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 136 Matches

Tizanidine_V18R1_LongIslandUniversity_20210119

This is compound file for tizanidine, a CYP1A2 substrate. The input values for the Tizanidine PBPK model are listed in table 1 of the publication. The file uses a User fugut of 1E-06. A solid formulation is used with the segregated transit time model activated and a predicted aqueous phase intrinsic solubility.

Tramadol_V14R1_AstraZeneca_20200427

Tramadol adult compound file for pediatric prediction. The following parameters need to be updated, as compared to Table 2 in the manuscript: CYP2D6 0.7, CYP3A4 0.035, CYP2B6 0.1, CLr 6.6 L/hr

Cycloguanil

Brand Name(s) include: N/A

Disease: Malaria

Drug Class: Antimalarials

Date Updated: March 2022

Related drugs: Proguanil

The model at-a-glance

  Absorption Model

First-Order

  Volume of Distribution

Full PBPK (Method 2)

  Route of Elimination

Formed by CYP2C19, CYP3A4; unknown clearance mechanism

  Perpetrator DDI

  • CYP2D6 Inhibitor

  Validation

  • Proguanil and cycloguanil files were built using in vitro and clinical (Jeppersen et al., 1997) data
  • 5 clinical studies describing single and multiple dose exposure of cycloguanil were used to verify the PBPK model. 60% of studies were within 2-fold, of which 40% were within 1.5-fold.
  • A clinical DDI study where proguanil was the victim of a CYP2C19-mediated DDI was accurately recovered using the PBPK model.  

  Limitations

  • Prediction of cycloguanil exposure was complicated by not knowing the polymorphism classification of subjects in each study, hence the model performance was deemed acceptable using the criteria of being within 2-fold of observed.
  • Verification needed for perpetrator DDI assessment as literature data is unavailable at this time

  Updates in V19

  • Recalculated fm values using the corrected dose administered in Jeppesen et al., 1997
  • Previous version used paper calculation of total clearance which did not account for the weight of the salt in the 200 mg dose administered
  • Model converted from minimal to full PBPK distribution model
  • Updated in vitro data
  • Updated CYP2D6 IC50

 

Brand Name(s) include: Selzentry

Disease: HIV

Drug Class: HIV Entry and Fusion Inhibitor

Date of Review: 2020

Number of Models Reviewed: 3

Number of Models added to the Repository: 1

The model at-a-glance

 Publication

Kimoto, E., Vourvahis, M., Scialis, R. J., Eng, H., Rodrigues, A. D., & Varma, M. V. S. (2019). Mechanistic Evaluation of the Complex Drug-Drug Interactions of Maraviroc: Contribution of Cytochrome P450 3A, P-Glycoprotein and Organic Anion Transporting Polypeptide 1B1. Drug metabolism and disposition: the biological fate of chemicals, 47(5), 493–503.

 Simcyp Version

V15

 Published Model Application

DDI prediction

 Absorption Model

ADAM; includes P-gp in the intestines

 Volume of Distribution Details

Full PBPK

 Route of Elimination

  • CYP3A4
  • Renal clearance
  • Includes hepatic biliary clearance by OATP1B1

 Advantages and Limitations

  • Model was developed to evaluate DDI of maraviroc as victim.
  • Model was verified with IV and oral data.
  • Model was verified as a victim of interactions with ketoconazole, ritonavir, efavirenz and rifampin

 Model Compound Files

  • v15_res_maraviroc_simcyp_kimoto
  • v15_res_maraviroc_simcyp_kimoto_iv_3mg
  • v15_res_maraviroc_simcyp_kimoto_iv_10mg
  • v15_res_maraviroc_simcyp_kimoto_iv_30mg
  • v15_res_maraviroc_simcyp_kimoto_po_150mg_bid

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