Developing BioInteract technology to identify therapeutic drug targets in genetic disease models

Higher drug discovery failure rate has led to an increase in drug prises in the market. BioInteract technique is designed to combat the failure rate by identifying most potential therapeutic drug for a broad range of genetic diseases by analysing the drug effect at molecular level. It is a scoring system that can rank drugs based on their ability to restore the key interactors at the molecular level in the mutant cell and thus predict how successful a drug will be in the given disease. The drug with higher score will be more likely to have fewer side effects and provide more normal levels of functionality. This information would be advantageous for drug discovery companies as they can eliminate a lot of ineffective drugs at preclinical stage and hence help reduce the cost burden due to drug failure. BioInteract can also helps find new interactors which could be better drug targets for the genetic disease. This technique will be validated using a pilot study on Autosomal Dominant Polycystic Kidney Disease (ADPKD). It is a genetic disorder causing cyst formation on kidneys. It is a 4th leading cause of end-stage renal disease in Canada.

Faculty Supervisor:

Gagan Gupta

Student:

Dhairya Patel

Partner:

BioInteract

Discipline:

Biology

Sector:

Professional, scientific and technical services

University:

Ryerson University