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.

To contribute published user compound and/or population files, upload your files here: Upload Model Files

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Found 126 Matches

Morphine&Morphine-3-Glucuronide_V18R1_UniversityOfNorthCarolina_20201005

The submitted workspace file is for Morphine and Morphine-3-glucuronide compound files, with a full PBPK distribution model, ADAM and permeability-limited liver. The model also includes enterohepatic recycling and cleavage of the glucuronide in the gut lumen. The Sim-Healthy Volunteers population library was modified with regards to the relative enzyme abundance of luminal deglucuronidation. The setting in the workspace reflects the trial design from Stuart-Harris et al., 2000. Stuart-Harris R, Joel SP, McDonald P, Currow D, Slevin ML. The pharmacokinetics of morphine and morphine glucuronide metabolites after subcutaneous bolus injection and subcutaneous infusion of morphine. Br J Clin Pharmacol 49 207-214. (2000)

Zepatier_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 Zepatier. Zepatier is an antiviral medicine that contains the active substances elbasvir and grazoprevir. The two compounds were simulated as Inhibitor 1 and Inhibitor 2, respectively. Link to the publication with further details: http://doi.org/10.1002/psp4.12672

Dolutegravir

Brand Name: Tivicay

Disease: HIV

Drug Class: HIV integrase inhibitor

Version: 21

Date Updated: March 2023

The model at-a-glance

 Absorption Model

ADAM (precipitation with solution)

 Volume of Distribution Details

Full PBPK (Method 3)

 Route of Elimination

  • CYP3A4 = 21%; UGT1A1 = 51%; Additional HLM = 28%

 Perpetrator DDI

  • OCT2
  • MATE

 Validation

Model can recover positive food effect for single and multiple dose.

The UGT1A1 fm was verified against UGT1A1 genotype study and with rifampin and atazanavir DDI studies. The fm of CYP3A4 was verified against nevirapine, rifabutin, rifampin, atazanavir, efavirenz, and carbamazepine.

One clinical study in which dolutegravir was administered with metformin was used to verify the Ki of OCT2 and MATE.

Nine clinical DDI studies where dolutegravir was administered with either nevirapine, rifampicin, rifabutin, ritonavir, atazanavir, efavirenz, and carbamazepine were used to verify the PBPK model. In comparison of predicted vs. observed AUC, 100% of the studies were 2-fold and 67% were within 1.25-fold.

 Limitations

DDI with efavirenz and carbamazepine are underpredicted, likely because efavirenz and carbamazepine are inducers of UGT1A1 which is not considered in the current efavirenz and carbamazepine compound files.

Brand Name(s) include: Prezista, Prezcobix, Rezolsta

Disease: HIV

Drug Class: Antiretroviral

Date of Review: 2020

Number of Models Reviewed: 2

Number of Models added to the Repository: 2

The model at-a-glance

Publication – MODEL 1

Wagner et al., Physiologically-Based Pharmacokinetic Modeling for Predicting the Effect of Intrinsic and Extrinsic Factors on Darunavir or Lopinavir Exposure Co-administered with Ritonavir. J Clin Pharmacol. 2017 October ; 57(10): 1295–1304.  (FDA model)

 Simcyp Version

V13

 Published Model Application

Prediction of exposure in hepatic impairment

 Absorption Model

  • First-Order
 Volume of Distribution Details
  • Minimal

 Route of Elimination

  • CYP3A4, Non-specific metabolism, renal clearance
  • Bottom-up approach for clearance, fm,CYP3A4 was optimized with clinical DDI data with ketoconazole

 Perpetrator DDI

  • CYP2B6 Competitive Inhibitor
  • CYP2C9 Competitive Inhibitor
  • CYP2C19 Competitive Inhibitor
  • CYP2D6 Competitive Inhibitor
  • CYP3A4 Competitive Inhibitor
  • CYP3A5 Competitive Inhibitor

 Advantages and Limitations

  • Model developed to predict the impact of CYP3A4.
  • fm,CYP3A4 was optimized with clinical DDI data with ketoconazole.
  • Model recovers PK data after IV administration and single and multiple oral doses to healthy volunteers.
  • Model was used to evaluate the impact of hepatic impairment.
  • Perpetrator DDI not verified with clinical data.

 Model Compound Files

  • v18_darunavir_wagner. cmpz
  • v18_darunavir_600_mg_wagner. wksz

Publication – MODEL 2

Colbers, A., Greupink, R., Litjens, C., Burger, D., & Russel, F. G. (2016). Physiologically Based Modelling of Darunavir/Ritonavir Pharmacokinetics During Pregnancy. Clinical pharmacokinetics, 55(3), 381–396. 

 Simcyp Version

V13

 Published Model Application

Prediction of exposure in pregnancy

 Absorption Model

  • ADAM (transporter efflux and influx included)
 Volume of Distribution Details
  • Full (permeability liver model, transporter efflux and influx included)

 Route of Elimination

  • CYP3A4 and renal clearance
  • ‘Bottom-up’ approach for CYP3A4 clearance from HLM data
  • Non-linear CYP3A4 kinetics

 Perpetrator DDI

  • None

 Advantages and Limitations

  • Model developed to extrapolate darunavir pharmacokinetics in pregnancy.
  • CYP3A4 enzyme kinetics derived from HLM data only.
  • Linked with ritonavir PBPK model.
  • Model recovers single dose PK data with and without ritonavir

 Model Compound Files

  • v18_darunavir_colbers. cmpz
  • v18_darunavir_600_mg_colbers. wksz
  • v18_darunavir_with_ritonavir_colbers. wksz

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