In the present study the compositional analysis of the amino acids released by the acidic hydrolysis of the vaccine antigens was approached as an alternative to the dye-binding methods, for improvement of the quality control. In particular, the Analytical Quality by Design principles were undertaken in optimizing the hydrolysis conditions of the antigens to be applied prior to the quantitation by UHPLC-UV. Bexsero was used as a case study; it is a recombinant meningococcal B vaccine and one of its critical quality attributes is the content of the three core protein antigens, namely Neisseria Heparin Binding Antigen, factor H binding protein and Neisseria adhesin A, in the final formulation. Conventionally, the proteins quantitation is carried out by dye-binding assays. Analytical Target Profile was defined as the accurate determination of amounts of the Bexsero antigens. The Critical Method Parameters were chosen by means of the cause-effect matrix. A Face Centered Design was used to select the experiments to investigate the process and finally a Method Operable Design Region with a risk of failure of 5% was defined. The selected working point for routine use was: hydrolysis time, 17 hrs; temperature, 112 °C; 6 M HCl volume, 300 µl; antioxidant 90% phenol volume, 5 µl.

The One Health (OH) approach describes the interconnection between the health of animals, humans, and the environment. The need for collaboration between the veterinary and human fields is increasing due to the rise in several infectious diseases that cross human-animal barriers and need to be addressed jointly. However, such collaboration is not evident in practice, especially for non-zoonotic diseases. A qualitative research approach was used to explore the barriers and enablers influencing collaborative efforts on the development of vaccines for the non-zoonotic RSV virus. It was found that in the European context, most veterinary and human health professionals involved in RSV vaccine development see themselves as belonging to two distinct groups, indicating a lack of a common goal for collaboration. Next to this, the different conceptualizations of the OH approach, and the fact that RSV is not a zoonotic disease, strengthens the opinion that there is no shared need for collaboration. This paper adds insights on how, for a non-zoonotic situation, collaboration between human and veterinary professionals shaped the development of vaccines in both areas; thus, improving public health requires awareness, mutual appreciation, and shared goal setting.

Usefulness of Vaccine-Adverse Event-Reporting System (VAERS) data and protocols required for statistical analyses were pinpointed with a set of recommendations for the application of machine learning modeling or exploratory analyses on VAERS data with a case study of COVID-19 vaccines (Pfizer-BioNTech, Moderna, Janssen). A total of 262,454 duplicate reports (29%) from 905,976 reports were identified, which were merged into a total of 643,522 distinct reports. A customized online survey was also conducted providing 211 reports. A total of 20 highest reported adverse events were first identified. Differences in results after applying various machine learning algorithms (association rule mining, self-organizing maps, hierarchical clustering, bipartite graphs) on VAERS data were noticed. Moderna reports showed injection-site-related AEs of higher frequencies by 15.2%, consistent with the online survey (12% higher reporting rate for pain in the muscle for Moderna compared to Pfizer-BioNTech). AEs {headache, pyrexia, fatigue, chills, pain, dizziness} constituted >50% of the total reports. Chest pain in male children reports was 295% higher than in female children reports. Penicillin and sulfa were of the highest frequencies (22%, and 19%, respectively). Analysis of uncleaned VAERS data demonstrated major differences from the above (7% variations). Spelling/grammatical mistakes in allergies were discovered (e.g., ~14% reports with incorrect spellings for penicillin).

Vaccine development and implementation decisions need to be guided by accurate and robust burden of disease data. We developed an innovative systematic framework outlining the properties of such data that are needed to advance vaccine development and evaluation, and prioritize research and surveillance activities. We focus on 4 objectives-advocacy, regulatory oversight and licensure, policy and post-licensure evaluation, and post-licensure financing-and identify key stakeholders and specific requirements for burden of disease data aligned with each objective. We apply this framework to group A Streptococcus, a pathogen with an underrecognized global burden, and give specific examples pertinent to 8 clinical endpoints. This dynamic framework can be adapted for any disease with a vaccine in development and can be updated as vaccine candidates progress through clinical trials. This framework will also help with research and innovation priority setting of the Immunization Agenda 2030 (IA2030) and accelerate development of future vaccines.

Preventative vaccines are considered one of the most cost-effective and efficient means to contain outbreaks and prevent pandemics. However, the requirements to gain licensure and manufacture a vaccine for human use are complex, costly, and time-consuming. The 2013-2016 Ebola virus disease (EVD) outbreak was the largest EVD outbreak to date and the third Public Health Emergency of International Concern in history, so to prevent a pandemic, numerous partners from the public and private sectors combined efforts and resources to develop an investigational Zaire ebolavirus (EBOV) vaccine candidate (rVSVΔG-ZEBOV-GP) as quickly as possible. The rVSVΔG-ZEBOV-GP vaccine was approved as ERVEBOTM by the European Medicines Authority (EMA) and the United States Food and Drug Administration (FDA) in December 2019 after five years of development. This review describes the development program of this EBOV vaccine, summarizes what is known about safety, immunogenicity, and efficacy, describes ongoing work in the program, and highlights learnings applicable to the development of pandemic vaccines.