Clinical pharmacology in Stockholm 50 years—report from the jubilee symposium

Eichelbaum, Michel; Sjöqvist, Folke

doi:10.1007/s00228-018-2432-6

Cited by 8 publications

(10 citation statements)

References 30 publications

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“…In various countries, physicians specializing in clinical pharmacology routinely utilize pharmacogenomics as a means to avoid drug toxicity by mainly using TDM, applying Bayesian dosing methods, and other techniques with the aim of patient drug safety (Borobia et al, 2017;Eichelbaum, Dahl & Sjöqvist, 2018). In the U.S., there needs to be a significant increase in clinical pharmacology training programs that provide direct entry following medical school, as is done internationally, to have more clinical pharmacologists within the hospitals to carry out traditional patient care roles, consult with other physicians, interpret the pharmacogenomics testing reports, and advance the field.…”

Section: Pharmacogenomics Therapeutic Drug Monitoring and Clinical mentioning

confidence: 99%

Association of sleep among 30 antidepressants: a population-wide adverse drug reaction study, 2004–2019

Eugene

2020

PeerJ

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Background Sleep is one of the most essential processes required to maintain a healthy human life, and patients experiencing psychiatric illness often experience an inability to sleep. The aim of this study is to test the hypothesis that antidepressant compounds with strong binding affinities for the serotonin 5-HT2C receptor, histamine H1 receptors, or norepinephrine transporter (NET) will be associated with the highest odds of somnolence. Methods Post-marketing cases of patient adverse drug reactions were obtained from the United States Food and Drug Administration Adverse Events Reporting System (FAERS) during the reporting window of January 2004 to September 2019. Disproportionality analyses of antidepressants reporting somnolence were calculated using the case/non-case method. The reporting odds-ratios (ROR) and corresponding 95% confidence interval (95% CI) were computed and all computations and graphing conducted in R. Results There were a total of 69,196 reported cases of somnolence out of a total of 7,366,864 cases reported from January 2004 to September 2019. Among the 30 antidepressants assessed, amoxapine (n = 16) reporting odds-ratio (ROR) = 7.1 (95% confidence interval [CI] [4.3–11.7]), atomoxetine (n = 1,079) ROR = 6.6 (95% CI [6.2–7.1]), a compound generally approved for attention deficit hyperactivity disorder (ADHD), and maprotiline (n = 18) ROR = 6.3 (95% CI, 3.9–10.1) were the top three compounds ranked with the highest reporting odds of somnolence. In contrast, vortioxetine (n = 52) ROR = 1.3 (95% CI [1.0–1.8]), milnacipran (n = 58) ROR = 2.1 (95% CI [1.7–2.8]), and bupropion (n = 1,048) ROR = 2.2 (95% CI [2.1–2.4]) are least significantly associated with somnolence. Moreover, levomilnacipran (n = 1) ROR = 0.4 (95% CI [0.1–2.9]) was not associated with somnolence. Conclusion Among the thirty tested antidepressants, consistent with the original hypothesis, amoxepine has strongest 5-HT2C receptor binding affinity and has the highest reporting odds of somnolence. Atomoxetine, ranked second in reporting odds of somnolence overall, binds to the NET with with the strongest binding affinity among the thirty compounds. Mirtazapine, a tetracyclic antidepressant, was ranked 11th in reporting odds of somnolence and had the strongest H1 receptor binding affinity. This study provides an informative ranking of somnolence among thirty antidepressant compounds with an already wide array of clinical indications as well as provides insight into potential drug repurposing in psychopharmacology.

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Section: Pharmacogenomics Therapeutic Drug Monitoring and Clinical mentioning

confidence: 99%

Association of sleep among 30 antidepressants: a population-wide adverse drug reaction study, 2004–2019

Eugene

2020

PeerJ

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“…Across Europe and in North America, centres of excellence exist where paediatric clinical pharmacology services are well established and contribute to patient care directly. [6][7][8] Children and young people (CYP) deserve medical treatments that are of the same quality and safety as adults. Within paediatrics, despite formularies such as the British National Formulary for Children, there is evidence that prescriptions for similar conditions in CYP in different healthcare settings or geographical areas vary considerably, indicating that there are still considerable improvements to be made in implementing rational prescribing in the UK.…”

Section: Introductionmentioning

confidence: 99%

Implementing a specialist paediatric clinical pharmacology service in a UK children's hospital

Hawcutt

Warner

Kenyon

et al. 2021

Brit J Clinical Pharma

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Aims: Royal College of Paediatrics and Child Health subspecialist training in Paediatric Clinical Pharmacology and Therapeutics has been delivered in the UK for 20 years, but no specialist clinical services have been set up previously. Methods: Prospective audit and service evaluation of paediatric clinical pharmacology service pilot phase and dedicated service at a UK children's hospital. Results: Pilot scheme (May-October 2019), then weekly service (established June 2020). Service covers the High Dependency Unit, and inpatients with polypharmacy.The pilot demonstrated high levels of acceptance, with 89% of suggested medication changes agreed by lead clinical team, and success, with 97.5% of suggested changes continued until discharge/pilot completion. Economic analysis estimated direct annualised cost savings on medications of up to £10 000. After 20 ward rounds of the established service, 270 potential medication changes were identified, 213 were carried out (78.9%). The most common were deprescribing (n = 143), prescribing (n = 47) and dose adjustment (n = 8). Seventy-five different medications were deprescribed, most commonly chloral hydrate (n = 12), Lactulose, ibuprofen, Bio-Kult and sodium alginate (all n = 4). The percentage of inpatients prescribed ≥10 medications decreased from 38.5 to 32.1%, while the subset prescribed ≥20 medications decreased from 11.0 to 5.67%. The mean number of medicines prescribed decreased from 9.0 to 8.0, while the median was unchanged at 7. Annual Yellow Card reports of suspected adverse drug reactions more than doubled (n = 66). Conclusion:A UK model for subspecialist paediatric clinical pharmacology service delivery has demonstrated a positive clinical impact and could be replicated at other UK secondary/tertiary children's hospitals.

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“…In such cases, hospital systems should embed clinical pharmacologist physicians, as is done by leading hospitals globally (e.g. Karolinska Institute in Stockholm Sweden awarding the Nobel Prize, the Mayo Clinic, and more) that aim to maintain high rates of patient drug safety and hospital quality outcome measures ( Eichelbaum et al ., 2018; Eugene & Eugene, 2018). However, even after accounting for drug doses and drug selection to avoid adverse drug reactions, divergent clinical response rates, among genders, are well-known and reported in psychiatric patients treated with lithium ( Viguera et al ., 2000).…”

Section: Introductionmentioning

confidence: 99%

Predicting lithium treatment response in bipolar patients using gender-specific gene expression biomarkers and machine learning

2018

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Background: We sought to test the hypothesis that transcriptome-level gene signatures are differentially expressed between male and female bipolar patients, prior to lithium treatment, in a patient cohort who later were clinically classified as lithium treatment responders. Methods: Gene expression study data was obtained from the Lithium Treatment-Moderate dose Use Study data accessed from the National Center for Biotechnology Information’s Gene Expression Omnibus via accession number GSE4548. Differential gene expression analysis was conducted using the Linear Models for Microarray and RNA-Seq (limma) package and the Decision Tree and Random Forest machine learning algorithms in R. Results: Using quantitative gene expression values reported from patient blood samples, the RBPMS2 and LILRA5 genes classify male lithium responders with an area under the receiver operator characteristic curve (AUROC) of 0.92 and the ABRACL, FHL3, and NBPF14 genes classify female lithium responders AUROC of 1. A Decision Tree rule for establishing male versus female samples, using gene expression values were found to be: if RPS4Y1 ≥ 9.643, patient is a male and if RPS4Y1 < 9.643, patient is female with a probability=100%. Conclusions: We developed a pre-treatment gender- and gene-expression-based predictive model selective for classifying male lithium responders with a sensitivity of 96% using 2-genes and female lithium responders with sensitivity=92% using 3-genes.

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Clinical pharmacology in Stockholm 50 years—report from the jubilee symposium

Cited by 8 publications

References 30 publications

Association of sleep among 30 antidepressants: a population-wide adverse drug reaction study, 2004–2019

Association of sleep among 30 antidepressants: a population-wide adverse drug reaction study, 2004–2019

Implementing a specialist paediatric clinical pharmacology service in a UK children's hospital

Predicting lithium treatment response in bipolar patients using gender-specific gene expression biomarkers and machine learning

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