According to current US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidance documents, physiologically based pharmacokinetic (PBPK) modeling is a powerful tool to explore and quantitatively predict drug‐drug interactions (DDIs) and may offer an alternative to dedicated clinical trials. This study provides whole‐body PBPK models of rifampicin, itraconazole, clarithromycin, midazolam, alfentanil, and digoxin within the Open Systems Pharmacology (OSP) Suite. All models were built independently, coupled using reported interaction parameters, and mutually evaluated to verify their predictive performance by simulating published clinical DDI studies. In total, 112 studies were used for model development and 57 studies for DDI prediction. 93% of the predicted area under the plasma concentration‐time curve (AUC) ratios and 94% of the peak plasma concentration (Cmax) ratios are within twofold of the observed values. This study lays a cornerstone for the qualification of the OSP platform with regard to reliable PBPK predictions of enzyme‐mediated and transporter‐mediated DDIs during model‐informed drug development. All presented models are provided open‐source and transparently documented.
The proposed semiphysiological modelling approach generated a mechanistic description of the complex DDI occurring at major CYP3A expression sites and thus may serve as a powerful tool to maximise information acquired from clinical DDI studies. The model has been shown to draw precise and accurate predictions. Therefore, simulations based on this kind of models may be used for various clinical scenarios to improve pharmacotherapy.
Background. Palliative care (PC) infrastructure has developed differently around the globe. Whereas some institutions consider the palliative care unit (PCU) a valuable component, others report that the sole provision of a stateof-the art palliative care consultation service (PCCS) suffices to adequately care for the severely ill and dying.Objective. To aid institutional planning, this study aimed at gathering patient data to distinguish assignments of a concomitantly run PCU and PCCS at a large hospital and academic medical center.Methods. Demographics, Eastern Cooperative Oncology Group performance status, symptom/problem burden, discharge modality, and team satisfaction with care for all 601 PCU and 851 PCCS patients treated in 2009 and 2010 were retrospectively analyzed.Results. Patients admitted to the PCU versus those con-
Adequate linezolid blood concentrations have been shown to be associated with an improved clinical outcome. Our goal was to assess new predictors of inadequate linezolid concentrations often observed in critically ill patients. Fifty-two critically ill patients with severe infections receiving standard dosing of linezolid participated in this prospective observational study. Serum samples (median, 32 per patient) were taken on four consecutive days, and total linezolid concentrations were quantified. Covariates influencing linezolid pharmacokinetics were identified by multivariate analysis and a population pharmacokinetic model. Target attainment (area under the concentration-time curve over 12 h [AUC 12 ]/MIC ratio of >50; MIC ؍ 2 mg/liter) was calculated for both the study patients and a simulated independent patient group (n ؍ 67,000). Target attainment was observed for only 36% of the population on both days 1 and 4. Independent covariates related to significant decreases of linezolid concentrations included higher weight, creatinine clearance rates, and fibrinogen and antithrombin concentrations, lower concentrations of lactate, and the presence of acute respiratory distress syndrome (ARDS). Linezolid clearance was increased in ARDS patients (by 82%) and in patients with elevated fibrinogen or decreased lactate concentrations. In simulated patients, most covariates, including fibrinogen and lactate concentrations and weight, showed quantitatively minor effects on target attainment (difference of <9% between the first and fourth quartiles of the respective parameters). In contrast, the presence of ARDS had the strongest influence, with only <6% of simulated patients reaching this target. In conclusion, the presence of ARDS was identified as a new and strong predictor of insufficient linezolid concentrations, which might cause treatment failure. Insufficient concentrations might also be a major problem in patients with combined alterations of other covariate parameters. (This study has been registered at ClinicalTrials.gov under registration number NCT01793012.)
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