
Individual medical studies are an essential tool in testing treatments for diseases, but when the results of several are combined, their collective power increases exponentially. Knowledge synthesis (KS) – the discipline of synthesizing the results of different studies − is the area of Dr. Areti Angeliki Veroniki’s expertise, and it is her mission to improve how KS is carried out.
The focus of Dr. Veroniki’s work, which won the 2017 Polanyi Prize for Physiology/Medicine, is developing methods for improving network meta-analysis (NMA), a process which brings together and compares several studies on trials of different interventions, such as drugs. NMAs are designed to discern which of the interventions are most effective on which types of patient, but the challenge is how to compare results from studies that may have used very different methodologies.
Dr. Veroniki’s research focuses on the use of individual patient data – the gold standard of study data – in the NMA process, as well as how to account for the risks of bias in each study’s data and potential inconsistencies across studies. More accurate synthesis of studies will lead to better decision-making on which interventions to use, and which are more effective for treating different groups of patients, for example those under or over certain ages. The use of individual patient data will help tailor findings – and therefore interventions − to individual patients.
Dr. Veroniki, who is a Postdoctoral Fellow at the Li Ka-Shing Knowledge Institute at St. Michael’s Hospital and the University of Toronto, moved from Greece to Canada to pursue her work in 2014. She says her research could result in better treatments for diseases such as Alzheimer’s Disease and Type-1 diabetes.