Search the PBPK Model Repository

 Publication

De Sousa Mendes, M., Hirt, D., Urien, S., Valade, E., Bouazza, N., Foissac, F., Blanche, S., Treluyer, J. M., & Benaboud, S. (2015). Physiologically-based pharmacokinetic modeling of renally excreted antiretroviral drugs in pregnant women. British journal of clinical pharmacology, 80(5), 1031–1041.

 Simcyp Version

V13

 Published Model Application

Prediction of exposure in pregnancy

 Absorption Model

First Order

Full PBPK

 Route of Elimination

• Renal Elimination
• Includes uptake by OCT2 and efflux by MRP4 in the kidney

 Perpetrator DDI

• None 

 Advantages and Limitations

• Model developed in healthy volunteers and verified in pregnant women.

 Model Compound Files

• v13_res_lamivudine_simcyp_mendex2015

 Publication

De Sousa Mendes M, Chetty M. Are Standard Doses of Renally-Excreted Antiretrovirals in Older Patients Appropriate: A PBPK Study Comparing Exposures in the Elderly Population With Those in Renal Impairment. Drugs R D. 2019 Dec;19(4):339-350.

 Simcyp Version

V17

 Published Model Application

Prediction of exposure in renal impairment

 Absorption Model

First Order

Full PBPK

 Route of Elimination

• Renal Elimination
• Additional non-specific clearance

 Perpetrator DDI

• None 

 Advantages and Limitations

• Model developed to extrapolate elderly populations and renally impaired populations.
• Model was verified in the elderly population

 Model Compound Files

• v17_res_ lamivudine_simcyp_mendex2019

 Publication

Shah, K., Fischetti, B., Cha, A., & Taft, D. R. (2020). Using PBPK Modeling to Predict Drug Exposure and Support Dosage Adjustments in Patients With Renal Impairment: An Example with Lamivudine. Current drug discovery technologies, 17(3), 387–396.

 Simcyp Version

V18

 Published Model Application

Prediction of exposure in renal impairment

 Absorption Model

First Order

Full (mechanistic kidney model)

 Route of Elimination

• Renal Elimination
• Includes uptake by OCT2 and efflux by MATE in the kidney

 Perpetrator DDI

• None 

 Advantages and Limitations

• Model developed to renally impaired populations.

 Model Compound Files

• v18_res_ lamivudine_simcyp_shah2020

 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

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

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

• Minimal

 Route of Elimination

• CYP3A4, Non-specific metabolism, renal clearance
• Bottom-up approach for clearance, f_m,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.
• f_m,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)

• 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