BELLEVUE, Wash.--(BUSINESS WIRE)--Translational Software®, Inc. (TSI), a leader in the intelligent use of genetic data for clinical decision support, undertook a large scale analysis to review the medication lists of 505,000 de-identified patients submitted to the company from 2013 to 2017 from its laboratory network to identify drug-gene interactions with four important pharmacogenes: CYP2C9, CYP2C19, CYP2D6 and SLCO1B1. Results of the analysis showed that 20 percent of patients had a pharmacogenetics (PGx) profile associated with a severe drug-gene interaction to drugs on their current medication list. An additional 48 percent of patients had a profile that caused a moderate drug-gene interaction.
According to the Centers for Disease Control and Prevention, adverse drug events cause more than one million emergency department visits and 280,000 hospitalizations each year. The CDC estimates that $3.5 billion is spent annually on excess medical costs to treat ADEs.
A drug-gene interaction was defined as severe when there was a high risk of an adverse drug reaction or therapeutic failure which might require an alternative therapy or a significant alteration in dosing. A drug-gene interaction was regarded as moderate when there was sufficient risk of an adverse drug reaction which might require therapy adjustment or close monitoring of the patient.
- PGx tests used in the analysis were requested by over 20,000 physicians representing more than 100 different laboratories. Organizations located in the US, Africa and Asia submitted the genotyping data.
- Over half a million patient samples were reviewed and the analysis revealed that approximately 375,000 patients (75 percent) were taking at least one medication for which PGx guidance was available.
- The medication lists of the 375,000 patients were further analyzed for the potential for drug-gene interactions with four important genes: CYP2C9, CYP2C19, CYP2D6 and SLCO1B1. The most commonly-prescribed drugs in the patient population that interacted with these four genes include atorvastatin, clopidogrel, hydrocodone, metoprolol, oxycodone, omeprazole, simvastatin and tramadol.
“These results underscore the fact that patients with specific genetic variations are at increased risk from taking many widely prescribed drugs, such as common pain medications and cardiovascular agents,” stated Don Rule, CEO, TSI. “There is no question that evidence-based genomic decision support and PGx practice guidelines are central to advancing precision medicine initiatives to improve patient outcomes.”
Use of PGx testing is valuable to help reduce the risk of harmful drug-gene interactions and adverse drug events. Yet the growing volume and complexity of available genetic diagnostic tests make it challenging for physicians to keep current or manually assess all the co-determinants for an appropriate course of treatment. Providers, laboratories, pharmacies and leading health information system vendors are increasingly implementing tools like TSI’s proprietary knowledge platform and Application Programming Interface to integrate genotyping prompts, genomic decision support and critical alerts regarding drug efficacy, toxicity and known interactions to guide clinical decision making, minimize adverse reactions and enable physicians to prescribe the most appropriate medications.
The results of this analysis were presented at the 2017 University of Florida Precision Medicine Conference which was held in Orlando, Florida on March 8-10. For additional information about the analysis and TSI’s solutions, please visit www.TranslationalSoftware.com.
About Translational Software, Inc.
Translational Software enables healthcare providers to realize the promise of precision medicine. We simplify complex genetic data into evidence-based actionable recommendations to deliver platform agnostic genomic decision support. Our PGx knowledge base and Fast Healthcare Interoperability Resource (FHIR)-based API has been used to provide over one million PGx recommendations. To learn more visit us at www.TranslationalSoftware.com.