Aim: The pharmacokinetics of doravirine have been studied in clinical trials, but not in real-world settings. Our study aims to characterize and identify factors influencing doravirine pharmacokinetics (a CYP3A4 substrate) in real-world people with HIV (PWH). Methods: A total of 174 doravirine concentrations measured in 146 PWH followed up in the therapeutic drug monitoring (TDM) program at the University Hospital of Lausanne (Switzerland) between 2019 and 2023 were included in the analysis. Population pharmacokinetic analysis and Monte Carlo simulations to investigate the clinical significance of the covariates retained in the final model were performed using NONMEM. Results: A one-compartment model with first-order absorption and linear elimination best described doravirine pharmacokinetics. Potent CYP3A4 inhibitors and, to a lesser extent age, were the only tested covariates to significantly impact doravirine clearance (CL). Potent CYP3A4 reduced CL by 50%, and a 30% decrease in CL was observed in an 80-year-old compared to a 55-year-old PWH. The effect of potent CYP3A4 inhibitors was prominent, explaining 59% of between-subject variability in CL. Model-based simulations predicted 2.8-fold and 1.6-fold increases in median steady-state trough and maximum doravirine concentrations, respectively, when a potent CYP3A4 inhibitor was co-administered. Conclusion: Our findings show that potent CYP3A4 inhibitors and age influence doravirine pharmacokinetics. However, given the good tolerability of doravirine, dosing adjustment of doravirine is probably not mandatory in those situations. TDM remains useful essentially in specific clinical situations, such as hepatic impairment, suspected non-adherence or pregnancy.

A reexamination of clinical principles of long-term opioid therapy (LTOT) for chronic pain is long overdue amid the ongoing opioid crisis. Most patients on LTOT report ineffectiveness (poor pain control, function, and health), but still find deprescribing challenging. Although prescribed as analgesics, opioids more likely provide pain relief primarily through reward system actions (enhanced relief and motivation) and placebo effect and less through anti-nociceptive effects. The unavoidable physiologic LTOT dependence can automatically lead to a paradoxical worsening of pain, disability, and medical instability (maladaptive opioid dependence) without addiction due to allostatic opponent neuroadaptations involving reward/anti-reward and nociceptive/anti-nociceptive systems. This opioid induced chronic pain syndrome (OICP) can persist/progress whether LTOT dose is maintained at the same level, increased, decreased, or discontinued. Current conceptualization of LTOT as a straightforward long-term analgesic therapy appears incongruous in view of the complex mechanisms of opioid action, LTOT dependence and OICP. LTOT can be more appropriately conceptualized as therapeutic induction and maintenance of an adaptive LTOT dependence for functional improvement irrespective of analgesic benefits. Adaptive LTOT dependence should be ideally used for a limited time to achieve maximum functional recovery and deprescribed while maintaining functional gains. Patients on LTOT should be regularly reevaluated to identify if maladaptive LTOT dependence with OICP has diminished any functional gains or lead to ineffectiveness. Ineffective LTOT (with maladaptive LTOT dependence) should be modified to make it safer and more effective. An adequately functional life without opioids is the ideal healthy long-term goal for both LTOT initiation and LTOT modification.

Aims: To evaluate the effect of the combination of carotegrast methyl with rifampicin, a potent inhibitor of organic anion transporter polypeptide, on the pharmacokinetics (PK), safety and tolerability. Methods: In this 2 x 2 crossover study in 20 healthy Japanese adults, 10 subjects received carotegrast methyl 960 mg and rifampicin 600 mg on day 1, and received carotegrast methyl 960 mg on day 8. The subjects in the other sequence received the same treatments but in the opposite order. When the 90% confidence interval (CI) of the geometric mean ratio of the AUC0-t and Cmax for carotegrast, the main active metabolite of carotegrast methyl, with/without rifampicin fell within the range of 0.80 – 1.25, it was deemed that no PK interaction occurred. Adverse events (AEs) were monitored. Results: The Cmax and AUC0-t for carotegrast with/without rifampicin was 11724.5 ± 6097.6 vs 2620.1 ± 1843.0 ng mL-1, and 55046.0 ± 23427.8 vs 9849.9 ± 4580.6 ng h mL-1, respectively. The ratios (90% CI) of the Cmax and AUC0-t with/without rifampicin were 4.78 (3.64 – 6.29) and 5.59 (4.60 – 6.79), respectively, indicating carotegrast has a PK interaction with rifampicin. The combination with rifampicin also increased the exposure of carotegrast and its metabolites. The incidence of any AEs with/without rifampicin was five (25.0%) and one (5.0%), respectively. Conclusion: Coadministration of carotegrast methyl with rifampicin significantly increased exposure of carotegrast compared with carotegrast methyl administration alone. However, no increase in the incidence of adverse drug reactions due to coadministration with rifampicin was observed.

Aims: To evaluate drug-drug interactions between carotegrast methyl, a CYP3A4 inhibitor, and other CYP3A4 substrates, midazolam, atorvastatin, and prednisolone. Methods: A total of 88 healthy volunteers orally received carotegrast methyl 960 mg three times daily for 14 days. A single oral (5 mg) or intravenous (0.017 mg kg-1) midazolam, oral (5 mg) prednisolone, or oral (10 mg) atorvastatin was administered before, with, and after carotegrast methyl treatment. When the 90% confidence interval (CI) for the geometric mean ratios of the pharmacokinetic (PK) parameters with coadministration with carotegrast methyl (day 14) to those before carotegrast methyl administration was between 0.80 and 1.25, no PK interaction were deemed. Results: The Cmax and AUC0-t of oral midazolam before administration of carotegrast methyl was 30.9 ± 9.8 ng mL-1 and 74.5 ± 21.9 ng h mL-1, respectively. The geometric mean ratio of the Cmax and AUC0-t of midazolam on day 14 to those on day -1 was 1.86 (90% CI, 1.64 – 2.11) and 3.07 (90% CI, 2.81 – 3.35), which did not fall within the range of 0.80 – 1.25, suggesting that carotegrast methyl had a PK interaction with midazolam. Similar PK interactions were found for intravenous midazolam and atorvastatin, but not for prednisolone. The inhibitory effect of carotegrast methyl on CYP3A4-mediated metabolism of midazolam and atorvastatin had almost disappeared by 14 days after the end of administration. Conclusion: Carotegrast methyl was classified as a moderate CYP3A4 inhibitor in humans. Carotegrast methyl might enhance the action of drugs that are metabolized by CYP3A4.

A middle-aged Caucasian man presented with a six-month history of bilateral enlargement of the breasts associated with pain. His hormonal profile was normal and no other underlying cause was identified, we diagnosed him with idiopathic gynecomastia. He is living with HIV, clinically stable (viral load <20copies/mL) and on injectable antiretrovirals cabotegravir/rilpivirine. Tamoxifen is an anti-estrogen recommended for gynecomastia and has been described in persons living with HIV. In this case, tamoxifen could potentially induce the activity of cytochrome P450 3A4 (CYP3A4), reducing rilpivirine concentrations, which consequently may cause virological failure. According to the National Health Service (NHS) guidelines in the UK, an aromatase inhibitor can be used in place of tamoxifen. To date, there have been no reported cases of using anastrozole as a treatment for gynecomastia in people living with HIV, or of its co-administration with antiretrovirals.

Aim: As the non-vitamin K antagonist oral anticoagulant (NOAC) most recently approved in China, data pertaining to clinical edoxaban use are still scarce. This study investigated the prevalence of and contemporary trends in edoxaban prescription among Chinese patients as well as factors associated with its inappropriate use in a multi-center registry of patients treated in real-world clinical practice. Methods: This real-world, prospective, multicenter, and non-interventional study included 1005 inpatients treated with edoxaban. According to National Medical Products Administration and European Heart Rhythm Association guidelines, edoxaban therapy was determined to be appropriate or inappropriate in each case. Results: The median patient age was 70.0 years (interquartile range, 61.0–78.0 years), and 46.3% were women. Overall, 456 (45.4%) patients received inappropriate edoxaban therapy, and common issues included an inappropriately low (183, 18.2%) or high (73, 7.3%) dosage, wrong drug selection (109, 10.8%), unreasonable off-label use (49, 4.9%), incorrect administration timing (16, 1.6%), and contraindication due to other medications (27, 2.7%). Several factors (e.g., age, weight, kidney function, anemia, and bleeding history) were associated with an increased risk of inappropriate edoxaban therapy, whereas factors associated with cardiovascular specialties (e.g., hospitalized in cardiovascular department and dronedarone or amiodarone use) decreased this risk. Conclusion: In this real-world study, 45.4% of patients received an inappropriate treatment with edoxaban. Multiple clinical characteristics can help identify patients who should receive edoxaban. Further development and implantation of educational activities and management strategies are needed to ensure the correct use of edoxaban.

Artificial intelligence (AI) will impact many aspects of clinical pharmacology including drug discovery and development, clinical trials, personalised medicine, pharmacogenomics, pharmacovigilance and clinical toxicology. The rapid progress of AI in healthcare means clinical pharmacologists should have an understanding of AI and its implementation into clinical practice. As with any new therapy or health technology, it is imperative that AI tools are subject to robust and stringent evaluation to ensure that they enhance clinical practice in a safe and equitable manner. This review serves as an introduction to AI for the clinical pharmacologist, highlighting current applications, aspects of model development and issues surrounding evaluation and deployment. The aim of this article is to empower clinical pharmacologists to embrace and lead on the safe and effective use of AI within healthcare.

Aim: The influence of human factors on safety in healthcare settings is well established, with targeted interventions reducing risk and enhancing team performance. In experimental and early phase clinical research participant safety is paramount and safeguarded by guidelines, protocolised care and staff training, however the real-world interaction and implementation of these risk-mitigating measures has never been subjected to formal system-based assessment. Methods: Independent structured observations, systematic review of study documents, and interviews and focus groups were used to collate data on three key tasks undertaken in a Clinical Research Facilty (CRF) during a SARS CoV-2 controlled human infection model (CHIM) study. The Systems Engineering Initiative for Patient Safety (SEIPS) was employed to analyse and categorise findings, and develop recommendations for safety interventions. Results: High levels of team functioning and a clear focus on participant safety were evident throughout the study. Despite this, latent risks in both study-specific and CRF work systems were identified in all four SEIPS domains (people, environment, tasks and tools). 14 actionable recommendations were generated collaboratively. These included inter-organisation and inter-study standardisation, optimised checklists for safety critical tasks, and use of simulation for team training and exploration of work systems. Conclusion: This pioneering application of human factors techniques to analyse work systems during the conduct of research in a CRF revealed risks unidentified by routine review and appraisal, and despite international guideline adherence. SEIPS may aid categorisation of system problems and the formulation of recommendations that reduce risk and mitigate potential harm applicable across a trials portfolio

Background Recombinant factor IX Fc fusion protein (rFIX-Fc) is an extended half-life (EHL) factor concentrate administered to haemophilia B patients. So far, a population pharmacokinetic (PK) model has only been published for patients ≥12 years of age. Aim Assess the predictive performance of the published rFIX-Fc population PK model for patients of all ages and develop a model that describes rFIX-Fc PK using real world data. Methods We collected prospective and retrospective data from patients with haemophilia B (FIX activity level ≤5 IU/dL) treated with rFIX-Fc and included in the OPTI-CLOT TARGET study (NTR7523) or United Kingdom (UK)-EHL Outcome Registry (NCT02938156). Predictive performance was assessed by comparing predicted with observed FIX activity levels. A novel population PK model was constructed using nonlinear mixed-effects modelling. Results Real world data was obtained from 37 patients (median age: 16 years, range 2-71) of whom 14 were <12 years of age. Observed FIX activity levels were significantly higher than levels predicted using the published model, with a median prediction error (PE) of -48.8%. The novel model showed a lower median PE (3.4%) and better described rFIX-Fc PK, especially for children <12 years of age. In the novel model, an increase in age was correlated with a decrease in clearance (p<0.01). Conclusion The published population PK model significantly underpredicted FIX activity levels. The novel model better describes rFIX-Fc PK, especially for children <12 years of age. This study underlines the necessity to strive for representative population PK models, thereby avoiding extrapolation outside the studied population.

Aim The prevalence of undocumented medical treatments among children is a significant issue, as well as many EU countries lack access to newly developed children friendly medicines. Consequently, there is a pressing need for supplementary resources that can facilitate informed decision-making regarding children’s medication. We therefore aim to describe the process of establishing a children’s Drug and Therapeutics Committee (cDTC), as well as the preparing and implementation of recommendations for children in the Capital region of Denmark Method Following the guidelines outlined by the World Health Organization a cDTC was established. Recommendations for pediatric medication practice were constructed from assessments of medication use patterns among children in the Capital Region between 2019 and 2021. The recommendations were meticulously crafted based on evaluation of the current marketing authorization landscape and existing best available evidence. Results In 2019, the Capital Region established the first cDTC supported by expert councils and an editorial board. A total of 2.429 purchase item numbers covering 1.222.846 defined daily doses and 592.088 purchased packages covering 10.200.000 defined daily doses were identified in the secondary and primary sectors, respectively. Three comprehensive lists covering recommendations for newborns and children were published between 2021 and 2020 totaling 331 recommended pharmaceutical products. The recommendations primarily intended for use in the secondary healthcare sector were implemented through the revision of 38 pediatric- and 6 neonatal product ranges throughout Capital region. Conclusion Recommendation lists for children governed by a cDTC provide a rational auxiliary tool that can be immediately implemented in the clinic.

Introduction: A key reason for the failure of anti-tuberculosis (TB) treatment is missed doses (instances where medication is not taken). Adverse drug reactions (ADRs) are one cause of missed doses, but the global evidence for this, their relative contribution to missed doses versus other causes, the patterns of missed doses due to ADRs, and the specific ADRs associated with missed doses have not been appraised. We sought to address these questions through a scoping review. Methods: MEDLINE, Embase and Web of Science were searched on 3 November 2021 using terms around active TB, missed doses and treatment challenges. Studies reporting both ADR and missed dose data were examined. (PROSPERO: CRD42022295209). Results: Searches identified 108 eligible studies. 88/108 (81%) studies associated ADRs with an increase in missed doses. 33/61 (54%) studies documenting the reasons for missed doses gave ADRs as a primary reason. No studies examined patterns of missed doses due to ADRs. 41/108 (38%) studies examined associations between 68 types of ADR (across 15 organ systems) and missed doses. Nuance around ADR-missed doses relations regarding drug susceptibility testing profile and missed dose originator was found. Conclusions: There is extensive evidence that ADRs are a key driver for missed doses of anti-TB treatment. Some papers examined specific ADRs, none evaluated the patterns of missed doses due to ADRs, demonstrating a knowledge deficit. Knowing why doses both are and are not missed due to ADRs is essential in providing targeted interventions to improve treatment outcomes.

Aim To evaluate the performance of ChatGPT in key areas of clinical pharmacy practice, including prescription review, patient medication education, adverse drug reaction (ADR) recognition, ADR causality assessment, and drug counseling. Methods Quantitative and qualitative analyses were conducted to assess the accuracy and quality of ChatGPT in comparison to those of the clinical pharmacist. Results The results indicate that ChatGPT is excellent in drug counseling and weak in prescription review, patient medication education, ADR recognition, and ADR causality. Conclusions While ChatGPT holds promise in clinical pharmacy practice as a supplementary tool, the ability of ChatGPT to handle complex problems needs further improvement and refinement.

Aims Information on breastfeeding and the safety of biologics in infants is lacking due to difficulties in case collection. We evaluated a method for determining the concentration of biologics in breast milk using a dry filter method that can simplify the collection, storage, and transport of breast milk. Methods To generate dried filter paper (DFP) samples, approximately 30 L of breast milk was placed onto a Whatman 903 card and punched out. After extraction, the supernatant was measured using an enzyme-linked immunosorbent assay. Three concentrations of each drug were prepared in liquid breast milk (LBM) and DFP samples for stability testing, which confirmed that samples were stable up to 28 days after storage at 2–8 ºC or -20 ºC for LBM and at 25±5 ºC for DFP. LBM and DFP samples were provided by lactating mothers using biologics during lactation. Drug concentrations were compared. Results Breast milk was provided by 12 lactating mothers (tocilizumab, n=4; abatacept, n=2; etanercept, n=1; golimumab, n=1; sarilumab, n=1; and belimumab, n=3). The accuracy and precision of measurements for the six drugs were within acceptable limits. After 28 days, concentrations remained at more than 90% under all storage conditions. The quantitative values of the provided LBM and DFP samples were similar. The maximum relative infant dose ranged from 0.09% to 1.12%, which was an acceptable range. Conclusion A method for determining the concentration of biologics using DFP is expected to help improve pharmacotherapy for lactating women.

The potential of using chatGPT in pharmacometrics was explored in this study, with a focus on developing a pharmacokinetic (PK) model for standard half-life factor VIII. Our results demonstrated that chatGPT can be utilized to accurately obtain typical PK parameters from literature, generate a population PK model in R, and develop an interactive Shiny application to visualize the results. ChatGPT’s language generation capabilities enabled the development of R codes with minimal programming knowledge and helped identify and fix errors in the code. While chatGPT presents several advantages, such as its ability to streamline the development process, its use in pharmacometrics also has limitations and challenges, including the accuracy and reliability of AI-generated data, the lack of transparency and interpretability of AI. Overall, our study demonstrates the potential of using chatGPT in pharmacometrics, but researchers must carefully evaluate its use for their specific needs.

Objective Methotrexate (MTX) is the cornerstone in the treatment of rheumatoid arthritis (RA) patients. However, adherence to MTX therapy is not optimal, and instruments to assess medication non-adherence are warranted. To date there is no consensus on the best method to determine adherence to MTX. The aim of this study was to assess the correlation between adherence assessed with a Medication Event Monitoring System (MEMS) versus pill count, MTX-polyglutamate (PG) concentration and Compliance-Questionnaire-Rheumatology (CQR) in patients with established RA. Second, the correlations between these methods and the Disease Activity Scores of 28 joints (DAS28) were examined. Methods Adult RA patients currently treated with MTX were included. Multivariable linear and logistic regression were used, with adherence assessed with MEMS as dependent variable versus pill count, MTX-PG concentrations, CQR as independent variables, and DAS28 versus each of the four adherence measurements. Covariates were included, such as comedication, age and use of corticosteroids. Results 190 consecutive RA patients were included. Pill count was correlated with adherence assessed with MEMS (linear regression, β = .690, p = <.001), whereas CQR and MTX-PGs were not. Logistic regression confirmed the correlation between dichotomized adherence and pill count only (β = 5.64, p= <.001). No other correlations were found, neither for all adherence outcomes and DAS28. Conclusion Measuring adherence with MEMS is correlated with pill count, whereas other methods were not correlated with MEMS, nor with DAS28. Pill count can be used to estimate adherence to MTX therapy, in case MEMS is not achievable.

Tamoxifen is the most used hormonal therapy for estrogen receptor positive breast cancer. CYP2D6 is the main enzyme in the metabolic pathway of tamoxifen to endoxifen. Variations in endoxifen plasma concentrations are associated with CYP2D6 polymorphisms. This study aimed to determine the association between the CYP2D6 polymorphisms and endoxifen plasma concentrations in a cohort of Zimbabwean breast cancer patients (n = 40). TaqMan genotyping and copy number assays were done to determine CYP2D6 genotypes. Tamoxifen and metabolites were quantitated using LC-MS/MS. The population had high frequencies of the CYP2D6 reduced function alleles, *17 (15%) and *29 (18%). The median endoxifen concentration was 4.78 ng/ml and 55% of the patients, mostly intermediate metabolizers were below the endoxifen therapeutic threshold 5.97 ng/ml. The CYP2D6 phenotypes and activity scores were significantly associated with endoxifen plasma concentrations (p = 0.0151) and with endoxifen to N-desmethyl tamoxifen ratios (p = 0.0006).

Aim: This study was conducted to develop a population pharmacokinetic (PK) model of methotrexate in Korean patients with hematologic malignancy, identify factors affecting methotrexate PK, and propose optimal dosage regimen for the Korean population. Methods: Data were retrospectively collected from 188 patients with acute leukemia or non-Hodgkin’s lymphoma who were admitted to Severance Hospital for the period from 2005 to 2015. Using demographic factors and laboratory results as potential covariates for PK parameters, model development was performed using NONMEM and optimal dosing regimens were developed using the final PK model. Results: A two-compartment model incorporating body weight via allometry best described the data, yielding typical parameter values of 25.99L for central volume of distribution (V_1), 18.76L for peripheral volume of distribution (V_2), 12.9L/h for clearance (CL) and 0.646L/h for inter-compartmental clearance. Covariate analyses showed that, at the weight of 50kg, CL decreased by 0.11 L/h for each one-year increase in age above 14 years old and decreased to 0.8-fold when serum creatinine level doubled, indicating the importance of age-specific dose individualization in methotrexate treatment. Volume of distribution at steady state derived from PK parameters (=V_1+V_2) was 0.90L/kg, which was similar to those in the Western or Chinese population. Optimal doses simulated from the final model successfully produced the PK measures close to the target chosen. Conclusion: The population PK model and optimal dosage regimens developed in this study can be used as a basis to achieve precision dosing in Korean patients with hematologic malignancy.

Purpose Chemodenervation with botulinum neurotoxin type A (BoNTA) is the preferred method for focal spasticity management among various treatment options. While BoNTA injection is considered safe, its widespread use and increasing evidence raise safety concerns. Case In this paper, we present a patient with central pontine myelinolysis, a rare disease, who developed Acute Respiratory Distress Syndrome (ARDS) on the third day after BoNTA application to the spastic gastrocnemius muscle group and required intubation in the intensive care unit due to this complication. Conclusion To our knowledge, this is the first case reported in the literature to develop an acute pulmonary complication after BoNTA injection into spastic lower extremity muscles.