Search the PBPK Model Repository

Quickly find freely available drug and population models in our PBPK model repository.

The models provided have been collated from published examples which authors have shared in our Published Model Collection or developed as part of various global health projects in our Global Health Collection. This search facility searches both model collections simultaneously.

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Found 80 Matches

Dihydroartemisinin (DHA) from Artesunate

Brand Name(s) include: Camoquin (FDC with amodiaquine)

Disease: Malaria

Drug Class: Antimalarials

Related Drugs: DHA, Amodiaquine

Date Updated: March 2022

The model at-a-glance

  Absorption Model

  • First-Order

  Volume of Distribution

  • Full PBPK (Method 2)

Note: Kp scalar used

  Route of Elimination

  • UGT1A9 (50%); UGT2B7(50%)

  Perpetrator DDI

  • CYP1A2 Inhibitor

  Validation

  • One clinical study describing single dose exposure of DHA was used to verify the PBPK model.  100% of studies were within 2-fold, of which 100% were within 1.5-fold. 

  Limitations

  • The absorption model does not consider the formation of ‘DHA from artesunate’ mechanistically. Instead, an optimized ka and fa were applied to the DHA model to describe the observed plasma concentration-time curve of DHA. The remainder of the DHA model was identical to the DHA model which is described above.
  • The model does not account for the differences in plasma fraction unbound observed in patients compared to healthy volunteers.
  • Verification needed for perpetrator DDI assessment as literature data is unavailable at this time.

  Updates in V19

  • Updated in vitro data
    • Propranolol Papp: 30 cm/s x 106
  • Converted model to full PBPK with Vss predicted through Method 2
  • Updated retrograde clearance

 

Doxycycline

Brand Name(s) include: Adoxa, Doryx, Monodox, Oracea, Periostat, Vibramycin, Vibra-tabs

Disease: Malaria

Drug Class: Antibiotic

Date Updated: June 2022

The model at-a-glance

  Absorption Model

  • First-Order

  Volume of Distribution

  • Full PBPK (Method 2)
  • Note: A Kp scalar (0.3) was used in the model

  Route of Elimination

  • Biliary = 66%; Renal= 44%

  Perpetrator DDI

  • None

  Validation

  • Seven clinical studies describing single and multiple dose exposure of doxycycline were used to verify the PBPK model. The model predicted AUC values in 86% of studies within 2-fold (100% if one simulated/observed ratio is rounded down from 1.52 to 1.5), of which 57% were within 1.5-fold. 

  Limitations

  • Model is not verified at doses below 100 mg or about 200 mg (dose-linearity of doxycycline is uncertain)
  • Model assumes hyclate, monohydrate and hydrochloride formulations are bioequivalent
  • Model is not developed for the prediction of IV doxycycline
  • Model was developed and verified primarily in healthy volunteer studies (except Newton et al. 2005); appropriateness of extrapolation to acute malaria patients is unknown

  Updates in V19

  • Updated in vitro­ data
    • fu: 0.142 -> 0.23
    • B:P: 1.5 -> 0.78
  • Converted from minimal PBPK model to full PBPK model
  • Elimination changed from user input IV clearance to retrograde clearance with biliary clearance and additional hepatic clearance

 

Sulfadoxine

Brand Name(s) include: Fansidar

Disease: Malaria

Drug Class: Sulfonamide

Date Updated: March 2021

The model at-a-glance

  Absorption Model

  • First-Order

  Volume of Distribution

  • Minimal PBPK (User input Vss)

  Route of Elimination

  • Renal clearance (90%); non-specific hepatic metabolism (10%)

  Perpetrator DDI

  • None

  Validation

  • Four clinical studies describing single and multiple dose exposure of sulfadoxine were used to verify the PBPK model. In comparison of predicted vs. observed AUC, 100% of the studies were within 2-fold and 75% were within 1.5-fold. 

  Limitations

  • In the absence of adequate data on the metabolism and excretion of sulfadoxine, it was assumed that 90% was cleared renally and 10% was metabolized by the liver.

  Updates in V19

  • Updated in vitro­ data
    • LogP: 4.22 -> 0.54

 

Capmatinib_V19R1_Pfizer_20210804

An optimized Rosuvastatin (V19) model was used and DDIs predominantly driven by gut BCRP inhibition are reasonably recovered. Altogether, the following inhibitors were used: Capmatinib Fenebrutinib Fostamatinib Itraconazole Zepatier The workspace represents the DDI between Rosuvastatin and Capmatinib. Note: The fuGut in the inhibitor file is set as user input to 1. A minimal PBPK model with VSAC is used. Link to the publication with further details: http://doi.org/10.1002/psp4.12672

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