Project Members
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Sonali Parbhoo
PhD Candidate
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Mario Wieser
PhD Candidate
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SystemsX.ch HIV-X: Deciphering Host-Virus Interactions to Cure HIV
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What is HIV?
The Human Immunodeficiency Virus (HIV) is the cause of a pandemic that currently affects more than 36 million individuals worldwide. The virus infects the CD4+ helper cells and therefore harms the immune system of an individual. HIV belongs to the class of retroviruses and is characterized by both its high replication and high mutation rate. This characteristic causes resistance against available HIV drugs where prolonged use of the drugs has occurred. To overcome this problem, patients are treated with cycled combinations of antiretroviral drugs which is known as Highly Active Antiretroviral Therapy (HAART). However, to this day it is not possible to cure HIV because a part of the virus population still remains in the body as a latent reservoir.
Project Overview
This project consists of eight groups with research focuses ranging from medicine to machine learning. We are analyzing 1600 patients from the Swiss HIV Cohort Study (SHCS) who are more than five years under successful HAART treatment. For analyzing the interactions between host and virus, we are using various data including the host and virus genome, CD4+/CD8+ counts, viral loads, treatments as well as the viral reservoir decay.
Project Aim
The aim of this project is to identify host and viral factors that have an impact on the pathomechanisms of HIV latency. Based on these factors, we derive models to predict treatment responses for individual patients to improve treatment planning.
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1. Data input, e.g. genotype or phenotype data.
2. Constructing a network of dependencies between host and virus data.
3. Mapping of network to a subspace of relevant health descriptors.
4. Personalised inference of treatments for individual patients based on their history and health descriptors.
Funding
This project is supported by the Swiss National Science Foundation (SNF) and SystemsX.ch.