Student combating tuberculosis with algorithms
A Lincoln student is hunting for a universal vaccine for over 140 strains of tuberculosis (TB) which kill 1.4 million people every year worldwide, in a computer lab.
According to the WHO, TB infection is currently spreading at the rate of one person per second. It kills more young people and adults than any other infectious disease and is the world's biggest killer of women
Pooja Pawar is a PhD student at the Complex Systems, Big Data and Informatics Initiative (CSBII) at Lincoln University, and is supervised by Professor Sandhya Samarasinghe and Professor Don Kulasiri.
“Despite the great success of vaccines, new vaccines are still needed for re-emerging and drug-resistant pathogens. The process of development and production is very costly and it takes many years to develop an effective vaccine,” Pooja says.
“Moreover, currently, there is no approach available for developing an effective universal vaccine.”
Computational vaccinology using algorithms lessens the time and cost required for laboratory analysis and produces safer options which can be less likely to have an adverse reaction.
Certain areas of a pathogen- a virus or bacteria- elicit a response from the body to fight back. These are targeted in vaccinations to prepare the body to fight when exposed to the full pathogen, but can be different areas in different pathogen strains, as they can quickly mutate.
Pooja’s research is focused on a very promising and novel conceptual approach to determining targets for universal vaccines with a broad coverage and specific immunity using advanced Bioinformatics Modelling and Computational Vaccinology, combined with a deep understanding of the mechanisms of the disease and its host –pathogen interactions.
She has chosen TB as the case study to test the efficacy of the concept while intending to find the most crucial vaccine targets for TB.
Currently, there is only one licensed vaccine available for TB, called BCG, that was designed from only one strain of the bacteria. This vaccine protects babies and young children; however, it fails to protect adults.
The low efficacy of BCG, reemergence of the disease in immunocompetent individuals and growth in the number of drug-resistant strains have generated an urgent requirement for a powerful and effective vaccine. Computer Vaccinology has great potential to fill this need.
The Complex Systems, Big Data and Informatics Initiative (CSBII) at Lincoln University aims to transform the way we perceive and solve complex problems through trans-disciplinary integration of advanced domain knowledge and cutting-edge complex systems, big data and informatics methodologies to provide effective and flexible solutions to evolving grand challenges. These challenges include transformations in Agriculture and Biological systems; Health, Disease and Wellbeing; Sustainable Environments, Ecosystems and Societies; and Artificial Intelligence and Digital Methodology Innovations to promote these transformations.