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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 72 Matches

Pyronaridine

Brand Name(s) include: Pyramax

Disease: Malaria

Drug Class: Antimalarials

Date Updated: March 2022

Related files: Artesunate (fixed dose combination – Pyramax)

The model at-a-glance

  Absorption Model

  • First-Order

  Volume of Distribution

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

  Route of Elimination

  • CYP1A2, CYP2B6, CYP2C8, CYP2D6 and CYP3A4

  Perpetrator DDI

  • CYP2D6 Inhibitor
  • P-gp Inhibitor

  Validation

  • Two clinical studies describing pyronaridine exposure were available for model verification.  100% of predicted Cmax were within 1.5-fold of those observed whereas 40% of AUC were predicted within 1.5-fold of observed. This can be explained as observed exposure at 9mg/kg dose was lower than at 6 mg/kg.  The model recovered the observed data at the 6 mg/kg dose but then over predicted that at the higher dose.

  Limitations

  • One challenge in the verification of the model is the diverse ethnicities of subjects in reported clinical data and how best to reflect this in simulations.  In the absence of virtual Korean populations within the Simulator, the Caucasian population was modified in terms of bodyweight.  In the absence of supporting information, no changes to enzyme abundance (pmol/mg) were made to the population, although changes to liver weight (as a function of body weight) and hence total CYP abundance were propagated into the model.

  Updates in V19

  • Switched to Method 3 to facilitate like for like comparisons for covid- 19     repurposing strategies

 

Probenecid_V12R1_FDA_20150709
Supplemental table. Ki against OAT transporters can be changed (sensitivity analysis was conducted in the referenced publication to explore "in vivo" Ki).
Darunavir&Ritonavir_V13R2_USFDA_20190719
Compound files from publication: Physiologically Based Pharmacokinetic Modeling for Predicting the Effect of Intrinsic and Extrinsic Factors on Darunavir or Lopinavir Exposure Coadministered With Ritonavir Wagner, C., Zhao, P., Arya, V., Mullick, C., Struble, K. and Au, S (2017). https://doi.org/10.1002/jcph.936 /PMID: 28569994 These two files were used in combination (linked models). Note: Darunavir model also has fu,mic for DDI, and induction parameters for CYP1A that were not captured in Supplemental Table 1. Correction: Ritonavir's pKa2 should be 2.6 instead of 2.8 in Suppl. Table 1. https://accp1.onlinelibrary.wiley.com/doi/full/10.1002/jcph.936
Curcumin_Japanese_V19R1_AstraZeneca_20210726
For curcumin, the Japanese population library file from the Simcyp Human Simulator was used, and a sulfotransferase clearance pathway was incorporated as published for the curcumin PBPK model (Physiologically-Based Pharmacokinetic Predictions of the Effect of Curcumin on Metabolism of Imatinib and Bosutinib: In Vitro and In Vivo Disconnect - PubMed (nih.gov)). The curcumin model used in the publication linked is also based on this earlier published model. Fugut=1 represents worst-case scenario DDI while Fugut=0.03 represents assumption that fu,gut = fu,whole blood.

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