4 Clinical Trials for Various Conditions
The purpose of this study is to determine whether the implementation of pre-emptive pharmacogenomic (PGx) testing of a panel of clinically relevant PGx markers, to guide the dose and drug selection for 39 commonly prescribed drugs, will result in an overall reduction in the number of clinically relevant drug-genotype associated ADRs which are causally related to the initial drug of inclusion (referred to as 'index drug').
This randomized controlled trial will evaluate whether the use of pharmacogenetic testing through a Medication Therapy Management (MTM) program has a beneficial impact on drug therapy problems. More specifically, cytochrome DNA testing, which provides information with regards to participant specific metabolism of medications, will be used in the evaluation of participant medication regimens. The overall aim of the project is to evaluate if the addition of genetic CYP testing to a standardized MTM Program provides increased clinical value. To answer this question, the investigators will look at the drug therapy problems (DTPs) identified by the genetic test compared to those DTPs discovered without the test.
Patients meeting eligibility criteria will be randomized into two groups, one receiving pharmacogenetic testing and the other not receiving pharmacogenetic testing. In this open-label trial, a pharmacist will make medication therapy recommendations using YouScript® Personalized Prescribing System for patients who receive genetic testing and standard drug information resources per usual for patients who do not undergo pharmacogenetic testing.
This multicenter observational study aims to investigate the benefits of providing pharmacogenetic testing with the YouScript Personalized Prescribing System which includes a clinical decision support tool and individualized pharmacist recommendations to elderly polypharmacy patients who are most at risk of adverse drug events. The YouScript system is unique in identifying drug-gene, and drug-drug-gene interactions that are missed by existing systems, and represent over 35% of significant interaction warnings. Data analysis will assess the impact of recommendations for medication changes on clinical decision making, patient outcomes, and healthcare resource utilization to determine which medications, specialties, or patient segments derive the greatest benefit from this intervention. Data gathered from patients enrolled in this study will be compared to patients matched on key characteristics from Inovalon's MORE2 healthcare database.