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MEDICAL RESEARCH
 A better way to predict effectiveness of HIV treatment at hand
Despite the growing number of approved treatments for HIV, experts say the virus is becoming resistant to some drugs and is spinning off other strains. In order to ensure the effectiveness of anti-HIV drugs, a combination or "cocktail" of drugs must be used. These drugs are prescribed as the patient's individual virus progresses and as resistance to the drugs change. Joining this fight is a group of European and Israeli researchers who are co-developing an EU-funded integrated system for clinical management of antiretroviral drug resistance called EuResist.
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This innovative project will give clinicians the tools they need to predict the response to antiretroviral treatment for HIV patients. Project partners will develop a number of prediction engines, including evolutionary models, mutual information-based data mining and case-based reasoning.
Clinicians will finally be able to select the best drugs and cocktails for treating their patients. The consortium is using EuResist's biomedical information integration technology to collect data from three leading HIV databases in Europe: ARCA of Italy, AREVIR of Germany and Sweden's Karolinska Infectious Diseases and Clinical Virology Department.
Included in the data collection are treatment response information, treatment histories and the sequence of the relevant part of the HIV genome from more than 17 000 patients. The database is continuously growing. The work being carried out by EuResist will result in the emergence of one of the biggest integrated data sets worldwide.
Partners of EuResist include Italy's Informa Srl as coordinator, as well as Israel's IBM Haifa Research Lab, Sweden's Karolinska, University Hospital of Cologne in Germany, RMKI of Hungary and the European Federation of Pharmaceutical Industries and Associations (EFPIA).
'If we look closely at the current patient's blood work, virus stage, family history, race and so forth, and then compare it to the thousands of people who have been treated over the years, we can see what was done, what worked and what didn't,' explains Professor Maurizio Zazzi, scientific coordinator of EuResist and professor of microbiology at the University of Siena School of Medicine. He notes that the history data will help the project partners to predict how the virus will respond to a certain cocktail.
'This method not only provides a huge savings in costs, it also means a patient's chances for successful treatment are not dependant on their doctor's individual knowledge,' Prof. Zazzi goes on to say.
IBM Haifa Research Lab's Boaz Carmeli says the history of treatments and the progress of the virus must be monitored to ensure successful patient care. 'Tapping into knowledge garnered from a huge collection of data will help doctors take into account the patient, the virus, the viral mutations and the current stage of the disease,' he says.
To date, the EuResist project is bearing fruit. Results are showing a whopping success rate of 75 percent. The partners are currently comparing the treatment predictions generated by the system with training sets, as well as with actual patient data.
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More information:
EuResist
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