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 125 Matches

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
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.

Darolutamide_RES_V21R1_Simcyp_20230615

The RES-Darolutamide_V21 model has been developed primarily as inhibitor of hepatic OATP1B1 and OATP1B3, and intestinal BCRP using the New GI physiology in Simcyp V21 with altered GI tract population inputs that became default in V22. Darolutamide shows dose proportional PK between 100 to 700 mg BID. It is a BSCII compound, where the metabolite is a potent BCRP-inhibitor too. Darolutamide is possibly a weak CYP3A inducer in the clinic. The back-conversion of Keto-darolutamide to Darolutamide is efficiently catalyzed via cytosolic AKR1C3 (in vitro). This back-conversion is also observed in incubations of feces under anaerobic conditions (in vitro). In the compound fit-for-purpose compound file, the back-conversion was fixed to recover the concentration time profile for the 600 mg BID as this was the dose for the reported Rosuvastatin DDI. Note that two workspaces need to be run to simulate the Darolutamide DDI and then the results have to be combined. This is due to having to switch the position of Darolutamide and rosuvastatin (limitations on functionality on inhibitory metabolite in the Simcyp Simulator currently).

Digoxin_V12R2_Simcyp_20150702
For the file, ADAM and permeability-ltd liver models were used together with the full-PBPK and Rodgers and Rowland method. The file was evaluated using the Jalava et al. 1997 PK data as overlay.

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