Faster Development Of Drugs Using Machine Learning

The Problem

Developing a new medicine to successfully treat a disease could take years of research. It is estimated that developing a new treatment takes an average of $2.6 Billion. A lot of this money is wasted as it is spent on research and development of therapies that do not succeed. Can pharmaceutical companies using latest tech to improve the process?

Solution

Machine Learning models deployed on Kranium can greatly help in the discovery and development of new drugs. Machine learning models can use vast data sets to rapidly identify patient response markers and develop drugs cheaply and efficiently.

Models can be used to quicken various stages of Drug Development including:

• Identifying good targets for treating diseases from large data
• Finding a compound that can interact with the identified target molecule in desired way
• Identifying suitable candidates for clinical trials
• Finding biomarkers for disease diagnosis