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 9 Matches

Rivaroxaban_V17R1_NationalUniversityofSingapore_20200923
Model Files Publication
https://dmd.aspetjournals.org/content/47/11/1291/tab-article-info This workspace was developed to recapitulate the magnitude of drug-drug interaction reported between Rivaroxaban and Verapamil as reported by Greenblatt et al. (https://pubmed.ncbi.nlm.nih.gov/29194698/) Note 1: In Table 1 of the publication the Caco-2 Papp (pH 7.4:7.4) was reported as 8 x 10-6 cm/s; however, the Rivaroxaban file in the workspace is using a Caco-2 Papp (pH 7.4:7.4) of 21.8 x 10-6 cm/s. This Papp is in line with the reported scalar in the EXCEL outputs and the Table 1. The obtained Rivaroxaban plasma concentration time profile is in line with the reported Figure 2C in the publication. Note 2: In Table 1 of the publication, input data for Mech KiM are stated; however, the Rivaroxaban file in the workspace is using a User Input for the renal clearance of 3.1 L/h; while the input data for Mech KiM are included in the compound file, they are not activated within the workspace, which is mimicking a DDI with Verapamil and Norverapamil. Note 3: Bile:micelle parameters were changed from 3.4 to 3.5.
Search Score: 1
Atovaquone
Model Files Publication

Brand Name(s) include: Malarone

Disease: Malaria

Drug Class: Antimalarials

Date Updated: March 2021

The model at-a-glance

  Absorption Model
  • First-Order

  Volume of Distribution

  • Full PBPK (Method 2)

Note: A Kp scalar (0.04) was used in the model

  Route of Elimination
  • No metabolism; a biliary CLint was input based on clinical data

  Perpetrator DDI
  • None

  Validation

  • Two clinical studies describing single and multiple dose exposure of atovaquone were used to verify the PBPK model. 100% of studies were within 1.5-fold.

  Limitations
  • There are some data to suggest atovaquone is an inhibitor of BCRP.  This is currently not included within the model.

  Updates in V19
  • Updated in vitro­ data
    • LogP: 5.8 -> 8.4
    • Caco-2 Papp 164 > 300 x 10-6 cm/s
    • Propranolol Papp 101 x 10-6 cm/s
  • Optimized ka and tlag
  • Converted from minimal PBPK model to full PBPK model

 

Search Score: 1
Quinine
Model Files Publication

Brand Name(s) include: Qualaquin

Disease: Malaria

Drug Class: Antimalarials

Date Updated: 2021

The model at-a-glance

  Absorption Model

First-Order

  Volume of Distribution

Minimal PBPK (Method 1)

  Route of Elimination

CYP3A4 (fm = 0.50); renal clearance (fe = 0.1)

  Perpetrator DDI
  • CYP2D6 Inhibitor

  Validation

  • Three clinical studies describing Quinine PK were identified for model verification.
  • Three clinical DDI studies where quinine was the victim of CYP-mediated DDIs were used to verify the PBPK model.  All studies were well recovered with simulated Cmax and AUC GMRs within 1.5-fold of the observed

  Limitations
  • The Simcyp quinine PBPK model was able to recover interactions CYP3A inducers and inhibitors with reasonable accuracy.
  • Verification needed for perpetrator DDI assessment as literature data is unavailable at this time.

  Updates in V19
  • Updated in vitro­ data
    • fup: 0.199 -> 0.37
    • Caco-2 A -> B Permeability: 70 x 10-6 cm/s -> 39 x 10-6 cm/s
    • Propranolol reference Permeability: 101 x 10-6 cm/s -> 45 x 10-6 cm/s
  • Minimal PBPK with Vss predicted through Method 1
    • Updated retrograde clearance

 

Search Score: 1
Tramadol_V14R1_JohnsonandJohnson_20151029
Model Files Publication
V12 R1 compound file built to simulate adult Human PK and pediatric PK. Supplied file is for V14 R1. “Physiology-Based IVIVE Predictions of Tramadol from in Vitro Metabolism Data” in Pharm Res January 2015, Volume 32, Issue 1, pp 260-274 http://link.springer.com/article/10.1007%2Fs11095-014-1460-x “Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation.” in AAPSJ November 2015, Volume 17, Issue 6, pp 1376-1387 http://link.springer.com/article/10.1208%2Fs12248-015-9803-z
Search Score: 1

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