Faster, better, cheaper... how often have we heard these words, in the context of any process along the long path of drug development? There are a myriad of solutions that can help at different stages, enabling more comprehensive target assessment, more rapid lead optimization, and so on. One of the most expensive parts of the drug development process is clinical trials, with bottlenecks including access to knowledge for site selection, patient populations, principal investigators and key opinion leaders.
Researchers naturally look to utilize information from current and past trials but manually extracting the relevant information can be resource-intensive, repetitive and, therefore, prone to errors. Time is money, so reducing costs and errors is critical.
One of our customers, Merck, use Linguamatics I2E for text analytics over public domain clinical trial data, to improve clinical trial site selection.
One example of the benefits of text analytics is a site selection project for Merck Experimental Medicine division (EMS). They needed to locate a clinical trial site that would be able to conduct gastric bypass trials with the ability to measure gut peptides before and after surgery. The ideal trial site needed to fit many different characteristics - over a dozen - which would be hugely time-consuming to find using the public domain search interface to ClinicalTrials.gov.