Research Interest

Peptide based Vaccine Design: Vaccine is considered to be most effective and safest method in controlling viral infection. Towards this end, peptide as a choice of vaccine candidate offer great advantages as it contains conserved multiple immunogenic epitopes with wide HLA-restrictions, absence of infectious potential and self-reactivity, and easy to produce. Our research group are working on different immunoinformatics approach which includes epitope prediction algorithms, molecular docking and simulation and HLA-coverage analysis tools in designing epitopes enriched peptide against Infleunza, Ebola, Zika virus and Orthohantavirus. Selected potential were then assessed for their immunogenic response in experimental system.

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Artificial intelligence approach in disease prediction and management: Artificial intelligence system have proven to be effective in different health sector. Our group is applying different machine learning approaches in prediction and classification of Multiple Sclerosis based on serum cytokines and MRI. We are also applying this approach in prediction and management of cancer based on different SNPs.

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Application of nanomaterial as cancer therapy and adjuvant: Nanotechnology presents an innovative platform for different therapeutic application. One of my PhD student is working on thermo-chemotherapeutic effects of magnetic nanoparticles on cancer cells. Application of nanoparticles as adjuvant in vaccine formulations allows higher antigen stability and immunogenicity as well as target delivery and slow release of antigen. We are also working on development of hybrid nanoparticle as adjuvant against viral peptide vaccine candidates.

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