EuResist Network GEIE improves HIV treatment with more accurate patient modeling

Validated on 12 Mar 2013

"Accurately simulating the interactions of HIV treatment drugs within a human body is no easy endeavor. And with IBM, we’ve managed to create one of the most successful tools to do so." - EuResist Network GEIE

Customer:
EuResist Network GEIE

Industry:
Healthcare

Deployment country:
Italy

Solution:
Smarter Planet

Smarter Planet:
Smarter Healthcare

The EuResist Network GEIE is a nonprofit economic interest group dedicated to promoting medical research among its members. It works to support clinical management of antiretroviral drug resistance, focusing its efforts on improving the success rate of human immunodeficiency virus (HIV) treatment while minimizing its evolving drug resistance.

Business need:
EuResist Network GEIE was looking to help physicians determine the optimal com­bination of HIV treatment drugs that would help patients while limiting the evolution of drug resistance. Previously, physicians based much of their decision making on personal experience and limited prediction tools. But EuResist hoped to introduce a better modeling solution that would better reflect patient reactions.

Solution:
Working with IBM Research, EuResist developed a drug interaction modeling tool that lets users predict the success rate and impact on virus evolution of various drug combinations via an online portal. The prediction engine, operating within an IBM WebSphere® Application Server environment, leverages medical data (for example, viral gene sequences, patient histories) from seven sources hosted within an IBM DB2® data server.

Benefits:
Improves the accuracy of prediction of patient response to therapy to 76 percent, outperforming other common tools; compares patient details against 41,000 previous cases and treatment data to help choose a therapy with a high probability of success; reduces incidents of treatment-related toxicity by pulling data from seven sources to create more accurate patient models

IBM products and services that were used in this case study.

Software:
WebSphere Application Server, DB2 Enterprise 9

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