Physiologically-based pharmacokinetic modelling in sepsis; a tool to elucidate how pathophysiology affects meropenem pharmacokinetics: A PBPK model of meropenem in sepsis.

Applying physiologically-based pharmacokinetic (PBPK) modelling in sepsis could help to better understand how PK changes are influenced by drug- and patient-related factors. We aimed to elucidate the influence of sepsis pathophysiology on the PK of meropenem by applying PBPK modelling. A whole-body meropenem PBPK model was developed and evaluated in healthy individuals, and renally impaired non-septic patients. Sepsis-induced physiological changes in body composition, organ blood flow, kidney function, albumin, and haematocrit were implemented according to a previously proposed PBPK sepsis model. Model performance was evaluated, and a local sensitivity analysis was conducted. The model-predicted PK metrics (AUC, Cmax, CL, Vss) were within 1.33-fold-error margin of published data for 87.5% of the simulated profiles in healthy individuals. In sepsis, the model provided good predictions for literature-digitised average plasma and tissue exposure data, where the model-predicted AUC was within 1.33-fold-error margin for 9 out 11 simulated study profiles. Furthermore, the model was applied to individual plasma concentration data from 52 septic patients, where the model-predicted AUC, Cmax, and CL had a fold-error ratio range of 0.98-1.12, with alignment of the predicted and observed variability. For Vss, the fold-error ratio was 0.81, and the model underpredicted the population variability. CL was sensitive to renal plasma clearance, and kidney volume, whereas Vss was sensitive to the unbound fraction, organ volume fraction of the interstitial compartment, and the organ volume. These findings may be extended to more diverse drug types and support a more mechanistic understanding of the effect of sepsis on drug exposure.

Predicting cytokine kinetics during sepsis; a modelling framework from a porcine sepsis model with live Escherichia coli.

BACKGROUND: Describing the kinetics of cytokines involved as biomarkers of sepsis progression could help to optimise interventions in septic patients. This work aimed to quantitively characterise the cytokine kinetics upon exposure to live E. coli by developing an in silico model, and to explore predicted cytokine kinetics at different bacterial exposure scenarios. METHODS: Data from published in vivo studies using a porcine sepsis model were analysed. A model describing the time courses of bacterial dynamics, endotoxin (ETX) release, and the kinetics of TNF and IL-6 was developed. The model structure was extended from a published model that quantifies the ETX-cytokines relationship. An external model evaluation was conducted by applying the model to literature data. Model simulations were performed to explore the sensitivity of the host response towards differences in the input rate of bacteria, while keeping the total bacterial burden constant. RESULTS: The analysis included 645 observations from 30 animals. The blood bacterial count was well described by a one-compartment model with linear elimination. A scaling factor was estimated to quantify the ETX release by bacteria. The model successfully described the profiles of TNF, and IL-6 without a need to modify the ETX-cytokines model structure. The kinetics of TNF, and IL-6 in the external datasets were well predicted. According to the simulations, the ETX tolerance development results in that low initial input rates of bacteria trigger the lowest cytokine release. CONCLUSION: The model quantitively described and predicted the cytokine kinetics triggered by E. coli exposure. The host response was found to be sensitive to the bacterial exposure rate given the same total bacterial burden.

Clinical Pharmacist-Provided Services In Iron-Overloaded Beta-Thalassaemia Major Children: A New Insight Into Patient Care.

Iron-overloaded ß-thalassaemia major (BTM) children have high risk of delayed sexual/physical maturation, liver/heart diseases and reduced life expectancy. The lifelong need to use iron chelators, their unpleasant administration, side effects and lack of awareness regarding iron overload risks all hamper BTM patient compliance to iron chelators. This study evaluated the impact of clinical pharmacist-provided services on the outcome of iron-overloaded BTM children. Forty-eight BTM children were randomly assigned to either control group, who received standard medical care, or intervention group, who received standard medical care plus clinical pharmacist-provided services. Services included detection of drug-related problems (DRPs) and their management, patient education regarding disease nature and iron chelators, as well as providing patient-tailored medication charts. After six months of study implementation, there was a highly significant difference between the control and intervention groups in serum ferritin (SF) (mean: 3871 versus 2362, µg/l, p = 0.0042), patient healthcare satisfaction (median: 24.47 versus 90.29, p < 0.0001) and quality of life (QoL) (median: 49.84 versus 63.51, p = 0.0049). The intervention group showed a decline from baseline to the end of study in DRPs (64-4), the number of non-compliant patients (24-3) and mean SF levels (3949-2362 µg/l, p < 0.0001). Clinical pharmacist-provided services can positively impact the outcome of BTM children.