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  • 1.
    Andersen, Maria Goul
    et al.
    Aarhus Univ Hosp, Dept Infect Dis, Aarhus, Denmark.
    Thorsted, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Storgaard, Merete
    Aarhus Univ Hosp, Dept Infect Dis, Aarhus, Denmark.
    Kristoffersson, Anders N.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena E
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Öbrink-Hansen, Kristina
    Aarhus Univ Hosp, Dept Infect Dis, Aarhus, Denmark.
    Population Pharmacokinetics of Piperacillin in Sepsis Patients: Should Alternative Dosing Strategies Be Considered?2018In: Antimicrobial Agents and Chemotherapy, ISSN 0066-4804, E-ISSN 1098-6596, Vol. 62, no 5, article id e02306Article in journal (Refereed)
    Abstract [en]

    Sufficient antibiotic dosing in septic patients is essential for reducing mortality. Piperacillin-tazobactam is often used for empirical treatment, but due to the pharmacokinetic (PK) variability seen in septic patients, optimal dosing may be a challenge. We determined the PK profile for piperacillin given at 4 g every 8 h in 22 septic patients admitted to a medical ward. Piperacillin concentrations were compared to the clinical breakpoint MIC for Pseudomonas aeruginosa (16 mg/liter), and the following PK/pharmacodynamic (PD) targets were evaluated: the percentage of the dosing interval that the free drug concentration is maintained above the MIC (fTMIC) of 50% and 100%. A two-compartment population PK model described the data well, with clearance being divided into renal and nonrenal components. The renal component was proportional to the estimated creatinine clearance (eCLCR) and constituted 74% of the total clearance in a typical individual (eCLCR, 83.9 ml/min). Patients with a high eCLCR (>130 ml/min) were at risk of subtherapeutic concentrations for the current regimen, with a 90% probability of target attainment being reached at MICs of 2.0 (50% fTMIC) and 0.125 mg/liter (100% fTMIC). Simulations of alternative dosing regimens and modes of administration showed that dose increment and prolonged infusion increased the chance of achieving predefined PK/PD targets. Alternative dosing strategies may therefore be needed to optimize piperacillin exposure in septic patients. (This study has been registered at ClinicalTrials.gov under identifier NCT02569086.)

  • 2.
    Brill, Margreke J. E.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Kristoffersson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Zhao, Chenyan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena E
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Semi-mechanistic pharmacokinetic-pharmacodynamic modelling of antibiotic drug combinations2018In: Clinical Microbiology and Infection, ISSN 1198-743X, E-ISSN 1469-0691, Vol. 24, no 7, p. 697-706Article, review/survey (Refereed)
    Abstract [en]

    Background: Deriving suitable dosing regimens for antibiotic combination therapy poses several challenges as the drug interaction can be highly complex, the traditional pharmacokinetic-pharmacodynamic (PKPD) index methodology cannot be applied straightforwardly, and exploring all possible dose combinations is unfeasible. Therefore, semi-mechanistic PKPD models developed based on in vitro single and combination experiments can be valuable to suggest suitable combination dosing regimens. Aims: To outline how the interaction between two antibiotics has been characterized in semi-mechanistic PKPD models. We also explain how such models can be applied to support dosing regimens and design future studies. Sources: PubMed search for published semi-mechanistic PKPD models of antibiotic drug combinations. Content: Thirteen publications were identified where ten had applied subpopulation synergy to characterize the combined effect, i.e. independent killing rates for each drug and bacterial subpopulation. We report the various types of interaction functions that have been used to describe the combined drug effects and that characterized potential deviations from additivity under the PKPD model. Simulations from the models had commonly been performed to compare single versus combined dosing regimens and/or to propose improved dosing regimens.

  • 3.
    Dickstein, Yaakov
    et al.
    Rambam Hlth Care Campus, Div Infect Dis, Haifa, Israel..
    Leibovici, Leonard
    Beilinson Med Ctr, Rabin Med Ctr, Dept Med E, Petah Tiqwa, Israel.;Tel Aviv Univ, Sackler Fac Med, Ramat Aviv, Israel..
    Yahav, Dafna
    Tel Aviv Univ, Sackler Fac Med, Ramat Aviv, Israel.;Beilinson Med Ctr, Rabin Med Ctr, Infect Dis Unit, Petah Tiqwa, Israel..
    Eliakim-Raz, Noa
    Tel Aviv Univ, Sackler Fac Med, Ramat Aviv, Israel.;Beilinson Med Ctr, Rabin Med Ctr, Infect Dis Unit, Petah Tiqwa, Israel..
    Daikos, George L.
    Univ Athens, Dept Med 1, Athens, Greece..
    Skiada, Anna
    Univ Athens, Dept Med 1, Athens, Greece..
    Antoniadou, Anastasia
    Univ Athens, Dept Med 4, Athens, Greece..
    Carmeli, Yehuda
    Tel Aviv Univ, Tel Aviv Sourasky Med Ctr, Div Epidemiol & Prevent Med, IL-69978 Tel Aviv, Israel..
    Nutman, Amir
    Tel Aviv Univ, Sackler Fac Med, Ramat Aviv, Israel.;Tel Aviv Univ, Tel Aviv Sourasky Med Ctr, Div Epidemiol & Prevent Med, IL-69978 Tel Aviv, Israel..
    Levi, Inbar
    Tel Aviv Univ, Tel Aviv Sourasky Med Ctr, Div Epidemiol & Prevent Med, IL-69978 Tel Aviv, Israel..
    Adler, Amos
    Tel Aviv Univ, Tel Aviv Sourasky Med Ctr, Microbiol Lab, IL-69978 Tel Aviv, Israel..
    Durante-Mangoni, Emanuele
    Univ Naples 2, Monaldi Hosp AORN Colli, Internal Med, Naples, Italy..
    Andini, Roberto
    Univ Naples 2, Monaldi Hosp AORN Colli, Internal Med, Naples, Italy..
    Cavezza, Giusi
    Univ Naples 2, Monaldi Hosp AORN Colli, Internal Med, Naples, Italy..
    Mouton, Johan W.
    Erasmus MC, Dept Med Microbiol & Infect Dis, Rotterdam, Netherlands.;Radboudumc, Dept Med Microbiol, Nijmegen, Netherlands..
    Wijma, Rixt A.
    Erasmus MC, Dept Med Microbiol & Infect Dis, Rotterdam, Netherlands..
    Theuretzbacher, Ursula
    Ctr Antiinfect Agents, Vienna, Austria..
    Friberg, Lena E.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Kristoffersson, Anders N.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Zusman, Oren
    Beilinson Med Ctr, Rabin Med Ctr, Dept Med E, Petah Tiqwa, Israel.;Tel Aviv Univ, Sackler Fac Med, Ramat Aviv, Israel..
    Koppel, Fidi
    Rambam Hlth Care Campus, Div Infect Dis, Haifa, Israel..
    Benattar, Yael Dishon
    Rambam Hlth Care Campus, Div Infect Dis, Haifa, Israel..
    Altunin, Sergey
    Technion Israel Inst Technol, Fac Med, Haifa, Israel..
    Paul, Mical
    Rambam Hlth Care Campus, Div Infect Dis, Haifa, Israel.;Technion Israel Inst Technol, Fac Med, Haifa, Israel..
    Multicentre open-label randomised controlled trial to compare colistin alone with colistin plus meropenem for the treatment of severe infections caused by carbapenem-resistant Gram-negative infections (AIDA): a study protocol2016In: BMJ Open, ISSN 2044-6055, E-ISSN 2044-6055, Vol. 6, no 4, article id e009956Article in journal (Refereed)
    Abstract [en]

    Introduction: The emergence of antibiotic-resistant bacteria has driven renewed interest in older antibacterials, including colistin. Previous studies have shown that colistin is less effective and more toxic than modern antibiotics. In vitro synergy studies and clinical observational studies suggest a benefit of combining colistin with a carbapenem. A randomised controlled study is necessary for clarification. Methods and analysis: This is a multicentre, investigator-initiated, open-label, randomised controlled superiority 1:1 study comparing colistin monotherapy with colistin-meropenem combination therapy for infections caused by carbapenem-resistant Gram-negative bacteria. The study is being conducted in 6 centres in 3 countries (Italy, Greece and Israel). We include patients with hospital-associated and ventilator-associated pneumonia, bloodstream infections and urosepsis. The primary outcome is treatment success at day 14, defined as survival, haemodynamic stability, stable or improved respiratory status for patients with pneumonia, microbiological cure for patients with bacteraemia and stability or improvement of the Sequential Organ Failure Assessment (SOFA) score. Secondary outcomes include 14-day and 28-day mortality as well as other clinical end points and safety outcomes. A sample size of 360 patients was calculated on the basis of an absolute improvement in clinical success of 15% with combination therapy. Outcomes will be assessed by intention to treat. Serum colistin samples are obtained from all patients to obtain population pharmacokinetic models. Microbiological sampling includes weekly surveillance samples with analysis of resistance mechanisms and synergy. An observational trial is evaluating patients who met eligibility requirements but were not randomised in order to assess generalisability of findings. Ethics and dissemination: The study was approved by ethics committees at each centre and informed consent will be obtained for all patients. The trial is being performed under the auspices of an independent data and safety monitoring committee and is included in a broad dissemination strategy regarding revival of old antibiotics.

  • 4.
    Khan, David D.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Kristoffersson, Anders N.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Lagerbäck, Pernilla
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Lustig, Ulrika
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Annerstedt, Charlotte
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Cars, Otto
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Andersson, Dan I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Hughes, Diarmaid
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena E.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    A PKPD model characterizing the combined effects of colistin and ciprofloxacin on MG1655 wild type and a clinical isolate of E. coliManuscript (preprint) (Other academic)
  • 5.
    Khan, David
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Lagerbäck, Pernilla
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Infectious Diseases.
    Malmberg, Christer
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Infectious Diseases.
    Kristoffersson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Gullberg, Erik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Cao, Sha
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Cars, Otto
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Infectious Diseases.
    Andersson, Dan I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Hughes, Diarmaid
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena E
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Predicting mutant selection in competition experiments with ciprofloxacin-exposed Escherichia coli2018In: International Journal of Antimicrobial Agents, ISSN 0924-8579, E-ISSN 1872-7913, Vol. 51, no 3, p. 399-406, article id S0924-8579(17)30392-8Article in journal (Refereed)
    Abstract [en]

    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.

  • 6.
    Kristoffersson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Study Design and Dose Regimen Evaluation of Antibiotics based on Pharmacokinetic and Pharmacodynamic Modelling2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Current excessive use and abuse of antibiotics has resulted in increasing bacterial resistance to common treatment options which is threatening to deprive us of a pillar of modern medicine. In this work methods to optimize the use of existing antibiotics and to help development of new antibiotics were developed and applied.

    Semi-mechanistic pharmacokinetic-pharmacodynamic (PKPD) models were developed to describe the time course of the dynamic effect and interaction of combinations of antibiotics. The models were applied to illustrate that colistin combined with a high dose of meropenem may overcome meropenem-resistant P. aeruginosa infections.

    The results from an in vivo dose finding study of meropenem was successfully predicted by the meropenem PKPD model in combination with a murine PK model, which supports model based dosage selection. However, the traditional PK/PD index based dose selection was predicted to have poor extrapolation properties from pre-clinical to clinical settings, and across patient populations.

    The precision of the model parameters, and hence the model predictions, is dependent on the experimental design. A limited study design is dictated by cost and, for in vivo studies, ethical reasons. In this work optimal design (OD) was demonstrated to be able to reduce the experimental effort in time-kill curve experiments and was utilized to suggest the experimental design for identification and estimation of an interaction between antibiotics.

    OD methods to handle inter occasion variability (IOV) in optimization of individual PK parameter estimates were proposed. The strategy was applied in the design of a sparse sampling schedule that aim to estimate individual exposures of colistin in a multi-centre clinical study. Plasma concentration samples from the first 100 patients have been analysed and indicate that the performance of the design is close to the predicted.

    The methods described in this thesis holds promise to facilitate the development of new antibiotics and to improve the use of existing antibiotics.

    List of papers
    1. Dynamic Interaction of Colistin and Meropenem on a Wild-type and a Resistant strain of Pseudomonas aeruginosa as Quantified in a PKPD-Model
    Open this publication in new window or tab >>Dynamic Interaction of Colistin and Meropenem on a Wild-type and a Resistant strain of Pseudomonas aeruginosa as Quantified in a PKPD-Model
    Show others...
    (English)Article in journal (Refereed) Submitted
    Keywords
    eer r Antibiotic resistance, Antibiotic therapy, Antimicrobial interactions, Pharmacodynamics, PK/PD, Modelling, Pseudomonas aeruginosa, Colistin, Combination treatment, Meropenem
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:uu:diva-264797 (URN)
    Available from: 2015-10-19 Created: 2015-10-19 Last updated: 2015-11-13
    2. Simulation-based evaluation of PK/PD indices for meropenem across patient groups and experimental designs
    Open this publication in new window or tab >>Simulation-based evaluation of PK/PD indices for meropenem across patient groups and experimental designs
    Show others...
    (English)In: Article in journal (Refereed) Submitted
    Keywords
    Antibiotic, Dose selection, Meropenem, Pseudomonas aeruginosa, Pharmacometric
    National Category
    Medical and Health Sciences
    Research subject
    Pharmaceutical Science
    Identifiers
    urn:nbn:se:uu:diva-264793 (URN)
    Available from: 2015-10-19 Created: 2015-10-19 Last updated: 2018-03-01
    3. Optimal design of ciprofloxacin in vitro time-kill experiments
    Open this publication in new window or tab >>Optimal design of ciprofloxacin in vitro time-kill experiments
    Show others...
    (English)Manuscript (preprint) (Other academic)
    Keywords
    Optimal design (OD), Time-kill curve, Antibiotic, Ciprofloxacin, PKPD-modeling
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:uu:diva-264794 (URN)
    Available from: 2015-10-19 Created: 2015-10-19 Last updated: 2015-11-13
    4. A PKPD model characterizing the combined effects of colistin and ciprofloxacin on MG1655 wild type and a clinical isolate of E. coli
    Open this publication in new window or tab >>A PKPD model characterizing the combined effects of colistin and ciprofloxacin on MG1655 wild type and a clinical isolate of E. coli
    Show others...
    (English)Manuscript (preprint) (Other academic)
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:uu:diva-264795 (URN)
    Available from: 2015-10-19 Created: 2015-10-19 Last updated: 2016-05-12
    5. Handling of Inter Occasion Variability (IOV) in Individual Optimal Design (OD) of a Colistin PK Sampling Schedule
    Open this publication in new window or tab >>Handling of Inter Occasion Variability (IOV) in Individual Optimal Design (OD) of a Colistin PK Sampling Schedule
    2013 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 40, no S1, p. S123-S124Article in journal, Meeting abstract (Other academic) Published
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:uu:diva-219423 (URN)000330126000132 ()
    Conference
    The American Conference on Pharmacometrics, May 12-15, 2013, Fort Lauderdale, USA
    Available from: 2014-03-09 Created: 2014-02-28 Last updated: 2017-12-05Bibliographically approved
    6. A sparse sampling design, with interim evaluation, for estimation of individual colistin pharmacokinetics
    Open this publication in new window or tab >>A sparse sampling design, with interim evaluation, for estimation of individual colistin pharmacokinetics
    (English)Manuscript (preprint) (Other academic)
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:uu:diva-264796 (URN)
    Available from: 2015-10-19 Created: 2015-10-19 Last updated: 2015-11-13
  • 7.
    Kristoffersson, Anders
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    David-Pierson, Pascale
    Parrott, Neil J
    Kuhlmann, Olaf
    Lave, Thierry
    Friberg, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nielsen, Elisabet
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Simulation-Based Evaluation of PK/PD Indices for Meropenem Across Patient Groups and Experimental Designs2016In: Pharmaceutical research, ISSN 0724-8741, E-ISSN 1573-904X, Vol. 33, no 5, p. 1115-1125Article in journal (Refereed)
    Abstract [en]

    PURPOSE: Antibiotic dose predictions based on PK/PD indices rely on that the index type and magnitude is insensitive to the pharmacokinetics (PK), the dosing regimen, and bacterial susceptibility. In this work we perform simulations to challenge these assumptions for meropenem and Pseudomonas aeruginosa.

    METHODS: A published murine dose fractionation study was replicated in silico. The sensitivity of the PK/PD index towards experimental design, drug susceptibility, uncertainty in MIC and different PK profiles was evaluated.

    RESULTS: The previous murine study data were well replicated with fT > MIC selected as the best predictor. However, for increased dosing frequencies fAUC/MIC was found to be more predictive and the magnitude of the index was sensitive to drug susceptibility. With human PK fT > MIC and fAUC/MIC had similar predictive capacities with preference for fT > MIC when short t1/2 and fAUC/MIC when long t1/2.

    CONCLUSIONS: A longitudinal PKPD model based on in vitro data successfully predicted a previous in vivo study of meropenem. The type and magnitude of the PK/PD index were sensitive to the experimental design, the MIC and the PK. Therefore, it may be preferable to perform simulations for dose selection based on an integrated PK-PKPD model rather than using a fixed PK/PD index target.

  • 8.
    Kristoffersson, Anders
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    David-Pierson, Pascale
    F. Hoffmann-La Roche Ltd.
    Parrott, Neil
    F. Hoffmann-La Roche Ltd.
    Kuhlmann, Olaf
    F. Hoffmann-La Roche Ltd.
    Lave, Thierry
    F. Hoffmann-La Roche Ltd.
    Friberg, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nielsen, Elisabet
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Simulation-based evaluation of PK/PD indices for meropenem across patient groups and experimental designsIn: Article in journal (Refereed)
  • 9.
    Kristoffersson, Anders
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Dishon, Yael
    Division of Infectious Diseases, Rambam Health Care Campus, Haifa, Israel.
    Paul, Mical
    Division of Infectious Diseases, Rambam Health Care Campus, Haifa, Israel.
    Friberg, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    A sparse sampling design, with interim evaluation, for estimation of individual colistin pharmacokineticsManuscript (preprint) (Other academic)
  • 10.
    Kristoffersson, Anders
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Hooker, Andrew
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Cao, Sha
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Lustig, Ulrika
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Karlsson, Mats
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Optimal design of ciprofloxacin in vitro time-kill experimentsManuscript (preprint) (Other academic)
  • 11.
    Kristoffersson, Anders N.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena E.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nyberg, Joakim
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Handling of Inter Occasion Variability (IOV) in Individual Optimal Design (OD) of a Colistin PK Sampling Schedule2013In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 40, no S1, p. S123-S124Article in journal (Other academic)
  • 12.
    Kristoffersson, Anders N.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena E.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nyberg, Joakim
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Inter occasion variability in individual optimal design2015In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 42, no 6, p. 735-750Article in journal (Refereed)
    Abstract [en]

    Inter occasion variability (IOV) is of importance to consider in the development of a design where individual pharmacokinetic or pharmacodynamic parameters are of interest. IOV may adversely affect the precision of maximum a posteriori (MAP) estimated individual parameters, yet the influence of inclusion of IOV in optimal design for estimation of individual parameters has not been investigated. In this work two methods of including IOV in the maximum a posteriori Fisher information matrix (FIMMAP) are evaluated: (i) MAP(occ)-the IOV is included as a fixed effect deviation per occasion and individual, and (ii) POPocc-the IOV is included as an occasion random effect. Sparse sampling schedules were designed for two test models and compared to a scenario where IOV is ignored, either by omitting known IOV (Omit) or by mimicking a situation where unknown IOV has inflated the IIV (Inflate). Accounting for IOV in the FIMMAP markedly affected the designs compared to ignoring IOV and, as evaluated by stochastic simulation and estimation, resulted in superior precision in the individual parameters. In addition MAP(occ) and POPocc accurately predicted precision and shrinkage. For the investigated designs, the MAP(occ) method was on average slightly superior to POPocc and was less computationally intensive.

  • 13.
    Maarbjerg, Sabine F.
    et al.
    Aarhus Univ Hosp, Dept Pediat & Adolescent Med, Palle Juul Jensens Blvd 99, DK-8200 Aarhus N, Denmark.
    Thorsted, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Kristoffersson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena E.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Wang, Mikala
    Aarhus Univ Hosp, Dept Clin Microbiol, Aarhus, Denmark.
    Brock, Birgitte
    Steno Diabet Ctr, Gentofte, Denmark.
    Schroder, Henrik
    Aarhus Univ Hosp, Dept Pediat & Adolescent Med, Palle Juul Jensens Blvd 99, DK-8200 Aarhus N, Denmark.
    Piperacillin pharmacokinetics and target attainment in children with cancer and fever: Can we optimize our dosing strategy?2019In: Pediatric Blood & Cancer, ISSN 1545-5009, E-ISSN 1545-5017, Vol. 66, no 6, article id e27654Article in journal (Refereed)
    Abstract [en]

    Background

    Data on piperacillin-tazobactam pharmacokinetics and optimal dosing in children with cancer and fever are limited. Our objective was to investigate piperacillin pharmacokinetics and the probability of target attainment (PTA) with standard intermittent administration (IA), and to simulate PTA in other dosing regimens.

    Procedure

    This prospective pharmacokinetic study was conducted from April 2016 to January 2018. Children with cancer receiving empiric piperacillin-tazobactam to treat infections were included. Piperacillin-tazobactam 100 mg/kg was infused over 5 min every 8 hours (IA). An optimized sample schedule provided six blood samples per subject for piperacillin concentration determination. The evaluated targets included: (1) 100% time of free piperacillin concentration above the minimum inhibitory concentration (fT > MIC) and (2) 50% fT > 4x MIC. MIC50 and MIC90 were defined based on an intrainstitutional MIC range.

    Results

    A total of 482 piperacillin concentrations were obtained from 43 children (aged 1-18 years) during 89 fever episodes. Standard IA resulted in insufficient target attainment, with significant differences in piperacillin pharmacokinetics for different body weights. Median fT > MIC was 61.2%, 53.5%, and 36.3% for MIC50 (2.0 mg/L), MIC90 (4.0 mg/L), and breakpoint for Pseudomonas aeruginosa (16.0 mg/L), respectively. Correspondingly, the median fT > 4x MIC was 43%, 36.3%, and 20.1%. Simulations showed that only continuous infusion reached a PTA of 95% for MIC = 16.0 mg/L, while extended infusion lasting half of the dosing interval reached a PTA of 95% for MIC <= 8 mg/L.

    Conclusions

    Our data revealed insufficient PTA with standard IA of piperacillin-tazobactam in children with cancer and fever. Alternative dosing strategies, preferably continuous infusion, are required to ensure adequate PTA.

  • 14.
    Mohamed, Ami F
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Kristoffersson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karvanen, Matti
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Nielsen, Elisabet
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Cars, Otto
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Infectious Diseases.
    Friberg, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Dynamic interaction of colistin and meropenem on a WT and a resistant strain of Pseudomonas aeruginosa as quantified in a PK/PD model2016In: Journal of Antimicrobial Chemotherapy, ISSN 0305-7453, E-ISSN 1460-2091, Vol. 71, no 5, p. 1279-1290Article in journal (Refereed)
    Abstract [en]

    OBJECTIVES: Combination therapy can be a strategy to ensure effective bacterial killing when treating Pseudomonas aeruginosa, a Gram-negative bacterium with high potential for developing resistance. The aim of this study was to develop a pharmacokinetic/pharmacodynamic (PK/PD) model that describes the in vitro bacterial time-kill curves of colistin and meropenem alone and in combination for one WT and one meropenem-resistant strain of P. aeruginosa.

    METHODS: In vitro time-kill curve experiments were conducted with a P. aeruginosa WT (ATCC 27853) (MICs: meropenem 1 mg/L; colistin 1 mg/L) and a meropenem-resistant type (ARU552) (MICs: meropenem 16 mg/L; colistin 1.5 mg/L). PK/PD models characterizing resistance were fitted to the observed bacterial counts in NONMEM. The final model was applied to predict the bacterial killing of ARU552 for different combination dosages of colistin and meropenem.

    RESULTS: A model with compartments for growing and resting bacteria, where the bacterial killing by colistin reduced with continued exposure and a small fraction (0.15%) of the start inoculum was resistant to meropenem, characterized the bactericidal effect and resistance development of the two antibiotics. For a typical patient, a loading dose of colistin combined with a high dose of meropenem (2000 mg q8h) was predicted to result in a pronounced kill of the meropenem-resistant strain over 24 h.

    CONCLUSIONS: The developed PK/PD model successfully described the time course of bacterial counts following exposures to colistin and meropenem, alone and in combination, for both strains, and identified a dynamic drug interaction. The study illustrates the application of a PK/PD model and supports high-dose combination therapy of colistin and meropenem to overcome meropenem resistance.

  • 15.
    Mohamed, Ami
    et al.
    Institute for Medical Research, Kuala Lumpur, Malaysia.
    Kristoffersson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karvanen, Matti
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Nielsen, Elisabet
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Cars, Otto
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Friberg, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Dynamic Interaction of Colistin and Meropenem on a Wild-type and a Resistant strain of Pseudomonas aeruginosa as Quantified in a PKPD-ModelArticle in journal (Refereed)
  • 16.
    Thorsted, Anders
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Kristoffersson, Anders N.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Pharmetheus AB, Uppsala, Sweden.
    Maarbjerg, Sabine F.
    Aarhus Univ Hosp, Dept Pediat & Adolescent Med, Aarhus, Denmark.
    Schrøder, Henrik
    Aarhus Univ Hosp, Dept Pediat & Adolescent Med, Aarhus, Denmark.
    Wang, Mikala
    Aarhus Univ Hosp, Dept Clin Microbiol, Aarhus, Denmark.
    Brock, Birgitte
    Aarhus Univ Hosp, Dept Clin Biochem, Aarhus, Denmark;Steno Diabet Ctr Copenhagen, Gentofte, Denmark.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Friberg, Lena E.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Population pharmacokinetics of piperacillin in febrile children receiving cancer chemotherapy: the impact of body weight and target on an optimal dosing regimen2019In: Journal of Antimicrobial Chemotherapy, ISSN 0305-7453, E-ISSN 1460-2091, Vol. 74, no 10, p. 2984-2993Article in journal (Refereed)
    Abstract [en]

    Background The β-lactam antibiotic piperacillin (in combination with tazobactam) is commonly chosen for empirical treatment of suspected bacterial infections. However, pharmacokinetic variability among patient populations and across ages leads to uncertainty when selecting a dosing regimen to achieve an appropriate pharmacodynamic target.

    Objectives To guide dosing by establishing a population pharmacokinetic model for unbound piperacillin in febrile children receiving cancer chemotherapy, and to assess pharmacokinetic/pharmacodynamic target attainment (100% fT>1xMIC and 50% fT>4xMIC) and resultant exposure, across body weights.

    Methods Forty-three children admitted for 89 febrile episodes contributed 482 samples to the pharmacokinetic analysis. The typical doses required for target attainment were compared for various dosing regimens, in particular prolonged infusions, across MICs and body weights.

    Results A two-compartment model with inter-fever-episode variability in CL, and body weight included through allometry, described the data. A high CL of 15.4L/h (70kg) combined with high glomerular filtration rate (GFR) values indicated rapid elimination and hyperfiltration. The target of 50% fT>4xMIC was achieved for an MIC of 4.0mg/L in a typical patient with extended infusions of 2-3 (q6h) or 3-4 (q8h)h, at or below the standard adult dose (75 and 100mg/kg/dose for q6h and q8h, respectively). Higher doses or continuous infusion were needed to achieve 100% fT>1xMIC due to the rapid piperacillin elimination.

    Conclusions The licensed dose for children with febrile neutropenia (80mg/kg q6h as a 30min infusion) performs poorly for attainment of fT>MIC pharmacokinetic/pharmacodynamic targets. Given the population pharmacokinetic profile, feasible dosing regimens with reasonable exposure are continuous infusion (100% fT>1xMIC) or prolonged infusions (50% fT>4xMIC).

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