Search

The fields of genetics and genomics have greatly expanded across medicine through the development of new technologies that have revealed genetic contributions to a wide array of traits and diseases. Thus, the development of widely available educational resources for all healthcare providers is essential to ensure the timely and appropriate utilization of genetics and genomics patient care. In 2020, the National Human Genome Research Institute released a call for new proposals to develop accessible, sustainable online education for health providers. This paper describes the efforts of the six teams awarded to reach the goal of providing genetic and genomic training modules that are broadly available for busy clinicians.

AIMS: High-dose methotrexate (HDMTX) is an essential part of the treatment of several adult and paediatric malignancies. Despite meticulous supportive care during HDMTX administration, severe toxicities, including acute kidney injury (AKI), may occur contributing to patient morbidity. Population pharmacokinetics provide a powerful tool to predict time to clear HDMTX and adjust subsequent doses. We sought to develop and validate pharmacokinetic models for HDMTX in adults with diverse malignancies and to relate systemic exposure with the occurrence of severe toxicity.METHODS: Anonymized, de-identified data were provided from 101 US oncology practices that participate in the Guardian Research Network, a non-profit clinical research consortium. Modelled variables included clinical, laboratory, demographic and pharmacological data. Population pharmacokinetic analysis was performed by means of nonlinear mixed effects modelling using MonolixSuite.RESULTS: A total of 693 HDMTX courses from 243 adults were analysed, of which 62 courses (8.8%) were associated with stage 2/3 acute kidney injury (43 stage 2, 19 stage 3). A three-compartment model adequately fitted the data. Time-dependent serum creatinine, baseline serum albumin and allometrically scaled bodyweight were clinically significant covariates related to methotrexate clearance. External evaluation confirmed a satisfactory predictive performance of the model in adults receiving HDMTX. Dose-normalized methotrexate concentration at 24 and 48 hours correlated with AKI incidence.CONCLUSION: We developed a population pharmacometric model that considers weight, albumin and time-dependent creatinine that can be used to guide supportive care in adult patients with delayed HDMTX elimination.

Adjunctive l-methylfolate is commonly prescribed for children and adolescents with treatment-resistant mood disorders; however, the relationship between l-methylfolate augmentation across methylenetetrahydrofolate reductase (MTHFR) genotypes in youths with depressive symptoms is unclear.We retrospectively examined the electronic health records of patients (N = 412) with depressive symptoms associated with unipolar depressive disorders and their MTHFR C677T genotypes from 2013 to 2019. Patients were ≤18 years of age at the time of MTHFR pharmacogenetic testing. Treatment response was assessed with Clinical Global Impression-Improvement (CGI-I) score reported in the medical record.Patients with an MTHFR C677T C/T or T/T genotype were more likely to be prescribed l-methylfolate when the clinician knew their MTHFR genotype (p 0.0001, OR: 15.1, 95 % CI: [5.1, 44.2]), but not when the clinician did not know their genotype (p = 0.4, OR: 2.1, 95 % CI: [0.4, 11.4]). Change in baseline and endpoint CGI-I scores between patients with an MTHFR C677T variant who were prescribed and not prescribed l-methylfolate did not significantly differ (p = 0.39). Response rate was not associated with l-methylfolate prescription (p = 0.17) or l-methylfolate dose (p = 0.69).This was a retrospective study, which yielded a heterogeneous patient population and limited data availability (e.g., adherence). Patients are severely ill and may have a refractory illness that limits response to adjunctive l-methylfolate.Clinicians prescribe l-methylfolate to children and adolescents with depressive symptoms associated with unipolar depressive disorders who have an MTHFR C677T variant, although augmentation may not be associated with treatment response, regardless of MTHFR genotype or dose.

Follicular lymphoma and diffuse large B-cell lymphoma (DLBCL) are the most common non-Hodgkin lymphomas distinguishable by unique mutations, chromosomal rearrangements, and gene expression patterns. Here, it is demonstrated that early B-cell progenitors express 2′,3′-cyclic-nucleotide 3′ phosphodiesterase (CNP) and that when targeted with Sleeping Beauty (SB) mutagenesis, Trp53R270H mutation or Pten loss gave rise to highly penetrant lymphoid diseases, predominantly follicular lymphoma and DLBCL. In efforts to identify the genetic drivers and signaling pathways that are functionally important in lymphomagenesis, SB transposon insertions were analyzed from splenomegaly specimens of SB-mutagenized mice (n = 23) and SB-mutagenized mice on a Trp53R270H background (n = 7) and identified 48 and 12 sites with statistically recurrent transposon insertion events, respectively. Comparison with human data sets revealed novel and known driver genes for B-cell development, disease, and signaling pathways: PI3K–AKT–mTOR, MAPK, NFκB, and B-cell receptor (BCR). Finally, functional data indicate that modulating Ras-responsive element-binding protein 1 (RREB1) expression in human DLBCL cell lines in vitro alters KRAS expression, signaling, and proliferation; thus, suggesting that this proto-oncogene is a common mechanism of RAS/MAPK hyperactivation in human DLBCL.Implications:A forward genetic screen identified new genetic drivers of human B-cell lymphoma and uncovered a RAS/MAPK–activating mechanism not previously appreciated in human lymphoid disease. Overall, these data support targeting the RAS/MAPK pathway as a viable therapeutic target in a subset of human patients with DLBCL.

PDF with supplemental figures 1-10 with each containing a figure legend at the bottom fo the figure.

Statins reduce cholesterol, prevent cardiovascular disease, and are among the most commonly prescribed medications in the world. Statin-associated musculoskeletal symptoms (SAMS) impact statin adherence and ultimately can impede the long-term effectiveness of statin therapy. There are several identified pharmacogenetic variants that impact statin disposition and adverse events during statin therapy. SLCO1B1 encodes a transporter (SLCO1B1; alternative names include OATP1B1 or OATP-C) that facilitates the hepatic uptake of all statins. ABCG2 encodes an efflux transporter (BCRP) that modulates the absorption and disposition of rosuvastatin. CYP2C9 encodes a phase I drug metabolizing enzyme responsible for the oxidation of some statins. Genetic variation in each of these genes alters systemic exposure to statins (i.e., simvastatin, rosuvastatin, pravastatin, pitavastatin, atorvastatin, fluvastatin, lovastatin), which can increase the risk for SAMS. We summarize the literature supporting these associations and provide therapeutic recommendations for statins based on SLCO1B1, ABCG2, and CYP2C9 genotype with the goal of improving the overall safety, adherence, and effectiveness of statin therapy. This document replaces the 2012 and 2014 Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for SLCO1B1 and simvastatin-induced myopathy.

Low‐dose methotrexate (MTX) is a first‐line therapy for the treatment of arthritis. However, there is considerable interindividual variability in MTX exposure following standard dosing. Polymorphisms in SLCO1B1 significantly effect MTX clearance, altering therapeutic response. One decreased function variant, rs4149056 (c.521T>C, Val174Ala), slows MTX clearance and in vitro uptake of MTX. This phenotype was recapitulated in a mouse model using a knockout (KO) of the murine orthologue, Slco1b2. Our objective was to investigate the impact of this phenotype on the pharmacokinetics and therapeutic outcomes of low‐dose MTX in a murine model of collagen‐induced arthritis (CIA). We evaluated response to MTX in mice with CIA using wildtype (WT), heterozygous, and KO Slco1b2 mice on a DBA1/J background. Arthritis was macroscopically evaluated daily to quantify disease progression. Mice received 2 mg/kg or a pharmacogenetically guided MTX dose subcutaneously 3 times a week for 2 weeks. MTX concentrations were collected at the end of the study and exposure (day*µM) was estimated using a two‐compartment model. Mice displayed a seven‐fold range in MTX exposure and revealed a significant exposure‐response relationship (p = 0.0027). KO mice receiving the 2 mg/kg dosing regimen had 2.3‐fold greater exposure to MTX (p < 0.0001) and a 66% reduction in overall disease progression (p = 0.011) compared to WT mice. However, exposure and response were equivalent when pharmacogenetically guided dosing was used. These studies demonstrate that an exposure‐response relationship exists for MTX and that Slco1b2 genotype affects MTX exposure and therapeutic response. Such evidence supports the use of SLCO1B1‐pharmacogenetic dosing of low‐dose MTX for patients with arthritis.

Amygdala-ventrolateral prefrontal cortex (VLPFC) circuitry is disrupted in pediatric anxiety disorders, yet how selective serotonin reuptake inhibitors (SSRIs) affect this circuitry is unknown. We examined the impact of the SSRI escitalopram on functional connectivity (FC) within this circuit, and whether early FC changes predicted treatment response in adolescents with generalized anxiety disorder (GAD).Resting-state functional magnetic resonance (MR) images were acquired before and after 2 weeks of treatment in 41 adolescents with GAD (12-17 years of age) who received double-blind escitalopram or placebo for 8 weeks. Change in amygdala-based whole-brain FC and anxiety severity were analyzed.Controlling for age, sex, and pretreatment anxiety, escitalopram increased amygdala-VLPFC connectivity compared to placebo (F = 17.79, p = .002 FWE-corrected). This early FC change predicted 76.7% of the variability in improvement trajectory in patients who received escitalopram (p .001) but not placebo (p = .169); the predictive power of early amygdala-VLPFC FC change significantly differed between placebo and escitalopram (p = .013). Furthermore, this FC change predicted improvement better than baseline FC or clinical/demographic characteristics. Exploratory analyses of amygdala subfields' FC revealed connectivity of left basolateral amygdala (BLA) -VLPFC (F = 19.64, p .001 FWE-corrected) and superficial amygdala-posterior cingulate cortex (F = 22.92, p = .001 FWE-corrected) were also increased by escitalopram, but only BLA-VLPFC FC predicted improvement in anxiety over 8 weeks of treatment.In adolescents with GAD, escitalopram increased amygdala-prefrontal connectivity within the first 2 weeks of treatment, and the magnitude of this change predicted subsequent clinical improvement. Early normalization of amygdala-VLPFC circuitry might represent a useful tool for identifying future treatment responders as well as a promising biomarker for drug development.Neurofunctional Predictors of Escitalopram Treatment Response in Adolescents With Anxiety; https://www.clinicaltrials.gov/; NCT02818751.

Low‐dose methotrexate (MTX) is an immunosuppressant used to treat inflammatory bowel disease (IBD). SLCO1B1 genetic variation has been associated with delayed MTX clearance and increased toxicity. The purpose of this study was to evaluate the association between SLCO1B1 genetic variation and MTX‐induced nausea in children with IBD. We performed a single center retrospective chart analysis of 278 patients who were prescribed MTX for IBD. Two hundred two patients had banked DNA and were genotyped for three SLCO1B1 single nucleotide polymorphisms (SNPs; rs4149056, rs2306283, and rs11045819). Diplotypes were determined by combining the SNPs into *1, *4, *5, *14, *15, and *37 alleles. Incidence of nausea was abstracted from clinician notes. Prescriptions and demographics were extracted from the medical record. The cohort was 69.8% boys, 89.1% White, and 87.6% had a diagnosis of Crohn’s disease with a mean age of 16.0 (± 3.8) years. MTX‐induced nausea was noted in 34% of the cohort. MTX‐induced nausea was associated with the number of reduced‐function *15 alleles (p = 0.034) and occurred 2.26 times more often in patients with at least one *15 allele who did not initiate MTX treatment with concomitant ondansetron (p = 0.034). MTX‐induced nausea was significantly independently associated with SLCO1B1 diplotype (p = 0.006) after controlling for MTX dose group and concomitant ondansetron. Our data demonstrate that the SLCO1B1 *15 allele is associated with MTX‐induced nausea in pediatric patients with IBD. Additionally, *15 allele carriers could benefit from a dose reduction of MTX to reduce exposure and treatment initiation with concomitant ondansetron to reduce nausea.

The new Pharmacogenomics Global Research Network (PGRN) is an independent society that builds on the National Institutes of Health (NIH)–funded Pharmacogenomics Research Network that was established in 2000. Leveraging the original PGRN’s previous success, the new network continues to be a leader in the field of personalized medicine focusing on research, discovery, and translation of genomic variation influencing drug efficacy and adverse events, while simultaneously increasing inclusion in the field and expanding globally.

Pharmacogenetics (PGx) seeks to enable selection of the right dose of the right drug for each patient to optimize therapeutic outcomes. Most PGx focuses on pharmacokinetics (PKs), due to our relatively advanced understanding of the genes involved in PKs and the causative effects of variants in those genes. Genetic variants can also affect pharmacodynamics (PDs), but relatively few PGx-PD associations have been identified. This is partially due to a more limited understanding of the relevant genes and the consequences of genetic variation, but is also due in part to the potential confounding of PK variability in assessments of clinical outcomes that have a contribution from both PKs and PDs. For example, it is challenging to confirm the effect of mu opioid receptor (OPRM1) genetic variation on opioid response due to the contribution of CYP2D6 genotype to bioactivation of some opioid drugs (i.e., codeine and tramadol). The objectives of this mini-review are to describe several recent efforts to discover and validate PGx-PD that disentangle the influence of PK variability and propose potential approaches that could be used in future PGx-PD analyses. We use the effect of OPRM1 genetics on opioid response to illustrate how these analyses could be conducted and conclude by discussing how PGx-PD could be translated into clinical practice to improve therapeutic outcomes.

Pharmacogenetics (PGx) association studies are used to discover, replicate, and validate the association between an inherited genotype and a treatment outcome. The objective of this tutorial is to provide trainees and novice PGx researchers with an overview of the major decisions that need to be made when designing and conducting a PGx association study. The first critical decision is to determine whether the objective of the study is discovery, replication, or validation. Next, the researcher must identify a patient cohort that has all of the data necessary to conduct the intended analysis. Then, the investigator must select and define the treatment outcome, or phenotype, that will be analyzed. Next, the investigator must determine what genotyping approach and genetic data will be included in the analysis. Finally, the association between the genotype and phenotype is tested using some statistical analysis methodology. This tutorial is divided into five sections; each section describes commonly used approaches and provides suggestions and resources for designing and conducting a PGx association study. Successful PGx association studies are necessary to discover and validate associations between inherited genetic variation and treatment outcomes, which enable clinical translation to improve efficacy and reduce toxicity of treatment.

AACAP's recent policy statement on Clinical Use of Pharmacogenetic Tests in Prescribing Psychotropic Medications for Children and Adolescents1 recommends that "clinicians avoid using pharmacogenetic testing to select psychotropic medications in children and adolescents." We agree that there are limitations to the nascent evidence base for using pharmacogenetics, especially in combinatorial form (eg, test results that bin medications based on multiple genes). However, all-or-nothing recommendations fail to recognize the nuance and context of this testing and contrast with the AACAP Facts for Families on pharmacogenetic testing. Moreover, pharmacogenetic testing may inform dosing for antidepressants that are commonly used in child and adolescent psychiatry (eg, sertraline, escitalopram, citalopram, fluvoxamine) as well as the tolerability of some psychotropic medications. With this in mind, we wish to remind the AACAP community of the accumulating evidence and to highlight important principles of pharmacogenetic testing in youths. Specifically: 1) pharmacogenetic testing is not always performed by commercial companies and is not always combinatorial; 2) dosing recommendations or assessment of risk for severe hypersensitivity reactions are based on pharmacogenetics in the Food and Drug Administration (FDA)-approved product inserts for several medications commonly prescribed to children (eg, citalopram, aripiprazole, atomoxetine, carbamazepine, oxcarbazepine at www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomarkers-drug-labeling); 3) expert consensus guidelines for dosing or identifying hypersensitivity risk for these drugs are available from the National Institutes of Health (NIH)-supported Clinical Pharmacogenetics Implementation Consortium (CPIC, www.cpicpgx.org/), which provides transparent, regularly updated, and evidence-based evaluations of pharmacogenetic data;2 and 4) randomized trials are not required for clinical dose adjustments; for example, dose adjustments because of decreased hepatic function or concomitant interacting medications are based on pharmacokinetic data, similar to many pharmacokinetic gene-based recommendations from CPIC.

This review evaluates the pediatric evidence for pharmacogenetic associations for drugs that are commonly prescribed by or encountered by pediatric clinicians across multiple subspecialties, organized from most to least pediatric evidence. We begin with the pharmacogenetic research that led to the warning of increased risk of death in certain pediatric populations ("ultrarapid metabolizers") who are prescribed codeine after tonsillectomy or adenoidectomy. We review the evidence for genetic testing for thiopurine metabolism, which has become routine in multiple pediatric subspecialties. We discuss the pharmacogenetic research in proton pump inhibitors, for which clinical guidelines have recently been made available. With an increase in the prevalence of behavioral health disorders including attention deficit hyperactivity disorder (ADHD), we review the pharmacogenetic literature on selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and ADHD medications. We will conclude this section on the current pharmacogenetic data on ondansetron. We also provide our perspective on how to integrate the current research on pharmacogenetics into clinical care and what further research is needed. We discuss how institutions are managing pharmacogenetic test results and implementing them clinically, and how the electronic health record can be leveraged to ensure testing results are available and taken into consideration when prescribing medications. IMPACT: While many reviews of pharmacogenetics literature are available, there are few focused on pediatrics. Pediatricians across subspecialties will become more comfortable with pharmacogenetics terminology, know resources they can use to help inform their prescribing habits for drugs with known pharmacogenetic associations, and understand the limitations of testing and where further research is needed.

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.

Antidepressants are standardly used to treat moderate to severe symptoms of depression and/or anxiety in youth but may also be associated with rare but serious psychiatric adverse events such as irritability, agitation, aggression, or suicidal ideation. Adverse events are especially common in youth with a family history of bipolar disorder (BD) who are at heightened risk for dysfunction in neurobiological systems that regulate emotion and arousal. To further understand this phenomenon, this study will examine (a) baseline risk factors associated with dysfunctional arousal in a sample of youth at high-risk for BD treated with or without an antidepressant, (b) whether antidepressant-related changes in arousal are mediated by changes in prefrontal-limbic circuitry, and (c) whether pharmacogenetic factors influence antidepressant-related changes in arousal. High-risk youth (aged 12–17 years with moderate to severe depressive and/or anxiety symptoms and at least one first-degree relative with bipolar I disorder) will be randomized to receive psychotherapy plus escitalopram or psychotherapy plus placebo. Neuroimaging and behavioral measures of arousal will be collected prior to randomization and at 4 weeks. Samples for pharmacogenetic analysis (serum escitalopram concentration, CYP2C19 metabolizer phenotype, and HTR2A and SLC6A4 genotypes) will be collected at 8 weeks. Youth will be followed for up to 16 weeks to assess change in arousal measures.

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms.

Anxiety and depressive disorders are the most common psychiatric illnesses among children and adolescents. These disorders are associated with impairments in social, family, and educational functioning. This article summarizes the evidence base for psychopharmacologic interventions; the developmental pharmacology of selective serotonin reuptake inhibitors (SSRIs) and serotonin norepinephrine reuptake inhibitors (SNRIs); and pharmacokinetic and pharmacodynamic differences between youths and adults that call for differences in dosage and affect response and tolerability. The authors also review the efficacy and tolerability of SSRIs and SNRIs in children and adolescents with depressive and anxiety disorder diagnoses, as well as data related to duration of therapy and SSRI/SNRI discontinuation in this population. Taken together, the current evidence suggests that SSRIs are the first-line psychopharmacologic intervention for youths with depressive and anxiety disorders, with SNRIs having a more limited role. These medications are safe and well tolerated, although emerging data and developmental pharmacologic concepts may help clinicians to choose from available SSRIs and to improve the efficacy and tolerability of these medications in children and adolescents.

Providing maximal therapeutic efficacy without toxicity is a universal goal of rational drug therapy. However, substantial between-patient variability in drug response often impedes such successful treatments and brings the necessity of tailoring drug dose to individual needs for more precise therapy. In many cases plenty of patient characteristics, such as body size, genetic makeup and environmental factors, need to be taken into consideration to find the optimal dose in clinical practice. A pharmacokinetics and pharmacodynamics (PK/PD) model-informed approach offers integration of various patient information to provide an expectation of drug response and derive practical dose estimates to support clinicians' dosing decisions. Such an approach was pioneered in the late 1970s, but its broad clinical acceptance and implementation have been hampered by the lack of widespread computer technology, including user-friendly software tools. This has significantly changed in recent years. With the advent of electronic health records (EHRs) and the ubiquity of user-friendly software tools, we now experience a convergence of clinical information, pharmacogenetics, systems pharmacology and pharmacometrics, and technology. Advanced pharmacometrics research is now more appliable and implementable to improve health care. This article presents examples of successful development and implementation of pharmacogenetics-guided and PK/PD model-informed decision support to facilitate precision dosing, including the development of an EHR-embedded decision support tool. Through the integration of clinical decision support tools in EHRs, clinical pharmacometrics support can be brought directly to the clinical team and the bedside.

Methotrexate (MTX), an antifolate, is administered at high doses to treat malignancies in children and adults. However, there is considerable interpatient variability in clearance of high-dose (HD) MTX. Patients with delayed clearance are at an increased risk for severe nephrotoxicity and life-threatening systemic MTX exposure. Glucarpidase is a rescue agent for severe MTX toxicity that reduces plasma MTX levels via hydrolysis of MTX into inactive metabolites, but is only indicated when MTX concentrations are > 2 SDs above the mean excretion curve specific for the given dose together with a significant creatinine increase (> 50%). Appropriate administration of glucarpidase is challenging due to the ambiguity in the labeled indication. A recent consensus guideline was published with an algorithm to provide clarity in when to administer glucarpidase, yet clinical interpretation of laboratory results that do not directly correspond to the algorithm prove to be a limitation of its use. The goal of our study was to develop a clinical decision support tool to optimize the administration of glucarpidase for patients receiving HD MTX. Here, we describe the development of a novel 3-compartment MTX population pharmacokinetic (PK) model using 31,672 MTX plasma concentrations from 772 pediatric patients receiving HD MTX for the treatment of acute lymphoblastic leukemia and its integration into the online clinical decision support tool, MTXPK.org. This web-based tool has the functionality to utilize individualized demographics, serum creatinine, and real-time drug concentrations to predict the elimination profile and facilitate model-informed administration of glucarpidase.

Background Pediatric anxiety disorders such as generalized anxiety disorder (GAD) are common, impairing, and often undertreated. Moreover, many youth do not respond to standard, evidence-based psychosocial or psychopharmacologic treatment. An increased understanding of the gamma-aminobutyric acid (GABA) and glutamate neurotransmitter systems has created opportunities for novel intervention development for pediatric GAD. Methods This narrative review examines potential candidates for pediatric GAD: eszopiclone, riluzole, eglumegad (LY354740), pimavanserin, agomelatine. Results The pharmacology, preclinical data, clinical trial findings and known side effects of eszopiclone, riluzole, eglumegad (LY354740), pimavanserin, agomelatine, are reviewed, particularly with regard to their potential therapeutic relevance to pediatric GAD. Conclusion Notwithstanding numerous challenges, some of these agents represent potential candidate drugs for pediatric GAD. Further treatment development studies of agomelatine, eszopiclone, pimavanserin and riluzole for pediatric GAD also have the prospect of informing the understanding of GABAergic and glutamatergic function across development.

Chemotherapy-induced nausea and vomiting (CINV) is commonly experienced by patients receiving antineoplastic agents prior to hemopoietic stem cell transplant (HSCT). Ondansetron, a 5-HT3 antagonist metabolized by CYP2D6, is an antiemetic prescribed to treat short-term CINV, but some patients still experience uncontrolled nausea and vomiting while taking ondansetron. Adult CYP2D6 ultrarapid metabolizers (UMs) are at higher risk for CINV due to rapid ondansetron clearance, but similar studies have not been performed in pediatric patients. We performed a retrospective chart review of 128 pediatric HSCT recipients who received ondansetron for CINV prevention and had CYP2D6 genotyping for 20 alleles and duplication detection. The number of emetic episodes for each patient was collected from the start of chemotherapy through 7 days after HSCT. The average age of the cohort was 6.6 years (range: 0.2-16.7) and included three UMs, 72 normal metabolizers, 47 intermediate metabolizers, and six poor metabolizers. Because UMs are the population at risk for inefficacy, we describe the course of treatment for these three patients, as well as the factors influencing emesis: chemotherapy emetogenicity, diagnosis, and duration of ondansetron administration. The cases described support guidelines recommending non-CYP2D6 metabolized antiemetics (e.g., granisetron) when a patient is a known CYP2D6 UM, but pediatric studies with a larger sample of CYP2D6 UMs are needed to validate our findings.

There is growing interest in utilizing pharmacogenetic (PGx) testing to guide antidepressant use, but there is lack of clarity on how to implement testing into clinical practice. We administered two surveys at 17 sites that had implemented or were in the process of implementing PGx testing for antidepressants. Survey 1 collected data on the process and logistics of testing. Survey 2 asked sites to rank the importance of Consolidated Framework for Implementation Research (CFIR) constructs using best‐worst scaling choice experiments. Of the 17 sites, 13 had implemented testing and four were in the planning stage. Thirteen offered testing in the outpatient setting, and nine in both outpatient/inpatient settings. PGx tests were mainly ordered by psychiatry (92%) and primary care (69%) providers. CYP2C19 and CYP2D6 were the most commonly tested genes. The justification for antidepressants selected for PGx guidance was based on Clinical Pharmacogenetics Implementation Consortium guidelines (94%) and US Food and Drug Administration (FDA; 75.6%) guidance. Both institutional (53%) and commercial laboratories (53%) were used for testing. Sites varied on the methods for returning results to providers and patients. Sites were consistent in ranking CFIR constructs and identified patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and the identification of champions as most important for implementation. Sites deployed similar implementation strategies and measured similar outcomes. The process of implementing PGx testing to guide antidepressant therapy varied across sites, but key drivers for successful implementation were similar and may help guide other institutions interested in providing PGx‐guided pharmacotherapy for antidepressant management.

The neuropharmacology of marijuana, including its effects on selective serotonin reuptake inhibitor (SSRI)/antidepressant metabolism and the subsequent response and tolerability in youth, has received limited attention. We sought to (1) review clinically relevant pharmacokinetic (PK) and pharmacodynamic (PD) interactions between cannabinoids and selected SSRIs, (2) use PK models to examine the impact of cannabinoids on SSRI exposure (area under curve (AUC)) and maximum concentration (CMAX) in adolescents, and (3) examine the frequency of adverse events reported when SSRIs and cannabinoids are used concomitantly. Cannabinoid metabolism, interactions with SSRIs, impact on relevant PK/PD pathways and known drug–drug interactions were reviewed. Then, the impact of tetrahydrocannabinol (THC) and cannabidiol (CBD) on exposure (AUC24) and CMAX for escitalopram and sertraline was modeled using pediatric PK data. Using data from the Food and Drug Administration Adverse Events Reporting System (FAERS), the relationship between CBD and CYP2C19-metabolized SSRIs and side effects was examined. Cannabis and CBD inhibit cytochrome activity, alter serotonergic transmission, and modulate SSRI response. In PK models, CBD and/or THC increases sertraline and es/citalopram concentrations in adolescents, and coadministration of CBD and CYP2C19-metabolized SSRIs increases the risk of cough, diarrhea, dizziness, and fatigue. Given the significant SSRI–cannabinoid interactions, clinicians should discuss THC and CBD use in youth prescribed SSRIs and be aware of the impact of initiating, stopping, or decreasing cannabinoid use as this may significantly affect es/citalopram and sertraline exposure.

Purpose: A number of institutions have clinically implemented CYP2D6 genotyping to guide drug prescribing. We compared implementation strategies of early adopters of CYP2D6 testing, barriers faced by both early adopters and institutions in the process of implementing CYP2D6 testing, and approaches taken to overcome these barriers. Methods: We surveyed eight early adopters of CYP2D6 genotyping and eight institutions in the process of adoption. Data were collected on testing approaches, return of results procedures, applications of genotype results, challenges faced, and lessons learned. Results: Among early adopters, CYP2D6 testing was most commonly ordered to assist with opioid and antidepressant prescribing. Key differences among programs included test ordering and genotyping approaches, result reporting, and clinical decision support. However, all sites tested for copy number variation and 9 common variants, and reported results in the medical record. Most sites provided automatic consultation and had designated personnel to assist with genotype-informed therapy recommendations. Primary challenges were related to stakeholder support, CYP2D6 gene complexity, phenotype assignment, and sustainability. Conclusion: There are specific challenges unique to CYP2D6 testing given the complexity of the gene and its relevance to multiple medications. Consensus lessons learned may guide those interested in pursuing similar clinical pharmacogenetic programs.