Browsing by Author "Certara USA, Inc."

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    Factors affecting the electrocardiographic QT interval in malaria: A systematic review and meta-analysis of individual patient data
    (2020-03-01) Xin Hui S. Chan; Yan Naung Win; Ilsa L. Haeusler; Jireh Y. Tan; Shanghavie Loganathan; Sompob Saralamba; Shu Kiat S. Chan; Elizabeth A. Ashley; Karen I. Barnes; Rita Baiden; Peter U. Bassi; Abdoulaye Djimde; Grant Dorsey; Stephan Duparc; Borimas Hanboonkunupakarn; Feiko O. Ter Kuile; Marcus V.G. Lacerda; Amit Nasa; François H. Nosten; Cyprian O. Onyeji; Sasithon Pukrittayakamee; André M. Siqueira; Joel Tarning; Walter R.J. Taylor; Giovanni Valentini; Michèle van Vugt; David Wesche; Nicholas P.J. Day; Christopher L.H. Huang; Josep Brugada; Ric N. Price; Nicholas J. White; Certara USA, Inc.; Singapore Army; University of Cambridge; Fundacao Oswaldo Cruz; Menzies School of Health Research; University of California, San Francisco; UCL; Liverpool School of Tropical Medicine; Christ Church; Mahidol University; University of Abuja; Obafemi Awolowo University; Nuffield Department of Clinical Medicine; Universitat de Barcelona; Amsterdam UMC - University of Amsterdam; University of Cape Town; Medicines for Malaria Venture; Sun Pharmaceutical Industries Limited; R&D Department; University of Sciences Techniques and Technologies of Bamako; Health and Diseases Control Unit; Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit (LOMWRU); WorldWide Antimalarial Resistance Network; Royal Institute of Thailand; INDEPTH Network
    BACKGROUND: Electrocardiographic QT interval prolongation is the most widely used risk marker for ventricular arrhythmia potential and thus an important component of drug cardiotoxicity assessments. Several antimalarial medicines are associated with QT interval prolongation. However, interpretation of electrocardiographic changes is confounded by the coincidence of peak antimalarial drug concentrations with recovery from malaria. We therefore reviewed all available data to characterise the effects of malaria disease and demographic factors on the QT interval in order to improve assessment of electrocardiographic changes in the treatment and prevention of malaria. METHODS AND FINDINGS: We conducted a systematic review and meta-analysis of individual patient data. We searched clinical bibliographic databases (last on August 21, 2017) for studies of the quinoline and structurally related antimalarials for malaria-related indications in human participants in which electrocardiograms were systematically recorded. Unpublished studies were identified by the World Health Organization (WHO) Evidence Review Group (ERG) on the Cardiotoxicity of Antimalarials. Risk of bias was assessed using the Pharmacoepidemiological Research on Outcomes of Therapeutics by a European Consortium (PROTECT) checklist for adverse drug events. Bayesian hierarchical multivariable regression with generalised additive models was used to investigate the effects of malaria and demographic factors on the pretreatment QT interval. The meta-analysis included 10,452 individuals (9,778 malaria patients, including 343 with severe disease, and 674 healthy participants) from 43 studies. 7,170 (68.6%) had fever (body temperature ≥ 37.5°C), and none developed ventricular arrhythmia after antimalarial treatment. Compared to healthy participants, patients with uncomplicated falciparum malaria had shorter QT intervals (-61.77 milliseconds; 95% credible interval [CI]: -80.71 to -42.83) and increased sensitivity of the QT interval to heart rate changes. These effects were greater in severe malaria (-110.89 milliseconds; 95% CI: -140.38 to -81.25). Body temperature was associated independently with clinically significant QT shortening of 2.80 milliseconds (95% CI: -3.17 to -2.42) per 1°C increase. Study limitations include that it was not possible to assess the effect of other factors that may affect the QT interval but are not consistently collected in malaria clinical trials. CONCLUSIONS: Adjustment for malaria and fever-recovery-related QT lengthening is necessary to avoid misattributing malaria-disease-related QT changes to antimalarial drug effects. This would improve risk assessments of antimalarial-related cardiotoxicity in clinical research and practice. Similar adjustments may be indicated for other febrile illnesses for which QT-interval-prolonging medications are important therapeutic options.
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    Prediction of olanzapine exposure in individual patients using physiologically based pharmacokinetic modelling and simulation
    (2018-03-01) Thomas M. Polasek; Geoffrey T. Tucker; Michael J. Sorich; Michael D. Wiese; Titus Mohan; Amin Rostami-Hodjegan; Porntipa Korprasertthaworn; Vidya Perera; Andrew Rowland; Certara USA, Inc.; Certara, United Kingdom; University of South Australia; Flinders Medical Centre; Flinders University; Mahidol University; University of Manchester; Bristol-Myers Squibb; University of Sheffield
    © 2017 The British Pharmacological Society Aim: The aim of the present study was to predict olanzapine (OLZ) exposure in individual patients using physiologically based pharmacokinetic modelling and simulation (PBPK M&S). Methods: A ‘bottom-up’ PBPK model for OLZ was constructed in Simcyp® (V14.1) and validated against pharmacokinetic studies and data from therapeutic drug monitoring (TDM). The physiological, demographic and genetic attributes of the ‘healthy volunteer population’ file in Simcyp® were then individualized to create ‘virtual twins’ of 14 patients. The predicted systemic exposure of OLZ in virtual twins was compared with measured concentration in corresponding patients. Predicted exposures were used to calculate a hypothetical decrease in exposure variability after OLZ dose adjustment. Results: The pharmacokinetic parameters of OLZ from single-dose studies were accurately predicted in healthy Caucasians [mean-fold errors (MFEs) ranged from 0.68 to 1.14], healthy Chinese (MFEs 0.82 to 1.18) and geriatric Caucasians (MFEs 0.55 to 1.30). Cumulative frequency plots of trough OLZ concentration were comparable between the virtual population and patients in a TDM database. After creating virtual twins in Simcyp®, the R2 values for predicted vs. observed trough OLZ concentrations were 0.833 for the full cohort of 14 patients and 0.884 for the 7 patients who had additional cytochrome P450 2C8 genotyping. The variability in OLZ exposure following hypothetical dose adjustment guided by PBPK M&S was twofold lower compared with a fixed-dose regimen – coefficient of variation values were 0.18 and 0.37, respectively. Conclusions: Olanzapine exposure in individual patients was predicted using PBPK M&S. Repurposing of available PBPK M&S platforms is an option for model-informed precision dosing and requires further study to examine clinical potential.