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.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Found 104 Matches

R-Omeprazole_V12R2_USFDA_20160714
Note: 1. fup was reported as 0.04 in our publication (http://www.ncbi.nlm.nih.gov/pubmed/24590877) without changing the cmp file (fup=0.043). 2. The compound file was developed for R-omeprazole solution 3. We also have converted V14R1 file that has been tested to generate identical results under the condition of mutual interaction with esomeprazole (Condition 2 in Table II in our publication).

Brand Name(s) include : Malarone (fixed dose combination with atovaquone)

Disease: Malaria, prophylaxis against Plasmodium falciparum in travelers

Drug Class: Antimalarials

Date Updated: March 2022

Related Files: Cycloguanil (metabolite of proguanil), Atovaquone (drug partner in fixed dose combinations)

Model at-a-glance

 Absorption Model

  •   First-Order

 Volume of Distribution 

  •   Full PBPK (Method 2)

  Note: Kp scalar used

 Route of Elimination

  •   CYP2C19, CYP3A4, renal clearance

 Perpetrator DDI

  •   CYP2D6 Inhibitor

 Validation

  • Proguanil and cycloguanil files were built using in vitro and clinical (Jeppersen et al., 1997) data
  • 3 clinical studies describing single and multiple dose exposure of proguanil were used to verify the PBPK model. 66% of studies were within 2-fold, of which 33% 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 proguanil 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
  • With a large CLRcomponent and chemical relation to metformin, we hypothesise that proguanil may be a substrate for active transport in the kidney. However, owing to a lack of mechanistic information relating to active transport this cannot be built into the model.​

 Updates in V19

  • Modification of fm values
  • Model converted from minimal to full PBPK distribution model
  • Updated CYP2D6 IC50
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

 

Enfuviridine

Brand Name(s) include: Fuzeon

Disease: HIV

Drug Class: HIV Entry and Fusion Inhibitor

Date of Review: 2020

Number of Models Reviewed: 1

Number of Models added to the Repository: 1

The model at-a-glance

 Publication

Pan, X., Stader, F., Abduljalil, K., Gill, K. L., Johnson, T. N., Gardner, I., & Jamei, M. (2020). Development and Application of a Physiologically-Based Pharmacokinetic Model to Predict the Pharmacokinetics of Therapeutic Proteins from Full-term Neonates to Adolescents. The AAPS journal, 22(4), 76.

 Simcyp Version

V18

 Published Model Application

Prediction of exposure in noenates

 Absorption Model

First Order

 Volume of Distribution Details

Full PBPK

 Route of Elimination

  • Renal filtration
  • Additional systemic clearance

 Perpetrator DDI

  • None 

 Advantages and Limitations

  • Model was developed to predict the PK of enfuviridine in neonates and adolescents.
  • Model was verified in adult and pediatric populations.
  • Model was verified for IV and subcutaneous dosing.
  • Model was developed in V18.  Due to changes in the Simulator, the model would need to be revalidated for use in V20 and subsequent versions.

 Model Compound Files

  • v18_res_enfuviridine_simcyp_pan
  • v18_res_enfuviridine_simcyp_pan_sc_paed

|<

<

12

13

14

15

16

17

18

19

20

21

22

23

24

25

>

>|