Web-based, analytic software tools help pharmaceutical firms keep patient recruitment on track for clinical trials.
In the pharmaceutical and life sciences industries, it's estimated that 70% of clinical trials are delayed due to patient enrollment problems. Those delays can tag on millions of dollars of added research and development and other costs to trials, not to mention cause postponements to promising new treatments entering the market.
Some pharmaceutical companies, including GlaxoSmithKline, are starting to get a better handle on patient enrollment issues earlier on in trials, helping them take action sooner to keep clinical trials on track.
At GSK, the average clinical trial involves about 400 patients at 60 sites in five to eight countries, said says Alex Lancksweert, GSK director of business performance analysis. However, some larger clinical trials can include thousands of patients and involve hundreds of clinical investigators globally. But frequently, trial sites -- which could include hospitals, clinics, and other healthcare facilities -- run into difficulties recruiting a target number of patients meeting trial requirements.
Those enrollment problems can involve lackluster patient recruitment efforts, patients dropping out of trials prematurely because of other medical issues, including pregnancies, regulatory changes unfolding in a country, and other challenges.
Through the use of DecisionView's StudyOptimizer over the last year or so, GSK has doubled its efficiency in patient recruitment for clinical studies, Lancksweert said. The Web-based software allows GSK clinical investigators see how their trial sites in various countries are tracking in terms of recruiting and screening patients based on study targets and compare their progress with other trial sites.
DecisionView CEO Jim Scullion said the power behind his company's newest release, StudyOptimizer 4, is in its ability to make "real time" forecasts about the progress of current trials based on analysis of historical data from multiple sources about a company's previous trials, including performance of specific clinical sites and countries. Predictive analysis helps clinical trial managers forecast accurate study end dates based on performance of the trials so far and historical data analysis.