Mechanisms of reduced maternal and fetal lopinavir exposure in a rat model of gestational diabetes

Abstract word count: 243 Introduction word count: 79

User considerations in assessing pharmacogenomic tests and their clinical support tools

Pharmacogenomic (PGx) testing is gaining recognition from physicians, pharmacists and patients as a tool for evidence-based medication management. However, seemingly similar PGx testing panels (and PGx-based decision support tools) can diverge in their technological specifications, as well as the genetic factors that determine test specificity and sensitivity, and hence offer different values for users. Reluctance to embrace PGx testing is often the result of unfamiliarity with PGx technology, a lack of knowledge about the availability of curated guidelines/evidence for drug dosing recommendations, and an absence of wide-spread institutional implementation efforts and educational support. Demystifying an often confusing and variable PGx marketplace can lead to greater acceptance of PGx as a standard-of-care practice that improves drug outcomes and provides a lifetime value for patients. Here, we highlight the key underlying factors of a PGx test that should be considered, and discuss the current progress of PGx implementation

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them

Expression of ABC Efflux Transporters in Placenta from Women with Insulin-Managed Diabetes

Drug efflux transporters in the placenta can significantly influence the materno-fetal transfer of a diverse array of drugs and other xenobiotics. To determine if clinically important drug efflux transporter expression is altered in pregnancies complicated by gestational diabetes mellitus (GDM-I) or type 1 diabetes mellitus (T1DM-I), we compared the expression of multidrug resistance protein 1 (MDR1), multidrug resistance-associated protein 2 (MRP2) and the breast cancer resistance protein (BCRP) via western blotting and quantitative real-time polymerase chain reaction in samples obtained from insulin-managed diabetic pregnancies to healthy term-matched controls. At the level of mRNA, we found significantly increased expression of MDR1 in the GDM-I group compared to both the T1DM-I (p<0.01) and control groups (p<0.05). Significant changes in the placental protein expression of MDR1, MRP2, and BCRP were not detected (p>0.05). Interestingly, there was a significant, positive correlation observed between plasma hemoglobin A1c levels (a retrospective marker of glycemic control) and both BCRP protein expression (r = 0.45, p<0.05) and BCRP mRNA expression (r = 0.58, p<0.01) in the insulin-managed DM groups. Collectively, the data suggest that the expression of placental efflux transporters is not altered in pregnancies complicated by diabetes when hyperglycemia is managed; however, given the relationship between BCRP expression and plasma hemoglobin A1c levels it is plausible that their expression could change in poorly managed diabetes

Inclusion/exclusion criteria.

<p>Inclusion/exclusion criteria.</p

Placental ABC efflux transporter expression in pregnancies complicated by insulin-managed diabetes.

<p><b>A</b>, MDR1 (ABCB1). <b>B</b>, MRP2 (ABCC2). <b>C</b>, BCRP (ABCG2). Boxes represent quartiles enclosing 50% of the data and the whiskers at either end extend to the 25^th and 75^th quartiles. The median is marked by a line, the mean is marked by an “+” and outliers are marked by a “•” outside the 25^th and 75^th quartiles. The “Combined” group presents data from all patients (n = 33) and was not included in statistical analyses. <b>D</b>, Spearman correlation analysis of the relationship between HbA1c levels (%) and BCRP protein expression in diabetic pregnancies (p<0.05).</p

Localization of MDR1, MRP2, and BCRP in placenta.

<p>The syncytiotrophoblast (S) layer of the placenta is comprised of multinucleated (N) cells that contain a number of apically-localized transport proteins that contribute to the function of the placental barrier, including MDR1, MRP2, and BCRP.</p

Placental ABC efflux transporter expression in pregnancies complicated by insulin-managed diabetes.

<p><b>A</b>, MDR1 (ABCB1). <b>B</b>, MRP2 (ABCC2). <b>C</b>, BCRP (ABCG2). Boxes represent quartiles enclosing 50% of the data and the whiskers at either end extend to the 25^th and 75^th quartiles. The median is marked by a line, the mean is marked by an “+” and outliers are marked by a “•” outside the 25^th and 75^th quartiles. The “Combined” group presents data from all patients (n = 33) and was not included in statistical analyses. <b>D</b>, Spearman correlation analysis of the relationship between HbA1c levels (%) and BCRP mRNA expression in diabetic pregnancies (p<0.01).</p

A Continuing Professional Development Program for Pharmacists Implementing Pharmacogenomics into Practice

A continuing professional development (CPD) program for pharmacists practicing in community and team-based primary care settings was developed and evaluated using Moore&rsquo;s framework for the assessment of continuing medical education. The program had three components: online lectures, a two-day training workshop, and patient case studies. Knowledge (pre-post multiple choice test); attitudes, readiness, and comfort with applying pharmacogenomics in their practices (pre-post surveys); and experiences of implementing pharmacogenomics in practice (semi-structured interviews) were assessed. Twenty-one of 26 enrolled pharmacists successfully completed the program, and were satisfied with their experience. Almost all achieved a score of 80% or higher on the post-training multiple choice test, with significantly improved scores compared to the pre-training test. Pre- and post-training surveys demonstrated that participants felt that their knowledge and competence increased upon completion of the training. In the follow-up, 15 pharmacists incorporated pharmacogenomics testing into care for 117 patients. Ten pharmacists participated in semi-structured interviews, reporting strong performance in the program, but some difficulty implementing new knowledge in their practices. This multi-component CPD program successfully increased pharmacists&rsquo; knowledge, readiness, and comfort in applying pharmacogenomics to patient care in the short-term, yet some pharmacists struggled to integrate this new service into their practices