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Individualised dosi...
Individualised dosing algorithm and personalised treatment of high‐dose rifampicin for tuberculosis
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- Svensson, Robin J. (författare)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Farmakometri,Uppsala Univ, Sweden
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- Niward, Katarina (författare)
- Linköpings universitet,Avdelningen för mikrobiologi, infektion och inflammation,Medicinska fakulteten,Region Östergötland, Infektionskliniken i Östergötland
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- Davies Forsman, Lina (författare)
- Karolinska Institutet
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- Bruchfeld, Judith (författare)
- Karolinska Institutet
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- Paues, Jakob (författare)
- Linköpings universitet,Avdelningen för mikrobiologi, infektion och inflammation,Medicinska fakulteten,Region Östergötland, Infektionskliniken i Östergötland
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- Eliasson, Erik (författare)
- Karolinska Institutet
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- Schön, Thomas (författare)
- Linköpings universitet,Avdelningen för mikrobiologi, infektion och inflammation,Medicinska fakulteten,Kalmar Cty Hosp, Sweden
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- Simonsson, Ulrika S. H., Professor (författare)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Farmakometri,Uppsala Univ, Sweden
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(creator_code:org_t)
- 2019-07-25
- 2019
- Engelska.
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Ingår i: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 85:10, s. 2341-2350
- Relaterad länk:
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Abstract
Ämnesord
Stäng
- AimsTo propose new exposure targets for Bayesian dose optimisation suited for high‐dose rifampicin and to apply them using measured plasma concentrations coupled with a Bayesian forecasting algorithm allowing predictions of future doses, considering rifampicin's auto‐induction, saturable pharmacokinetics and high interoccasion variability.MethodsRifampicin exposure targets for Bayesian dose optimisation were defined based on literature data on safety and anti‐mycobacterial activity in relation to rifampicin's pharmacokinetics i.e. highest plasma concentration up to 24 hours and area under the plasma concentration–time curve up to 24 hours (AUC0–24h). Targets were suggested with and without considering minimum inhibitory concentration (MIC) information. Individual optimal doses were predicted for patients treated with rifampicin (10 mg/kg) using the targets with Bayesian forecasting together with sparse measurements of rifampicin plasma concentrations and baseline rifampicin MIC.ResultsThe suggested exposure target for Bayesian dose optimisation was a steady state AUC0–24h of 181–214 h × mg/L. The observed MICs ranged from 0.016–0.125 mg/L (mode: 0.064 mg/L). The predicted optimal dose in patients using the suggested target ranged from 1200–3000 mg (20–50 mg/kg) with a mode of 1800 mg (30 mg/kg, n = 24). The predicted optimal doses when taking MIC into account were highly dependent on the known technical variability of measured individual MIC and the dose was substantially lower compared to when using the AUC0–24h‐only target.ConclusionsA new up‐to‐date exposure target for Bayesian dose optimisation suited for high‐dose rifampicin was derived. Using measured plasma concentrations coupled with Bayesian forecasting allowed prediction of the future dose whilst accounting for the auto‐induction, saturable pharmacokinetics and high between‐occasion variability of rifampicin.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmakologi och toxikologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmacology and Toxicology (hsv//eng)
Nyckelord
- clinical pharmacology
- modelling and simulation
- pharmacodynamics
- pharmacokinetics
- pharmacometrics
- population analysis
- therapeutic drug monitoring
- Farmaceutisk vetenskap
- Pharmaceutical Science
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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