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 62 Matches

Brand Name: Invirase (hard gel); Fortovase (soft gel)

Disease: HIV

Drug Class: protease inhibitor

Version: 21

Date Updated: March 2024

The model at-a-glance

 Absorption Model

First order (different absorption parameters for each formulation)

 Volume of Distribution Details

Minimal PBPK with Vsac and Q (Method 2)

 Route of Elimination

  • CYP3A4 = 95%; Additional HLM = 5%

 Perpetrator DDI

  • CYP3A4 Mechanism Based Inhibition

 Validation

The exposure of 1000mg BID saquinavir with 100 mg BID ritonavir regimen for hard gel were reasonably well recovered (3/3 within 2-fold). With the exception of the 1000 mg BID saquinavir with 100 mg BID ritonavir regimen for soft gel, the exposures of ritonavir-boosted regimens were well recovered (4/5 within 1.5-fold).

Ten clinical DDI studies where saquinavir (soft gel) was administered with either ritonavir, cimetidine, ketoconazole, rifampin, erythromycin, or rifabutin were used to verify the PBPK model of saquinavir as a victim. In comparison of predicted vs. observed AUC, 80% of the studies were within 2-fold.

Two clinical DDI studies where saquinavir (hard gel) was administered with either ritonavir or nelfinavir were used to verify the PBPK model of saquinavir (hard gel) as a victim. In comparison of predicted vs. observed AUC, 50% of the studies were within 2-fold.

Three clinical DDI studies where saquinavir was administered with either midazolam or rifabutin were used to verify the PBPK model of rifabutin (soft gel) as a perpetrator. In comparison of predicted vs. observed AUC, 100% of the studies were within 2-fold.

 Limitations

  • The variability within studies has presented a significant challenge to developing a single model to recover all data.
5HMT_V12R2_USFDA_20160510
Metabolite of fesoterodine. Note/correction: 1. PKa 9.3 instead of 7.6 (in supplemental materials) 2. the intrinsic clearance (CLint) values of CYP3A4 and CYP2D6 should be 0.085 and 1.455 uL/min/pmol enzyme 3. note simulation with ketoconazole, ketoconazole cmp file modified with p-gp inhibition constant (Ki) of 0.015 uM (assumed)
EsomeprazoleCapsule_V14R1_AstraZeneca_20200427
https://ascpt.onlinelibrary.wiley.com/doi/full/10.1002/cpt.905 Esomeprazole adult compound file for pediatric prediction. The following parameters need to be updated, as compared to Table 2 in the manuscript: Ka=1.331/h, tlag=1h, fu,gut=0.048
Tafenoquine

Brand Name(s) include: Arakoda, Krintafel

Disease: Malaria

Drug Class: Antimalarials

Date Updated: March 2022

The model at-a-glance

  Absorption Model

  • First-Order

  Volume of Distribution

  • Full PBPK (Method 3)
  • Note: Kp scalar used

  Route of Elimination

  • Undefined liver intrinsic clearance

  Perpetrator DDI

  • CYP2C9 Inhibitor
  • CYP3A4 Inhibitor

  Validation

  • Four clinical studies describing single and multiple dose exposure of tafenoquine were used to verify the PBPK model, although some of these provided PK profiles and no PK parameters and vice versa.  Of the clinical studies describing PK parameters, the model recovered 100% of the observed PK parameters within 1.5-fold (66% within 0.8-1.25-fold) and hence the model is considered predictive.  

  Limitations

  • Tafenoquine is administered with food to increase its exposure and minimize gastrointestinal side effects. The PBPK model was therefore developed to recover the PK of tafenoquine in the fed state.
  • It should be noted that in the absence of information defining the fm of drug metabolizing enzymes, an undefined liver intrinsic clearance is used in the model and hence the model is not able to simulate the liability of tafenoquine as a victim of DDIs.

 

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