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- Khan, David D., et al.
(author)
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A mechanism-based pharmacokinetic/pharmacodynamic model allows prediction of antibiotic killing from MIC values for WT and mutants
- 2015
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In: Journal of Antimicrobial Chemotherapy. - : Oxford University Press (OUP). - 0305-7453 .- 1460-2091. ; 70:11, s. 3051-3060
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Journal article (peer-reviewed)abstract
- Objectives: In silico pharmacokinetic/pharmacodynamic (PK/PD) models can be developed based on data from in vitro time-kill experiments and can provide valuable information to guide dosing of antibiotics. The aim was to develop a mechanism-based in silico model that can describe in vitro time-kill experiments of Escherichia coli MG1655 WT and six isogenic mutants exposed to ciprofloxacin and to identify relationships that may be used to simplify future characterizations in a similar setting. Methods: In this study, we developed a mechanism-based PK/PD model describing killing kinetics for E. coli following exposure to ciprofloxacin. WT and six well-characterized mutants, with one to four clinically relevant resistance mutations each, were exposed to a wide range of static ciprofloxacin concentrations. Results: The developed model includes susceptible growing bacteria, less susceptible (pre-existing resistant) growing bacteria, non-susceptible non-growing bacteria and non-colony-forming non-growing bacteria. The non-colony-forming state was likely due to formation of filaments and was needed to describe data close to the MIC. A common model structure with different potency for bacterial killing (EC50) for each strain successfully characterized the time-kill curves for both WT and the six E. coli mutants. Conclusions: The model-derived mutant-specific EC50 estimates were highly correlated (r(2) = 0.99) with the experimentally determined MICs, implying that the in vitro time-kill profile of a mutant strain is reasonably well predictable by the MIC alone based on the model.
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- Khan, David, et al.
(author)
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Predicting mutant selection in competition experiments with ciprofloxacin-exposed Escherichia coli
- 2018
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In: International Journal of Antimicrobial Agents. - : Elsevier BV. - 0924-8579 .- 1872-7913. ; 51:3, s. 399-406
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Journal article (peer-reviewed)abstract
- Predicting competition between antibiotic-susceptible wild-type (WT) and less susceptible mutant (MT) bacteria is valuable for understanding how drug concentrations influence the emergence of resistance. Pharmacokinetic/pharmacodynamic (PK/PD) models predicting the rate and extent of takeover of resistant bacteria during different antibiotic pressures can thus be a valuable tool in improving treatment regimens. The aim of this study was to evaluate a previously developed mechanism-based PK/PD model for its ability to predict in vitro mixed-population experiments with competition between Escherichia coli (E. coli) WT and three well-defined E. coli resistant MTs when exposed to ciprofloxacin. Model predictions for each bacterial strain and ciprofloxacin concentration were made for in vitro static and dynamic time–kill experiments measuring CFU (colony forming units)/mL up to 24 h with concentrations close to or below the minimum inhibitory concentration (MIC), as well as for serial passage experiments with concentrations well below the MIC measuring ratios between the two strains with flow cytometry. The model was found to reasonably well predict the initial bacterial growth and killing of most static and dynamic time–kill competition experiments without need for parameter re-estimation. With parameter re-estimation of growth rates, an adequate fit was also obtained for the 6-day serial passage competition experiments. No bacterial interaction in growth was observed. This study demonstrates the predictive capacity of a PK/PD model and further supports the application of PK/PD modelling for prediction of bacterial kill in different settings, including resistance selection.
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- Nielsen, Elisabet I., 1973-, et al.
(author)
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Can a pharmacokinetic/pharmacodynamic (PKPD) model be predictive across bacterial densities and strains? : External evaluation of a PKPD model describing longitudinal in vitro data
- 2017
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In: Journal of Antimicrobial Chemotherapy. - : OXFORD UNIV PRESS. - 0305-7453 .- 1460-2091. ; 72:11, s. 3108-3116
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Journal article (peer-reviewed)abstract
- Background: Pharmacokinetic/pharmacodynamic (PKPD) models developed based on data from in vitro time-kill experiments have been suggested to contribute to more efficient drug development programmes and better dosing strategies for antibiotics. However, for satisfactory predictions such models would have to show good extrapolation properties. Objectives: To evaluate if a previously described mechanism-based PKPD model was able also to predict drug efficacy for higher bacterial densities and across bacterial strains. Methods: A PKPD model describing the efficacy of ciprofloxacin on Escherichia coli was evaluated. The predictive performance of the model was evaluated across several experimental conditions with respect to: (i) bacterial start inoculum ranging from the standard of similar to 10(6) cfu/mL up to late stationary-phase cultures; and (ii) efficacy for seven additional strains (three laboratory and four clinical strains), not included during the model development process, based only on information regarding their MIC. Model predictions were performed according to the intended experimental protocol and later compared with observed bacterial counts. Results: The mechanism-based PKPD model structure developed based on data from standard start inoculum experiments was able to accurately describe the inoculum effect. The model successfully predicted the time course of drug efficacy for additional laboratory and clinical strains based on only the MIC values. The model structure was further developed to better describe the stationary phase data. Conclusions: This study supports the use of mechanism-based PKPD models based on preclinical data for predictions of untested scenarios.
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| 8. |
- Nielsen, Sara, et al.
(author)
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Effects of autism spectrum disorders on outcome in teenage-onset anorexia nervosa evaluated by the Morgan-Russell outcome assessment schedule: a controlled community-based study
- 2015
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In: Molecular Autism. - : Springer Science and Business Media LLC. - 2040-2392. ; 6:14
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Journal article (peer-reviewed)abstract
- Background: The purpose of the study was to evaluate time trends and effects of co-existing autism spectrum disorders (ASD) on outcome in an ongoing long-term follow-up study of anorexia nervosa (AN). Methods: The Morgan-Russell Outcome Assessment Schedule (MROAS) was used at 6-, 10- and 18-year follow-up of a representative sample of 51 individuals with teenage-onset AN and a matched group of 51 healthy comparison cases. The full multinomial distribution of responses for the full scale and each of the subscales was evaluated using exact nonparametric statistical methods. The impact of diagnostic stability of ASD on outcome in AN was evaluated in a dose–response model. Results: There were no deaths in either group. Food intake and menstrual pattern were initially poor in the AN group but normalised over time. MROAS ‘mental state’ was much poorer in the AN group and did not improve over time. The psychosexual MROAS domains ‘attitudes’ and ‘aims’ showed persistent problems in the AN group. In the MROAS socioeconomic domain, the subscales ‘personal contacts’, ‘social activities’ and ‘employment record’ all showed highly significant between-group differences at all three follow-ups. A statistically significant negative dose–response relationship was found between a stable diagnosis of ASD over time and the results on the subscales ‘mental state’, ‘psychosexual state’ and ‘socio-economic state’. Conclusions: Outcome of teenage-onset AN is favourable with respect to mortality and persisting eating disorder, but serious problems remain in the domains ‘mental state’, ‘psychosexual function’ and ‘socioeconomic state’. Outcome is considerably worse if ASD is present. Treatment programmes for AN need to be modified so as to accommodate co-existing ASD.
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| 10. |
- Abrantes, João A., et al.
(author)
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Bayesian Forecasting Utilizing Bleeding Information to Support Dose Individualization of Factor VIII
- 2019
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In: CPT. - : Wiley. - 2163-8306. ; 8:12, s. 894-903
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Journal article (peer-reviewed)abstract
- Bayesian forecasting for dose individualization of prophylactic factor VIII replacement therapy using pharmacokinetic samples is challenged by large interindividual variability in the bleeding risk. A pharmacokinetic‐repeated time‐to‐event model‐based forecasting approach was developed to contrast the ability to predict the future occurrence of bleeds based on individual (i) pharmacokinetic, (ii) bleeding, and (iii) pharmacokinetic, bleeding and covariate information using observed data from the Long‐Term Efficacy Open‐Label Program in Severe Hemophilia A Disease (LEOPOLD) clinical trials (172 severe hemophilia A patients taking prophylactic treatment). The predictive performance assessed by the area under receiver operating characteristic (ROC) curves was 0.67 (95% confidence interval (CI), 0.65–0.69), 0.78 (95% CI, 0.76–0.80), and 0.79 (95% CI, 0.77–0.81) for patients ≥ 12 years when using pharmacokinetics, bleeds, and all data, respectively, suggesting that individual bleed information adds value to the optimization of prophylactic dosing regimens in severe hemophilia A. Further steps to optimize the proposed tool for factor VIII dose adaptation in the clinic are required.
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