Fundamental and Advanced Therapies, Vaccine Development against SARS-CoV-2

Decision trees for early prediction of inadequate immune response to coronavirus infections: a pilot study on COVID-19

Introduction

Few artificial intelligence models exist to predict severe forms of COVID-19. Most rely on post-infection laboratory data, hindering early treatment for high-risk individuals.

Methods

This study developed a machine learning model to predict inherent risk of severe symptoms after contracting SARS-CoV-2. Using a Decision Tree trained on 153 Alpha variant patients, demographic, clinical and immunogenetic markers were considered. Model performance was assessed on Alpha and Delta variant datasets. Key risk factors included age, gender, absence of KIR2DS2 gene (alone or with HLA-C C1 group alleles), presence of 14-bp polymorphism in HLA-G gene, presence of KIR2DS5 gene, and presence of KIR telomeric region A/A.

Results

The model achieved 83.01% accuracy for Alpha variant and 78.57% for Delta variant, with True Positive Rates of 80.82 and 77.78%, and True Negative Rates of 85.00% and 79.17%, respectively. The model showed high sensitivity in identifying individuals at risk.

Discussion

The present study demonstrates the potential of AI algorithms, combined with demographic, epidemiologic, and immunogenetic data, in identifying individuals at high risk of severe COVID-19 and facilitating early treatment. Further studies are required for routine clinical integration.

Safety of administration of BNT162b2 mRNA (Pfizer-BioNTech) COVID-19 vaccine in youths and young adults with a history of acute lymphoblastic leukemia and allergy to PEG-asparaginase

Vaccinationis a critical tool in the prevention of COVID-19 infection for individuals and for communities. The mRNA vaccines contain polyethylene glycol (PEG) as a stabilizer. Currently, in North America, only the BNT162b2 (Pfizer-BioNTech) mRNA vaccine is approved for individuals aged 12-17. Most patients treated with contemporary regimens for acute lymphoblastic leukemia receive PEG-asparaginase (PEG-ASNase) and 10%-30% will develop allergic reactions. Optimizing access and safety for vaccine administration for these patients is critical. This report describes a process developed to support COVID vaccination in a cohort of adolescents and young adults with a history of PEG-ASNase allergy.