Model‐Informed Drug Development for Antimicrobials: Translational PK and PK/PD Modeling to Predict an Efficacious Human Dose for Apramycin. Issue 4 (28th November 2020)
- Record Type:
- Journal Article
- Title:
- Model‐Informed Drug Development for Antimicrobials: Translational PK and PK/PD Modeling to Predict an Efficacious Human Dose for Apramycin. Issue 4 (28th November 2020)
- Main Title:
- Model‐Informed Drug Development for Antimicrobials: Translational PK and PK/PD Modeling to Predict an Efficacious Human Dose for Apramycin
- Authors:
- Sou, Tomás
Hansen, Jon
Liepinsh, Edgars
Backlund, Maria
Ercan, Onur
Grinberga, Solveiga
Cao, Sha
Giachou, Paraskevi
Petersson, Anna
Tomczak, Magdalena
Urbas, Malgorzata
Zabicka, Dorota
Vingsbo Lundberg, Carina
Hughes, Diarmaid
Hobbie, Sven N.
Friberg, Lena E. - Abstract:
- Abstract : Apramycin represents a subclass of aminoglycoside antibiotics that has been shown to evade almost all mechanisms of clinically relevant aminoglycoside resistance. Model‐informed drug development may facilitate its transition from preclinical to clinical phase. This study explored the potential of pharmacokinetic/pharmacodynamic (PK/PD) modeling to maximize the use of in vitro time‐kill and in vivo preclinical data for prediction of a human efficacious dose (HED) for apramycin. PK model parameters of apramycin from four different species (mouse, rat, guinea pig, and dog) were allometrically scaled to humans. A semimechanistic PK/PD model was developed from the rich in vitro data on four Escherichia coli strains and subsequently the sparse in vivo efficacy data on the same strains were integrated. An efficacious human dose was predicted from the PK/PD model and compared with the classical PK/PD index methodology and the aminoglycoside dose similarity. One‐compartment models described the PK data and human values for clearance and volume of distribution were predicted to 7.07 L/hour and 26.8 L, respectively. The required f AUC/MIC (area under the unbound drug concentration‐time curve over MIC ratio) targets for stasis and 1‐log kill in the thigh model were 34.5 and 76.2, respectively. The developed PK/PD model predicted the efficacy data well with strain‐specific differences in susceptibility, maximum bacterial load, and resistance development. All three doseAbstract : Apramycin represents a subclass of aminoglycoside antibiotics that has been shown to evade almost all mechanisms of clinically relevant aminoglycoside resistance. Model‐informed drug development may facilitate its transition from preclinical to clinical phase. This study explored the potential of pharmacokinetic/pharmacodynamic (PK/PD) modeling to maximize the use of in vitro time‐kill and in vivo preclinical data for prediction of a human efficacious dose (HED) for apramycin. PK model parameters of apramycin from four different species (mouse, rat, guinea pig, and dog) were allometrically scaled to humans. A semimechanistic PK/PD model was developed from the rich in vitro data on four Escherichia coli strains and subsequently the sparse in vivo efficacy data on the same strains were integrated. An efficacious human dose was predicted from the PK/PD model and compared with the classical PK/PD index methodology and the aminoglycoside dose similarity. One‐compartment models described the PK data and human values for clearance and volume of distribution were predicted to 7.07 L/hour and 26.8 L, respectively. The required f AUC/MIC (area under the unbound drug concentration‐time curve over MIC ratio) targets for stasis and 1‐log kill in the thigh model were 34.5 and 76.2, respectively. The developed PK/PD model predicted the efficacy data well with strain‐specific differences in susceptibility, maximum bacterial load, and resistance development. All three dose prediction approaches supported an apramycin daily dose of 30 mg/kg for a typical adult patient. The results indicate that the mechanistic PK/PD modeling approach can be suitable for HED prediction and serves to efficiently integrate all available efficacy data with potential to improve predictive capacity. … (more)
- Is Part Of:
- Clinical pharmacology & therapeutics. Volume 109:Issue 4(2021)
- Journal:
- Clinical pharmacology & therapeutics
- Issue:
- Volume 109:Issue 4(2021)
- Issue Display:
- Volume 109, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 109
- Issue:
- 4
- Issue Sort Value:
- 2021-0109-0004-0000
- Page Start:
- 1063
- Page End:
- 1073
- Publication Date:
- 2020-11-28
- Subjects:
- Pharmacology -- Periodicals
Therapeutics -- Periodicals
615.5 - Journal URLs:
- http://www.nature.com/clpt/index.html ↗
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1532-6535 ↗
http://www.nature.com/ ↗
http://firstsearch.oclc.org ↗
http://www.mosby.com/cpt ↗
http://www.sciencedirect.com/science/journal/00099236 ↗
http://www2.us.elsevierhealth.com/scripts/om.dll/serve?action=searchDB&searchdbfor=home&id=cp ↗ - DOI:
- 10.1002/cpt.2104 ↗
- Languages:
- English
- ISSNs:
- 0009-9236
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3286.330000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 16109.xml