitoring to ensure consistency, efficiency, and safety. This study explores the potential of NIR spectroscopy, coupled with advanced chemometric tools, to modernize the monitoring process by providing real-time, non-invasive analysis (1).
In this study, the researchers conducted seven experiments using a recombinant baculovirus/Sf9 insect cell platform. This system was employed in benchtop bioreactors to simulate upstream production processes for Zika VLP vaccines (1). NIR spectroscopy was used to capture spectral data, which was then analyzed using two popular chemometric approaches: partial least squares (PLS) and artificial neural networks (ANNs) (1).
By comparing various conditions, including sample types (with or without cells) and analytical blanks (air or ultrapure water), the researchers aimed to identify the optimal configurations for monitoring key biochemical variables. These variables included viable cell density, cell viability, and concentrations of critical nutrients and metabolites such as glucose, lactate, glutamine, glutamate, ammonium, and potassium (1).
The study's results showed that precision and accuracy in predicting biochemical parameters improved. These findings underscore the capability of NIR spectroscopy, combined with PLS and ANN models, to provide robust, real-time insights into complex bioprocesses (1).
This research addresses a critical gap in biopharmaceutical production by offering a systematic comparison of sampling conditions, analytical blanks, and spectral pre-processing methods. The integration of NIR spectroscopy as a process analytical technology (PAT) aligns with the pharmaceutical industry's push for more efficient and precise bioprocess monitoring.
As the Zika virus continues to pose global health challenges, innovations in vaccine production and monitoring are crucial. Although the Zika virus does not have an approved vaccine yet, work is being done in this field to at least help people manage symptoms (2). This study highlights the potential for interdisciplinary approaches—merging spectroscopy, bioprocess engineering, and artificial intelligence (AI)—to drive advancements in public health interventions (1). The combination of NIR spectroscopy and chemometric modeling offers a promising pathway to optimize production processes, ensuring rapid and reliable responses to emerging health crises (1).
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