The retinoid, N-(4-hydroxyphenyl)retinamide (4-HPR), mediates p53-independent cytotoxicity and can increase reactive oxygen species and ceramide in solid tumor cell lines. We determined changes in ceramide and cytotoxicity upon treatment

Changes in behavior are necessary to apply genomic discoveries to practice. We prospectively studied medication changes made by providers representing eight different medicine specialty clinics whose patients had submitted to preemptive pharmacogenomic genotyping. An institutional clinical decision support (CDS) system provided pharmacogenomic results using traffic light alerts: green/genomically favorable, yellow/genomic caution, red/high risk. The influence of pharmacogenomic alerts on prescribing behaviors was the primary endpoint. 2279 outpatient encounters were analyzed. Independent of other potential prescribing mediators, medications with high pharmacogenomic risk were changed significantly more often than prescription drugs lacking pharmacogenomic information (odds ratio [OR]=26.2 [9.0–75.3], p<0.0001). Medications with cautionary pharmacogenomic information were also changed more frequently (OR=2.4 [1.7–3.5], p<0.0001). No pharmacogenomically high-risk medications were prescribed during the entire study when physicians consulted the CDS tool. Pharmacogenomic information improved prescribing in patterns aimed at reducing patient risk, demonstrating that enhanced prescription decision-making is achievable through clinical integration of genomic medicine.

Despite growing clinical use of genomic information, patient perceptions of genomic-based care are poorly understood. We prospectively studied patient-physician pairs who participated in an institutional pharmacogenomic implementation program. Trust/Privacy/Empathy/Medical Decision-Making (MDM)/Personalized Care (PC) dimensions were assessed through patient surveys after clinic visits at which physicians had access to preemptive pharmacogenomic results (Likert scale, 1-minimum/5-maximum; mean [SD]). From 2012–2015, 1,261 surveys were issued to 507 patients, with 792 (62.8%) returned. Privacy, Empathy, MDM and PC scores were significantly higher following visits when physicians considered pharmacogenomic results. Importantly, PC scores were significantly higher after physicians used pharmacogenomic information to guide medication changes (4.0[1.4] vs. 3.0[1.6], P<0.001) compared to prescribing visits without genomic guidance. Multivariable modeling controlling for clinical factors confirmed PC scores were more favorable following visits with genomic-influenced prescribing (OR=3.26 [1.31–8.14], P<0.05). Physicians appear to individualize care when utilizing pharmacogenomic results and this decision-making augmentation is perceived positively by patients.

Providers have expressed a strong desire to have additional clinical decision-support tools to help with interpretation of pharmacogenomic results. We developed and tested a novel disease–drug association tool that enables pharmacogenomic-based prescribing to treat common diseases. First, 324 drugs were mapped to 484 distinct diseases (mean number of drugs treating each disease was 4.9; range 1–37).Then the disease–drug association tool was pharmacogenomically annotated, with an average of 1.8 pharmacogenomically annotated drugs associated/disease. Applying this tool to a prospectively enrolled >1,000 patient cohort from a tertiary medical center showed that 90% of the top ∼20 diseases in this population and ≥93% of patients could appropriately be treated with ≥1 medication with actionable pharmacogenomic information. When combined with clinical patient genotypes, this tool permits delivery of patient-specific pharmacogenomically informed disease treatment recommendations to inform the treatment of many medical conditions of the US population, a key initial step towards implementation of precision medicine.