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Aim: The aim was to determine if the University of Minnesota (MN, USA) healthcare students' perceived value of pharmacogenomics matches their self-observed comfort and education in pharmacogenomics., Materials & Methods: A 24-question, anonymous, online survey was distributed to all pharmacy, nursing and medical students enrolled at the University of Minnesota., Results: Among healthcare students, 70.6% agreed or strongly agreed that pharmacogenomics should be an important part of their curriculum; however, only 11.1% agreed or strongly agreed that it actually is. Only 29.7% of students reported taking a genetics course that specifically addressed the applications of genetics in pharmacy, and those students were more likely to feel comfortable interpreting information from a pharmacogenetics test, answering questions on pharmacogenomics, educating patients on risks and benefits of testing, and were comfortable that they knew which medications required pharmacogenomics testing., Conclusion: Healthcare students consider pharmacogenomics to be an important area of clinical practice; yet generally express it has not been an important part of their curriculum. Education emphasizing medical applications of pharmacogenomics can increase student comfort level in pharmacogenomics practice.

The main objective of this study was to investigate the feasibility of using PharmGKB, a pharmacogenomic database, as a source of training data in combination with text of MEDLINE abstracts for a text mining approach to identification of potential gene targets for pathway-driven pharmacogenomics research. We used the manually curated relations between drugs and genes in PharmGKB database to train a support vector machine predictive model and applied this model prospectively to MEDLINE abstracts. The gene targets suggested by this approach were subsequently manually reviewed. Our quantitative analysis showed that a support vector machine classifiers trained on MEDLINE abstracts with single words (unigrams) used as features and PharmGKB relations used for supervision, achieve an overall sensitivity of 85% and specificity of 69%. The subsequent qualitative analysis showed that gene targets "suggested" by the automatic classifier were not anticipated by expert reviewers but were subsequently found to be relevant to the three drugs that were investigated: carbamazepine, lamivudine and zidovudine. Our results show that this approach is not only feasible but may also find new gene targets not identifiable by other methods thus making it a valuable tool for pathway-driven pharmacogenomics research., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Health-care information technology and genotyping technology are both advancing rapidly, creating new opportunities for medical and scientific discovery. The convergence of these two technologies is now facilitating genetic association studies of unprecedented size within the context of routine clinical care. As a result, the medical community will soon be presented with a number of novel opportunities to bring functional genomics to the bedside in the area of pharmacotherapy. By linking biological material to comprehensive medical records, large multi-institutional biobanks are now poised to advance the field of pharmacogenomics through three distinct mechanisms: (i) retrospective assessment of previously known findings in a clinical practice-based setting, (ii) discovery of new associations in huge observational cohorts, and (iii) prospective application in a setting capable of providing real-time decision support. This review explores each of these translational mechanisms within a historical framework.

Objective: The aim of the study was to investigate relationships among indinavir, lamivudine-triphosphate, and zidovudine-triphosphate pharmacokinetics and pharmacodynamics with polymorphisms in CYP3A5, MDR1, MRP2, MRP4, BCRP, and UGT1A1 genes., Study Design: Retrospective pilot investigation among 33 subjects who participated in a randomized pharmacological study of indinavir, lamivudine, and zidovudine. Subjects were defined as genetic variant carriers or not. Relationships were investigated with multivariable regression. Indinavir clearance was adjusted for African American race; triphosphates for sex; and HIV-response for study arm, drug exposure, and baseline HIV-RNA., Results: Genetically determined CYP3A5 expressors had 44% faster indinavir oral clearance versus nonexpressors (P = 0.002). MRP2-24C/T variant carriers had 24% faster indinavir oral clearance (P = 0.05). Lamivudine-triphosphate concentrations were elevated 20% in MRP4 T4131G variant carriers (P = 0.004). A trend for elevated zidovudine-triphosphates was observed in MRP4 G3724A variant carriers (P = 0.06). The log10 changes in HIV-RNA from baseline to week 52 were -3.7 for MDR1 2677 TT, -3.2 for GT, and -2.2 for GG (P < 0.05). Bilirubin increases were 2-fold higher in UGT1A1 [TA]7/[TA]7 genotypes. No relationships were identified with BCRP., Discussion: Novel relationships were identified among genetic variants in drug transporters and indinavir, lamivudine-triphosphate, and zidovudine-triphosphate concentrations. CYP3A5 expression was associated with faster indinavir oral clearance. These pilot data provide a scientific basis for more rational utilization of antiretroviral drugs.

The defense mechanisms responsible for protecting the body from endogenous toxins are also involved in the metabolism of drugs and are composed of phase I and phase II drug metabolizing enzymes, as well as drug transporters. Numerous drugs and chemicals have been shown to modulate the expression of the genes involved in these three drug-detoxifying processes. Induction of these genes contributes to both auto-induction of drug clearance and to drug-drug interactions in combination therapies. The orphan nuclear receptors PXR (pregnane X receptor) and CAR (Constitutive androstane receptor) are xenosensors that mediate drug-induced changes by increasing transcription of genes that are involved in drug clearance and disposition. Co-administration of drugs, one of which is a nuclear receptor agonist or antagonist, can either lead to altered clearance of the second drug and severe toxicity, or a loss of therapeutic efficacy or an imbalance in physiological substrate concentrations, providing a novel molecular mechanism for drug-drug interactions. Thus, genetic variability in these nuclear receptors will contribute to human variation in the magnitude of clinically significant drug-drug interactions. This review describes common PXR and CAR genetic variants that have been identified to date in the human population and the functional consequence of these variant alleles. In addition, alternatively spliced variants of PXR and CAR that may also contribute to individual variability as well as tissue specific expression of these receptors are also described. Identification of PXR and CAR genetic variants and alternatively spliced mRNAs may ultimately allow predictions of interindividual differences in target gene induction and drug-drug interactions.

Many pharmacogenomic predictors of drug response are now available, and include both drug metabolism-disposition factors and drug targets. Information on statistical approaches to analyzing large clinical data sets in relation to genetic polymorphisms is limited. The objective of this study was to evaluate whether logistic regression could identify pharmacogenomic predictors of outcome in a large data set in a complex transplant patient population. Seventy pediatric heart transplant patients were studied. Patients were followed for at least 1 yr post-transplantation as outpatients, and weaned from corticosteroids if clinically appropriate. Logistic regression analysis was used to identify the predictors of steroid dependency. The dependent variable was the presence or absence of steroid therapy at 1 yr post-transplantation. The independent variables were the patients' transplant age, gender, MDR1 C3435T and G2677T, CYP3A53B and cytokine polymorphisms. By chi-square test for the MDR1 C3435T polymorphism, 12 of 18 (67%) patients in the CC group were still on prednisone, whereas only 18 of 47 (38%) of the CT/TT group were still receiving prednisone (p = 0.04). For the IL-10 groups, two of 15 patients with the high producer genotype (13.3%) remained on prednisone, in comparison with 16 of 28 patients with the intermediate producer genotype (57.1%) and 15 of 26 patients with the low producer genotype (57.7%, p = 0.01). Logistic regression analysis confirmed MDR1 C3435T (p = 0.021), and IL-10 polymorphisms (intermediate producer genotype p = 0.015; low producer genotype p = 0.013) as independent risk factors for steroid dependency at 1 yr after transplantation. This approach identifies pharmacogenomic factors, which can be studied more extensively in larger data sets, and used in prospective studies to individualize immunosuppressive therapy following solid organ transplantation.