Vaccine clinical trials often generate a large number of immune measures at multiple time points. By using data from such trials, we develop new computational methods to carry out 1) univariate and correlation analyses, 2) multivariate analysis, and 3) mathematical modeling to identify potential correlates of protection or mechanisms of action in vaccine studies. We work closely with clinical collaborators on a range of infectious diseases, including malaria and dengue fever.
Chaudhury, S., E. H. Duncan, T. Atre, C. K. Storme, K. Beck, S. A. Kaba, D. E. Lanar, and E. S. Bergmann-Leitner. Identification of immune signatures of novel adjuvant formulations using machine learning. Scientific Reports. 2018 November 30; 8(1):17508. [PDF, PubMed]
Chaudhury, S., J. A. Regules, C. A. Darko, S. Dutta, A. Wallqvist, N. C. Waters, E. Jongert, F. Lemiale, and E. S. Bergmann-Leitner. Delayed fractional dose regimen of the RTS,S/AS01 malaria vaccine candidate enhances an IgG4 response that inhibits serum opsonophagocytosis. Scientific Reports. 2017 August 11; 7:7998. [PDF, PubMed]
Chaudhury, S., C. F. Ockenhouse, J. A. Regules, S. Dutta, A. Wallqvist, E. Jongert, N. C. Waters, F. Lemiale, and E. Bergmann-Leitner. The biological function of antibodies induced by the RTS,S/AS01 malaria vaccine candidate is determined by their fine specificity. Malaria Journal. 2016 May 31; 15:301. [PDF, PubMed]