Machine Learning-Based Prediction of Escitalopram and Sertraline Side Effects With Pharmacokinetic Data in Children and Adolescents.

Selective serotonin reuptake inhibitors (SSRI) are the first-line pharmacologic treatment for anxiety and depressive disorders in children and adolescents. Many patients experience side effects that are difficult to predict, are associated with significant morbidity, and can lead to treatment discontinuation. Variation in SSRI pharmacokinetics could explain differences in treatment outcomes, but this is often overlooked as a contributing factor to SSRI tolerability. This study evaluated data from 288 escitalopram-treated and 255 sertraline-treated patients ≤ 18 years old to develop machine learning models to predict side effects using electronic health record data and Bayesian estimated pharmacokinetic parameters. Trained on a combined cohort of escitalopram- and sertraline-treated patients, a penalized logistic regression model achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% confidence interval (CI): 0.66-0.88), with 0.69 sensitivity (95% CI: 0.54-0.86), and 0.82 specificity (95% CI: 0.72-0.87). Medication exposure, clearance, and time since the last dose increase were among the top features. Individual escitalopram and sertraline models yielded an AUROC of 0.73 (95% CI: 0.65-0.81) and 0.64 (95% CI: 0.55-0.73), respectively. Post hoc analysis showed sertraline-treated patients with activation side effects had slower clearance (P = 0.01), which attenuated after accounting for age (P = 0.055). These findings raise the possibility that a machine learning approach leveraging pharmacokinetic data can predict escitalopram- and sertraline-related side effects. Clinicians may consider differences in medication pharmacokinetics, especially during dose titration and as opposed to relying on dose, when managing side effects. With further validation, application of this model to predict side effects may enhance SSRI precision dosing strategies in youth.

Opportunities for Pharmacogenetic Testing to Guide Dosing of Medications in Youths With Medicaid.

Importance: There are an increasing number of medications with a high level of evidence for pharmacogenetic-guided dosing (PGx drugs). Knowledge of the prevalence of dispensings of PGx drugs and their associated genes may allow hospitals and clinical laboratories to determine which pharmacogenetic tests to implement. Objectives: To investigate the prevalence of outpatient dispensings of PGx drugs among Medicaid-insured youths, determine genes most frequently associated with PGx drug dispenses, and describe characteristics of youths who were dispensed at least 1 PGx drug. Design, Setting, and Participants: This serial cross-sectional study includes data from 2011 to 2019 among youths aged 0 to 17 years in the Marketscan Medicaid database. Data were analyzed from August to December 2022. Main Outcomes and Measures: PGx drugs were defined as any medication with level A evidence as determined by the Clinical Pharmacogenetics Implementation Consortium (CPIC). The number of unique youths dispensed each PGx drug in each year was determined. PGx drugs were grouped by their associated genes for which there was CPIC level A evidence to guide dosing, and a dispensing rate (No. of PGx drugs/100 000 youths) was determined for each group for the year 2019. Demographics were compared between youths dispensed at least 1 PGx drug and those not dispensed any PGx drugs. Results: The number of Medicaid-insured youths queried ranged by year from 2 078 683 youths in 2011 to 4 641 494 youths in 2017, including 4 126 349 youths (median [IQR] age, 9 [5-13] years; 2 129 926 males [51.6%]) in 2019. The proportion of Medicaid-insured youths dispensed PGx drugs increased from 289 709 youths (13.9%; 95% CI, 13.8%-14.0%) in 2011 to 740 072 youths (17.9%; 95% CI, 17.9%-18.0%) in 2019. Genes associated with the most frequently dispensed medications were CYP2C9, CYP2D6, and CYP2C19 (9197.0 drugs [95% CI, 9167.7-9226.3 drugs], 8731.5 drugs [95% CI, 8702.5-8759.5 drugs], and 3426.8 drugs [95% CI, 3408.1-3443.9 drugs] per 100 000 youths, respectively). There was a higher percentage of youths with at least 1 chronic medical condition among youths dispensed at least 1 PGx drug (510 445 youths [69.0%; 95% CI, 68.8%-69.1%]) than among 3 386 277 youths dispensed no PGx drug (1 381 544 youths [40.8%; 95% CI, 40.7%-40.9%) (P < .001) in 2019. Conclusions and Relevance: In this study, there was an increasing prevalence of dispensings for PGx drugs. This finding suggests that pharmacogenetic testing of specific drug-gene pairs should be considered for frequently prescribed PGx drugs and their implicated genes.

Influence of CYP2D6 Metabolizer Status on Risperidone and Paliperidone Tolerability in Children and Adolescents.

Background: Risperidone and, to a lesser extent, paliperidone are metabolized by CYP2D6; however, there are limited data related to variation in CYP2D6 phenotypes and the tolerability of these medications in children and adolescents. Furthermore, the impact of CYP2D6 on the association of risperidone and paliperidone with hyperprolactinemia in youth is not well understood. Methods: A retrospective chart review was performed in psychiatrically hospitalized children and adolescents prescribed risperidone (n = 263, age = 3-18 years, mean age = 13 ± 3 years, 49% female) or paliperidone (n = 124, age = 5-18 years, mean age = 15 ± 2 years, 44% female) who had CYP2D6 genotyping performed as part of routine care. CYP2D6 phenotypes were determined based on Clinical Pharmacogenetics Implementation Consortium guidelines and CYP2D6 inhibitors causing phenoconversion. Adverse effects were obtained from a review of the electronic health record, and patients were selected, in part, to enrich non-normal metabolizers. Results: Among risperidone-treated patients, 45% experienced an adverse effect, whereas 36% of paliperidone-treated patients experienced adverse effects. Discontinuation of risperidone due to lack of efficacy was more frequent in the CYP2D6 normal metabolizers and ultrarapid metabolizers compared with intermediate metabolizers (IMs) and phenoconverted poor metabolizers (pPMs) (54.5% vs. 32.7%, p < 0.001). Discontinuation due to weight gain was more common among risperidone- than paliperidone-treated patients (17% vs. 7%, p = 0.011). Among those taking paliperidone, CYP2D6 was associated with discontinuation due to side effects (p = 0.008), and youth with slower CYP2D6 metabolism (i.e., pPMs and IMs) were more likely to discontinue. Hyperprolactinemia was found in 10% of paliperidone-treated patients and 5% of risperidone-treated patients, and slower CYP2D6 metabolizers required higher risperidone doses to cause hyperprolactinemia (p = 0.011). Conclusions: CYP2D6 phenotype is associated with discontinuation of risperidone due to lack of efficacy and the dose of risperidone that induced hyperprolactinemia, as well as discontinuation of paliperidone due to adverse effects. Future studies should evaluate exposure-response and toxicity relationships in risperidone- and paliperidone-treated youth.

Pharmacogenetic Factors Influence Escitalopram Pharmacokinetics and Adverse Events in Youth with a Family History of Bipolar Disorder: A Preliminary Study.

Introduction: Escitalopram is an effective and generally well-tolerated antidepressant, but children of parents with bipolar disorder (BD) may be at increased risk for adverse events associated with antidepressants, including increased irritability, restlessness, impulsivity, and manic symptoms. This risk may be influenced by polymorphisms in genes encoding cytochrome P450 enzymes (CYP2C19 or CYP2D6), the serotonin transporter (SLC6A4), and the serotonin receptor 2A subtype (HTR2A). We explored whether gene-drug interactions influence the emergence of adverse events in depressed and/or anxious youth with a family history of BD. Materials and Methods: Children and adolescents aged 12-17 years with a first-degree relative with bipolar I disorder were treated with escitalopram and monitored for adverse effects, underwent pharmacogenetic testing, and provided serum escitalopram levels. Emergence of adverse events was determined by study clinicians, and symptoms were tracked using the Treatment-Emergent Activation and Suicidality Assessment Profile (TEASAP) and Pediatric Adverse Events Rating Scale. Clinical Pharmacogenetics Implementation Consortium guidelines were used to determine CYP2C19 and CYP2D6 phenotypes. Results: Slower CYP2C19 metabolizers had greater dose-normalized 24-hour area under the curve (AUC0-24; p = 0.025), trough concentrations (Ctrough; p = 0.013), and elimination half-lives (t1/2; p < 0.001). CYP2D6 phenotype was not significantly associated with any pharmacokinetic parameter. Slower CYP2D6 metabolizers had increased TEASAP akathisia (p = 0.015) scores. HTR2A A/A and A/G genotypes were associated with increased TEASAP "self-injury, suicidality, and harm to others" subscale scores (p = 0.017). Escitalopram maximum concentration, AUC0-24, CYP2C19 phenotype, and SLC6A4 genotype were not associated with adverse events. Conclusions: CYP2C19 phenotype influences escitalopram pharmacokinetics whereas CYP2D6 phenotype does not. Slower CYP2D6 metabolism was associated with increased akathisia, and HTR2A A/A or A/G genotypes were associated with increased risk of self-harm or harm to others. Larger cohorts are needed to identify associations between genetic test results and antidepressant-associated adverse events. Trial Registration: ClinicalTrials.gov identifier: NCT02553161.

CYP2D6 Phenotype Influences Pharmacokinetic Parameters of Venlafaxine: Results from a Population Pharmacokinetic Model in Older Adults with Depression.

In this study, we aimed to improve upon a published population pharmacokinetic (PK) model for venlafaxine (VEN) in the treatment of depression in older adults, then investigate whether CYP2D6 metabolizer status affected model-estimated PK parameters of VEN and its active metabolite O-desmethylvenlafaxine. The model included 325 participants from a clinical trial in which older adults with depression were treated with open-label VEN (maximum 300 mg/day) for 12 weeks and plasma levels of VEN and O-desmethylvenlafaxine were assessed at weeks 4 and 12. We fitted a nonlinear mixed-effect PK model using NONMEM to estimate PK parameters for VEN and O-desmethylvenlafaxine adjusted for CYP2D6 metabolizer status and age. At both lower doses (up to 150 mg/day) and higher doses (up to 300 mg/day), CYP2D6 metabolizers impacted PK model-estimated VEN clearance, VEN exposure, and active moiety (VEN + O-desmethylvenlafaxine) exposure. Specifically, compared with CYP2D6 normal metabolizers, (i) CYP2D6 ultra-rapid metabolizers had higher VEN clearance; (ii) CYP2D6 intermediate metabolizers had lower VEN clearance; (iii) CYP2D6 poor metabolizers had lower VEN clearance, higher VEN exposure, and higher active moiety exposure. Overall, our study showed that including a pharmacogenetic factor in a population PK model could increase model fit, and this improved model demonstrated how CYP2D6 metabolizer status affected VEN-related PK parameters, highlighting the importance of genetic factors in personalized medicine.

Current Practices in Pharmacogenomics.

Pharmacogenomics, where genomic information is used to tailor medication management, is a strategy to maximize drug efficacy and minimize toxicity. Although pediatric evidence is less robust than for adults, medications influenced by pharmacogenomics are prescribed to children and adolescents. Evidence-based guidelines and drug label annotations are available from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Pharmacogenomics Knowledgebase (PharmGKB). Some pediatric health care facilities use pharmacogenomics to provide dosing recommendations to pediatricians. Herein, we use a case-based approach to illustrate the use of pharmacogenomic data in pediatric clinical care and provide resources for finding and using pharmacogenomic guidelines.

Escitalopram and Sertraline Population Pharmacokinetic Analysis in Pediatric Patients.

BACKGROUND AND OBJECTIVE: Escitalopram and sertraline are commonly prescribed for anxiety and depressive disorders in children and adolescents. The pharmacokinetics (PK) of these medications have been evaluated in adults and demonstrate extensive variability, but studies in pediatric patients are limited. Therefore, we performed a population PK analysis for escitalopram and sertraline in children and adolescents to characterize the effects of demographic, clinical, and pharmacogenetic factors on drug exposure. METHODS: A PK dataset was generated by extracting data from the electronic health record and opportunistic sampling of escitalopram- and sertraline-treated psychiatrically hospitalized pediatric patients aged 5-18 years. A population PK analysis of escitalopram and sertraline was performed using NONMEM. Concentration-time profiles were simulated using MwPharm++ to evaluate how covariates included in the final models influence medication exposure and compared to adult therapeutic reference ranges. RESULTS: The final escitalopram cohort consisted of 315 samples from 288 patients, and the sertraline cohort consisted of 265 samples from 255 patients. A one-compartment model with a proportional residual error model best described the data for both medications. For escitalopram, CYP2C19 phenotype and concomitant CYP2C19 inhibitors affected apparent clearance (CL/F), and normalizing CL/F and apparent volume of distribution (V/F) to body surface area (BSA) improved estimations. The final escitalopram model estimated CL/F and V/F at 14.2 L/h/1.73 m2 and 428 L/1.73 m2, respectively. For sertraline, CYP2C19 phenotype and concomitant CYP2C19 inhibitors influenced CL/F, and empirical allometric scaling of patient body weight on CL/F and V/F was significant. The final sertraline model estimated CL/F and V/F at 124 L/h/70 kg and 4320 L/70 kg, respectively. Normalized trough concentrations (Ctrough) for CYP2C19 poor metabolizers taking escitalopram were 3.98-fold higher compared to normal metabolizers (151.1 ng/mL vs 38.0 ng/mL, p < 0.0001), and normalized Ctrough for CYP2C19 poor metabolizers taking sertraline were 3.23-fold higher compared to normal, rapid, and ultrarapid metabolizers combined (121.7 ng/mL vs 37.68 ng/mL, p < 0.0001). Escitalopram- and sertraline-treated poor metabolizers may benefit from a dose reduction of 50-75% and 25-50%, respectively, to normalize exposure to other phenotypes. CONCLUSION: To our knowledge, this is the largest population PK analysis of escitalopram and sertraline in pediatric patients. Significant PK variability for both medications was observed and was largely explained by CYP2C19 phenotype. Slower CYP2C19 metabolizers taking escitalopram or sertraline may benefit from dose reductions given increased exposure.

Clinical covariates that improve the description of high dose methotrexate pharmacokinetics in a diverse population to inform MTXPK.org.

The MTXPK.org webtool was launched in December 2019 and was developed to facilitate model-informed supportive care and optimal use of glucarpidase following the administration of high-dose methotrexate (HDMTX). One limitation identified during the original development of the MTXPK.org tool was the perceived generalizability because the modeled population comprised solely of Nordic pediatric patients receiving 24-h infusions for the treatment of acute lymphoblastic leukemia. The goal of our study is to describe the pharmacokinetics of HDMTX from a diverse patient population (e.g., races, ethnicity, indications for methotrexate, and variable infusion durations) and identify meaningful factors that account for methotrexate variability and improve the model's performance. To do this, retrospectively analyzed pharmacokinetic and toxicity data from pediatric and adolescent young adult patients who were receiving HDMTX (>0.5 g/m2 ) for the treatment of a cancer diagnosis from three pediatric medical centers. We performed population pharmacokinetic modeling referencing the original MTXPK.org NONMEM model (includes body surface area and serum creatinine as covariates) on 1668 patients, 7506 administrations of HDMTX, and 30,250 concentrations. Our results support the parameterizations of short infusion duration (<8 h) and the presence of Down syndrome on methotrexate clearance, the parameterization of severe hypoalbuminemia (<2.5 g/dL) on the intercompartmental clearance (Q2 and Q3), and the parameterization of pleural effusion on the volume of distribution (V1 and V2). These novel parameterizations will increase the generalizability of the MTXPK.org model once they are added to the webtool.

Tacrolimus pharmacokinetics are influenced by CYP3A5, age, and concomitant fluconazole in pediatric kidney transplant patients.

Tacrolimus, the most common immunosuppressant for organ transplant, has a narrow therapeutic range and is metabolized by CYP3A4/5. Trough concentration monitoring and dosing adjustments are used to reach a therapeutic range. CYP3A5 intermediate and normal metabolizers (*1 allele carriers; IM/NM) demonstrate faster tacrolimus metabolism than poor metabolizers (PM). We analyzed the electronic health records of 93 patients aged <21 years for the first 8 weeks after a kidney transplant between January 2010 and December 2021. The target tacrolimus trough was 10-15 ng/mL in the first 4 weeks and 7-10 ng/mL in the next 4 weeks. Banked DNA was collected and genotyped for CYP3A5*3, *6, *7, and *8 alleles. We found that CYP3A5 IM/NM (n = 21) took longer than PM (n = 72) to reach the therapeutic range (7 vs. 4 days, p = 0.048). IM/NM had more dose adjustments (8 vs. 6, p = 0.025) and needed >150% of the required daily dose compared with PM. The concentration/dose ratio was influenced by age and concomitant fluconazole (p = 0.0003, p = 0.034, respectively) and the average daily dose decreases with age in CYP3A5 PM (p = 0.001). Tremors were more common in patients who ever had a trough concentration >15 ng/mL compared with those who never had a trough concentration >15 ng/mL (OR 3.31, 95% CI 1.03-8.98, p = 0.038). Using standard dosing, CYP3A5 IM/NM took longer to reach the goal range and require more dose adjustments and higher doses than PM. Preemptive genotyping could decrease the number of dose changes necessary to reach a therapeutic dose. We have implemented pre-transplant CYP3A5 testing at our institution.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A Genotypes and Serotonin Reuptake Inhibitor Antidepressants.

Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI-like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin-2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing.

Advancing CYP2D6 Pharmacogenetics through a Pharmacoequity Lens.

Over 20% of US Food and Drug Administration (FDA)-approved drugs in the United States are metabolized by the hepatic enzyme cytochrome P450 2D6 (CYP2D6). The gene encoding CYP2D6 is highly polymorphic and genetic variation has been shown to impact drug response for many commonly dispensed drugs including opioids and antidepressants. Thus, it is important to understand an individual's CYP2D6 metabolizer status to optimize treatment outcomes for patients taking medications that are metabolized by this enzyme. Consequently, clinical CYP2D6 pharmacogenetic testing is being implemented by a growing number of health centers. Furthermore, clinical guidelines currently recommend adapting therapeutic regimens based on CYP2D6 genotype-informed phenotype. However, CYP2D6 genetic variation varies considerably across global populations and many allelic variants, or star alleles, are predominantly found in certain ancestral populations. Although CYP2D6 genetic variation has been extensively studied, there is still a paucity of information for many non-European populations. As has been shown for other pharmacogenes in randomized controlled trials, results from European populations cannot simply be extrapolated to other groups and, in some cases, even has the potential to cause harm. Therefore, enhanced inclusion in pharmacogenetic studies is urgently needed to increase ancestral representation, determine the extent of global CYP2D6 genetic variation (e.g., ancestry-specific variants), and determine the clinical impact of this variation on clinical treatment outcome. This review highlights knowledge gaps, challenges, and future directions in CYP2D6 pharmacogenomics through a unique pharmacoequity lens to address health inequities that hamper our ability to optimize drug therapy for improved pharmacological outcomes in diverse populations globally.

Adverse Effects of Antidepressant Medications and their Management in Children and Adolescents.

INTRODUCTION: Selective serotonin reuptake inhibitors (SSRIs) and, to a lesser extent, serotonin-norepinephrine reuptake inhibitors (SNRIs) are the cornerstone of pharmacotherapy for children and adolescents with anxiety and depressive disorders. These medications alleviate symptoms and restore function for many youths; however, they are associated with a distinct adverse effect profile, and their tolerability may complicate treatment or lead to discontinuation. Yet, SSRI/SNRI tolerability has received limited attention in the pediatric literature. METHODS: This review examines the early- (e.g., activation, gastrointestinal symptoms, sedation) and late-emerging (e.g., weight gain) adverse effects of SSRIs and some SNRIs in pediatric patients. RESULTS: We provide a framework for discussing SSRI/SNRI tolerability with patients and their families and describe the pharmacologic basis, course, and predictors of adverse events in youth. Strategies to address specific tolerability concerns are presented. For selected adverse events, using posterior simulation of mean differences over time, we describe their course based on Physical Symptom Checklist measures in a prospective, randomized trial of anxious youth aged 7-17 years who were treated with sertraline (n = 139) or placebo (n = 76) for 12 weeks in the Child/Adolescent Anxiety Multimodal Study (CAMS). MAIN RESULTS: In CAMS, the relative severity/burden of total physical symptoms (p < 0.001), insomnia (p = 0.001), restlessness (p < 0.001), nausea (p = 0.002), abdominal pain (p < 0.001), and dry mouth (p = 0.024) decreased from baseline over 12 weeks of sertraline treatment, raising the possibility that these symptoms are transient. No significant changes were observed for sweating (p = 0.103), constipation (p = 0.241), or diarrhea (p = 0.489). Finally, we review the antidepressant withdrawal syndrome in children and adolescents and provide guidance for SSRI discontinuation, using pediatric pharmacokinetic models of escitalopram and sertraline-two of the most used SSRIs in youth. CONCLUSION: SSRI/SNRIs are associated with both early-emerging (often transient) and late-emerging adverse effects in youth. Pharmacokinetically-informed appraoches may address some adverse effects and inform SSRI/SNRI discontinuation strategies.

Implementation of CYP2D6-guided opioid therapy at Cincinnati Children's Hospital Medical Center.

PURPOSE: We describe the implementation of CYP2D6-focused pharmacogenetic testing to guide opioid prescribing in a quaternary care, nonprofit pediatric academic medical center. SUMMARY: Children are often prescribed oral opioids after surgeries, for cancer pain, and occasionally for chronic pain. In 2004, Cincinnati Children's Hospital Medical Center implemented pharmacogenetic testing for CYP2D6 metabolism phenotype to inform codeine prescribing. The test and reports were updated to align with changes over time in the testing platform, the interpretation of genotype to phenotype, the electronic health record, and Food and Drug Administration (FDA) guidance. The use of the test increased when a research project required testing and decreased as prescribing of oxycodone increased due to FDA warnings about codeine. Education about the opioid-focused pharmacogenetic test was provided to prescribers (eg, the pain and sickle cell teams) as well as patients and families. Education and electronic health record capability increased provider compliance with genotype-guided postsurgical prescribing of oxycodone, although there was a perceived lack of utility for oxycodone prescribing. CONCLUSION: The implementation of pharmacogenetic testing to inform opioid prescribing for children has evolved with accumulating evidence and guidelines, requiring changes in reporting of results and recommendations.

PharmVar GeneFocus: SLCO1B1.

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.

Insights from a pharmacometric analysis of HDMTX in adults with cancer: Clinically relevant covariates for application in precision dosing.

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.

Development of Competency-based Online Genomic Medicine Training (COGENT).

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.

A retrospective examination of adjunctive L-methylfolate in children and adolescents with unipolar depression.

BACKGROUND: 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. METHODS: 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. RESULTS: 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). LIMITATIONS: 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. CONCLUSION: 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.

A Double-Blind Randomized Trial to Investigate Mechanisms of Antidepressant-Related Dysfunctional Arousal in Depressed or Anxious Youth at Familial Risk for Bipolar Disorder.

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.