EU project aims to personalise epilepsy medicines
And wants to avoid chronicity, prevent relapse and reduce adverse drug reactions
A €7.8m largely European Union (EU)-funded research project is analysing anonymised clinical data from nearly 2,000 epilepsy sufferers to work towards the personalisation of medicine for the condition.
The aim is to create genome-based biomarkers to indicate potential success for epilepsy medicines, and the development of diagnostic tests.
Epilepsy remains poorly understood, with a wide variety of conditions and an even wider variety of outcomes from medicine-based treatment. The EpiPGX project aims to understand why only some patients can be treated successfully, investigating interactions between drugs and genetics. This 'could in the long run personalise treatment and reduce ill-effects of anti-epileptic drugs', said the European Commission. These ill-effects can be serious, added the EC. 'While some patients respond immediately to available drugs, about one quarter are not helped by any medication and only face the adverse drug reactions, such as weight gain, liver dysfunctions or psychiatric conditions.'
The EpiPGX said it wanted to 'avoid chronicity, prevent relapse and reduce adverse drug reactions (ADRs)'.
The project is led by University College London, with scientists from Belgium, Italy, Germany, Ireland, Luxembourg, and the Netherlands also taking part, and will run until October 2015. It is being funded by €5.9m from the EU’s seventh framework programme for research (2007–14), whose budgets are still being spent.
EpiPGX has already established common standards to extract relevant data from existing clinical reports. Its specialists are now analysing the pooled data to see how medicines might interact with genes, drawing on expertise and computing power at the Luxembourg Centre for Systems Biomedicine (LCSB). It is a tough job as the Commission stressed.
'An individual variant of a gene might predispose for a particular reaction to drug treatment but genes do not work alone. All genes interact in multiple ways in living organisms. Detecting the combination of variants that influence each other is challenging…from computation to experimental validation…'.