Pharmaceutics SURVEYOR

Another application for Semantic Web in health care is the drug regimen selection. The US population is highly concern about drug safety. Millions of Americans visit health care websites to identify side effects of a specific drug. Americans also investigate specific drugs to determine if interactions with other drugs will cause unanticipated health concerns. Thousands of deaths occur each year due to erroneous drug selections and drug interactions. Many of these deaths could have been avoided if the existing knowledge of drug side affects and interactions stored in databases has been effectively applied.

Nowadays, the availability of a vast array of drugs makes evaluating their safety a hugely complex and time consuming task. A single criterion is not enough to make a selection. Many factors such as drug interactions, side effects, efficacy, and impacts on certain health problems must be considered. Physicians must evaluate other special factors as pill size and the patient's relative weight, just to prescribe one drug.

A survey system has been developing to help in this task. The PharmaSURVEYOR allows a map-reading of this complex task to identify the best trade-offs for each patient. Figure 1, provides a view of the proposed PharmaSURVEYOR.

Figure 1.

PharmaSURVEYOR, two possible regimens are shown considering the actual regimen [1].

In the specific case shown in Figure 1, PharmaSURVEYOR provides choices based on optimizing treatment safety while also relieving the physical condition. The physician and the patient must make trade-offs in risks and side effects when choosing from the various treatment options identified by the system.

To achieve the optimal use of Semantic language (RDF and OWL) when querying drug data, the system provides a standardized and interoperable form of medical ontologies comprised of signs and symptoms that are delivered in a user friendly language that patients can understand. This ontology supports lateral and hierarchical data relationships in the underlying databased that are queried.

This application of Semantic Web technology provides a valuable method for sharing drug side affects and interactions between patients, physicians, pharmacists, and researchers. This collaborative scenario helps improve clinical drug therapy over time.

References

Von Schweber, E. (2007). Case study: Composing safer drug regimens for the individual patient using semantic web technologies. Retrieved 5/16/2010, 2010, from http://www.w3.org/2001/sw/sweo/public/UseCases/PharmaSurveyor/