September 2017

CYP2D6 and CYP3A4 in opioid metabolism: Time to develop guidance for PGX biomarkers?

24. september 2017 at 13:32 | Veronika Valdova, ARETE-ZOE |  Medicine & Pharmacy
Clinically relevant insight into genetic makeup and phenotypic biomarkers, such as ADMET and treatment outcomes, would significantly improve predictability of individual response to medications. The combination of metabolomic and pharmacogenomic data from individual patients would offer better insight compared to genotyping alone, especially in patients who take multiple interacting drugs at a time.

Opioid overdose
Adverse drug events (ADEs) account for an estimated one-third of hospital adverse events and approximately 280,000 hospital admissions annually. Three types of ADEs were selected as high-priority targets as common, clinically significant, preventable, and measurable: Anticoagulants (primary concern: bleeding), diabetes agents(hypoglycemia) and opioids (accidental overdoses/oversedation /respiratory depression) (National Action Plan for ADE prevention, 2014)

Anticoagulants, antidiabetic agents, and opioid analgesics are responsible for ~60% of ED visits for adverse drug events among older adults (ADE Change Package, 2017)

The long way to clinically actionable pharmacogenomic biomarkers

24. september 2017 at 13:31 | Veronika Valdova, ARETE-ZOE |  Medicine & Pharmacy
The impact of cytochromes P450 (CYP450) variability on drug metabolism and drug interactions is well known and long recognized in the community of medical and pharmaceutical professionals as a major contributor to avoidable patient casualty (1). Many active pharmaceutical ingredients are known substrates, inducers and inhibitors of CYP450 enzymes. Some CYP450s are highly polymorphic, namely CYP2C9, CYP2C19 and CYP2D6 (1). Anticoagulants, opioid analgesics, and antidiabetics are among drug classes that cause the highest number of adverse events (2, 3).

Well-documented concern, limited clinical use

Information about pharmacogenomic biomarkers listed in U.S. drug labels includes drug interactions with germline or somatic gene variants (polymorphisms, mutations), functional deficiencies with a genetic etiology, gene expression differences, chromosomal abnormalities and selected proteins used for treatment selection (4). Some healthcare facilities already offer PGX testing to their patients, e.g. CYP2C9 and VKORC1 to better predict response to warfarin and adjust dosing (5).