Nearly 150 million people worldwide are currently infected with the hepatitis C virus. If left untreated, the virus can cause severe liver damage, leading potentially to liver cancer. Powerful drugs have been developed in the recent years that can cure hepatitis C virus infection. A key limitation of these drugs is their susceptibility to drug resistance. The virus mutates rapidly and produces variants that are no longer targeted efficiently by the drugs. Often, these variants can exist in individuals before the start of treatment but go unnoticed because they lie at levels that are below the detection limits of current assays. Patients thus run the risk of being administered ineffective drugs. The different viral mutants that exist in an infected individual define the different drug resistance pathways accessible to the virus at the start of treatment. Drug combinations that block these pathways the most effectively are likely to elicit the best responses. Prof. Dixit and his group in the department of chemical engineering constructed a novel mathematical model to estimate the pre-treatment levels of the entire spectrum of hepatitis C virus mutants resistant to a given drug. The model predictions unravelled the massive diversity of accessible resistance pathways and explained several confounding observations associated with current hepatitis C treatments. The study provides the most sophisticated description so far of hepatitis C virus evolution and presents the framework needed to identify optimal drug treatments and vaccine designs.
1) The New Indian Express:
2) Research Matters: