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Article ; Online: Where Do PBPK Models Stand in Pharmacometrics and Systems Pharmacology?

Jamei, Masoud

CPT: pharmacometrics & systems pharmacology

2020 Volume 9, Issue 2, Page(s) 75–76

MeSH term(s)	Computer Simulation ; Drug Development/methods ; Humans ; Models, Biological ; Pharmacokinetics ; Pharmacology/methods ; Systems Biology/methods
Language	English
Publishing date	2020-01-26
Publishing country	United States
Document type	Journal Article
ZDB-ID	2697010-7
ISSN	2163-8306 ; 2163-8306
ISSN (online)	2163-8306
ISSN	2163-8306
DOI	10.1002/psp4.12493
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Article: An Application of a Physiologically Based Pharmacokinetic Approach to Predict Ceftazidime Pharmacokinetics in a Pregnant Population.

Abduljalil, Khaled / Gardner, Iain / Jamei, Masoud

Pharmaceutics

2024 Volume 16, Issue 4

Abstract: Physiological changes during pregnancy can alter maternal and fetal drug exposure. The objective of this work was to predict maternal and umbilical ceftazidime pharmacokinetics during pregnancy. Ceftazidime transplacental permeability was predicted from ... ...

Abstract	Physiological changes during pregnancy can alter maternal and fetal drug exposure. The objective of this work was to predict maternal and umbilical ceftazidime pharmacokinetics during pregnancy. Ceftazidime transplacental permeability was predicted from its physicochemical properties and incorporated into the model. Predicted concentrations and parameters from the PBPK model were compared to the observed data. PBPK predicted ceftazidime concentrations in non-pregnant and pregnant subjects of different gestational weeks were within 2-fold of the observations, and the observed concentrations fell within the 5th-95th prediction interval from the PBPK simulations. The calculated transplacental clearance (0.00137 L/h/mL of placenta volume) predicted an average umbilical cord-to-maternal plasma ratio of 0.7 after the first dose, increasing to about 1.0 at a steady state, which also agrees well with clinical observations. The developed maternal PBPK model adequately predicted the observed exposure and kinetics of ceftazidime in the pregnant population. Using a verified population-based PBPK model provides valuable insights into the disposition of drug concentrations in special individuals that are otherwise difficult to study and, in addition, offers the possibility of supplementing sparse samples obtained in vulnerable populations with additional knowledge, informing the dosing adjustment and study design, and improving the efficacy and safety of drugs in target populations.
Language	English
Publishing date	2024-03-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527217-2
ISSN	1999-4923
ISSN	1999-4923
DOI	10.3390/pharmaceutics16040474
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Article: Recent Advances in Development and Application of Physiologically-Based Pharmacokinetic (PBPK) Models: a Transition from Academic Curiosity to Regulatory Acceptance.

Jamei, Masoud

Current pharmacology reports

2016 Volume 2, Page(s) 161–169

Abstract: There is a renewed surge of interest in applications of physiologically-based pharmacokinetic (PBPK) models by the pharmaceutical industry and regulatory agencies. Developing PBPK models within a systems pharmacology context allows separation of the ... ...

Abstract	There is a renewed surge of interest in applications of physiologically-based pharmacokinetic (PBPK) models by the pharmaceutical industry and regulatory agencies. Developing PBPK models within a systems pharmacology context allows separation of the parameters pertaining to the animal or human body (the system) from that of the drug and the study design which is essential to develop generic drug-independent models used to extrapolate PK/PD properties in various healthy and patient populations. This has expanded the classical paradigm to a 'predict-learn-confirm-apply' concept. Recently, a number of drug labels are informed by simulation results generated using PBPK models. These cases show that either the simulations are used in lieu of conducting clinical studies or have informed the drug label that otherwise would have been silent in some specific situations. It will not be surprising to see applications of these models in implementing precision dosing at the point of care in the near future.
Language	English
Publishing date	2016-04-14
Publishing country	Switzerland
Document type	Review ; Journal Article
ISSN	2198-641X
ISSN	2198-641X
DOI	10.1007/s40495-016-0059-9
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Article: Application of a Physiologically Based Pharmacokinetic Approach to Predict Theophylline Pharmacokinetics Using Virtual Non-Pregnant, Pregnant, Fetal, Breast-Feeding, and Neonatal Populations.

Abduljalil, Khaled / Gardner, Iain / Jamei, Masoud

Frontiers in pediatrics

2022 Volume 10, Page(s) 840710

Abstract: Perinatal pharmacology is influenced by a myriad of physiological variables that are changing dynamically. The influence of these covariates has not been assessed systemically. The objective of this work was to use theophylline as a model drug and to ... ...

Abstract	Perinatal pharmacology is influenced by a myriad of physiological variables that are changing dynamically. The influence of these covariates has not been assessed systemically. The objective of this work was to use theophylline as a model drug and to predict its pharmacokinetics before, during (including prediction of the umbilical cord level), and after pregnancy as well as in milk (after single and multiple doses) and in neonates using a physiological-based pharmacokinetic (PBPK) model. Neonatal theophylline exposure from milk consumption was projected in both normal term and preterm subjects. Predicted infant daily doses were calculated using theophylline average and maximum concentration in the milk as well as an estimate of milk consumption. Predicted concentrations and parameters from the PBPK model were compared to the observed data. PBPK predicted theophylline concentrations in non-pregnant and pregnant populations at different gestational weeks were within 2-fold of the observations and the observed concentrations fell within the 5th-95th prediction interval from the PBPK simulations. The PBPK model predicted an average cord-to-maternal plasma ratio of 1.0, which also agrees well with experimental observations. Predicted postpartum theophylline concentration profiles in milk were also in good agreement with observations with a predicted milk-to-plasma ratio of 0.68. For an infant of 2 kg consuming 150 ml of milk per day, the lactation model predicted a relative infant dose (RID) of 12 and 17% using predicted average (C
Language	English
Publishing date	2022-05-12
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2711999-3
ISSN	2296-2360
ISSN	2296-2360
DOI	10.3389/fped.2022.840710
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Article ; Online: Prediction of basic drug exposure in milk using a lactation model algorithm integrated within a physiologically based pharmacokinetic model.

Pansari, Amita / Faisal, Muhammad / Jamei, Masoud / Abduljalil, Khaled

Biopharmaceutics & drug disposition

2022 Volume 43, Issue 5, Page(s) 201–212

Abstract: Medication use during breastfeeding can be a matter of concern due to unintended infant exposure to drugs through breast milk. The available information relating to the safety of most medications is limited and may vary. More precise information is ... ...

Abstract	Medication use during breastfeeding can be a matter of concern due to unintended infant exposure to drugs through breast milk. The available information relating to the safety of most medications is limited and may vary. More precise information is needed regarding the safety to the newborn or infants of the medications taken by the mother during breastfeeding. Physiologically based Pharmacokinetic Model (PBPK) approaches can be utilized to predict the drug exposure in the milk of breastfeeding women and can act as a supporting tool in the risk assessment of feeding infants. This study aims to assess the predictive performance of an integrated 'log transformed phase-distribution' lactation model within a PBPK platform. The model utilizes the physicochemical properties of four basic drugs, namely tramadol, venlafaxine, fluoxetine, and paroxetine, and analyses the milk compositions to predict the milk-to-plasma (M/P) ratio. The M/P prediction model was incorporated within the Simcyp Simulator V20 to predict the milk exposure and to estimate the likely infant dose for these drugs. The PBPK models adequately predicted the maternal plasma exposure, M/P ratio, and the infant daily dose to within two-fold of the clinically observed values for all four compounds. Integration of the lactation model within PBPK models facilitates the prediction of drug exposure in breast milk. The developed model can inform the design of lactation studies and assist with the neonatal risk assessment after maternal exposure to such environmental chemicals or basic drugs which diffuse passively into the milk.
MeSH term(s)	Infant ; Infant, Newborn ; Humans ; Female ; Milk, Human/chemistry ; Breast Feeding ; Lactation ; Fluoxetine/analysis ; Algorithms
Chemical Substances	Fluoxetine (01K63SUP8D)
Language	English
Publishing date	2022-10-17
Publishing country	England
Document type	Journal Article
ZDB-ID	603014-2
ISSN	1099-081X ; 0142-2782
ISSN (online)	1099-081X
ISSN	0142-2782
DOI	10.1002/bdd.2334
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Article ; Online: Prediction of Maternal and Fetal Acyclovir, Emtricitabine, Lamivudine, and Metformin Concentrations during Pregnancy Using a Physiologically Based Pharmacokinetic Modeling Approach.

Abduljalil, Khaled / Pansari, Amita / Ning, Jia / Jamei, Masoud

Clinical pharmacokinetics

2022 Volume 61, Issue 5, Page(s) 725–748

Abstract: Background: Concerns over maternal and fetal drug exposure during pregnancy highlight the need for improved understanding of drug distribution to the fetus through the placental barrier.: Objective: Our objective was to predict maternal and fetal ... ...

Abstract	Background: Concerns over maternal and fetal drug exposure during pregnancy highlight the need for improved understanding of drug distribution to the fetus through the placental barrier. Objective: Our objective was to predict maternal and fetal drug disposition using a physiologically based pharmacokinetic (PBPK) modeling approach. Methods: We used the detailed maternal-placental-fetal PBPK model within the Simcyp Simulator V20 to predict the maternal and fetal drug exposure of acyclovir, emtricitabine, lamivudine, and metformin during pregnancy and at delivery. The dynamic model includes gestational changes to the maternal, fetal, and placental physiological parameters. Placental kinetics were parameterized using published ex vivo data for these four compounds. Amniotic data were included where available. PBPK predictions were compared with the observed data using twofold criteria. Results: Maternal-fetal PBPK models were developed completely from the bottom up without any parameter adjustments. The PBPK model-predicted exposures matched the observed maternal and umbilical exposure for acyclovir (six maternal studies, all of which all reported umbilical exposure), emtricitabine (six maternal studies, of which four reported umbilical exposure), lamivudine, (five maternal studies, of which four reported umbilical exposure), and metformin (seven studies, of which six reported umbilical exposure). Predicted pharmacokinetic parameters were within twofold of the observed values. Conclusion: Integration of fetal and maternal system parameters within PBPK models, together with experimental data from ex vivo placental perfusion studies, facilitated and extended the application of the pregnancy PBPK model. Such models can also be used inform clinical trials and maternal/fetal risk assessment following maternally administered drugs or unintended exposure to environmental toxicants.
MeSH term(s)	Acyclovir ; Emtricitabine/pharmacokinetics ; Female ; Fetus ; Humans ; Lamivudine ; Maternal-Fetal Exchange/physiology ; Metformin ; Models, Biological ; Pharmaceutical Preparations ; Placenta ; Pregnancy
Chemical Substances	Pharmaceutical Preparations ; Lamivudine (2T8Q726O95) ; Metformin (9100L32L2N) ; Emtricitabine (G70B4ETF4S) ; Acyclovir (X4HES1O11F)
Language	English
Publishing date	2022-01-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	197627-8
ISSN	1179-1926 ; 0312-5963
ISSN (online)	1179-1926
ISSN	0312-5963
DOI	10.1007/s40262-021-01103-0
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Zs.A 1246: Show issues

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Article ; Online: Prediction of drug concentrations in milk during breastfeeding, integrating predictive algorithms within a physiologically-based pharmacokinetic model.

Abduljalil, Khaled / Pansari, Amita / Ning, Jia / Jamei, Masoud

CPT: pharmacometrics & systems pharmacology

2021 Volume 10, Issue 8, Page(s) 878–889

Abstract: There is a risk of exposure to drugs in neonates during the lactation period due to maternal drug intake. The ability to predict drugs of potential hazards to the neonates would be useful in a clinical setting. This work aimed to evaluate the possibility ...

Abstract	There is a risk of exposure to drugs in neonates during the lactation period due to maternal drug intake. The ability to predict drugs of potential hazards to the neonates would be useful in a clinical setting. This work aimed to evaluate the possibility of integrating milk-to-plasma (M/P) ratio predictive algorithms within the physiologically-based pharmacokinetic (PBPK) approach and to predict milk exposure for compounds with different physicochemical properties. Drug and physiological milk properties were integrated to develop a lactation PBPK model that takes into account the drug ionization, partitioning between the maternal plasma and milk matrices, and drug partitioning between the milk constituents. Infant dose calculations that take into account maternal and milk physiological variability were incorporated in the model. Predicted M/P ratio for acetaminophen, alprazolam, caffeine, and digoxin were 0.83 ± 0.01, 0.45 ± 0.05, 0.70 ± 0.04, and 0.76 ± 0.02, respectively. These ratios were within 1.26-fold of the observed ratios. Assuming a daily milk intake of 150 ml, the predicted relative infant dose (%) for these compounds were 4.0, 6.7, 9.9, and 86, respectively, which correspond to a daily ingestion of 2.0 ± 0.5 mg, 3.7 ± 1.2 µg, 2.1 ± 1.0 mg, and 32 ± 4.0 µg by an infant of 5 kg bodyweight. Integration of the lactation model within the PBPK approach will facilitate and extend the application of PBPK models during drug development in high-throughput screening and in different clinical settings. The model can also be used in designing lactation trials and in the risk assessment of both environmental chemicals and maternally administered drugs.
MeSH term(s)	Adult ; Algorithms ; Breast Feeding ; Female ; Humans ; Infant, Newborn ; Lactation ; Milk, Human/chemistry ; Models, Biological ; Pharmaceutical Preparations/metabolism ; Research Design ; Risk Assessment ; Young Adult
Chemical Substances	Pharmaceutical Preparations
Language	English
Publishing date	2021-07-02
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2697010-7
ISSN	2163-8306 ; 2163-8306
ISSN (online)	2163-8306
ISSN	2163-8306
DOI	10.1002/psp4.12662
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Article ; Online: Prediction of Maternal and Fetoplacental Concentrations of Cefazolin, Cefuroxime, and Amoxicillin during Pregnancy Using Bottom-Up Physiologically Based Pharmacokinetic Models.

Abduljalil, Khaled / Ning, Jia / Pansari, Amita / Pan, Xian / Jamei, Masoud

Drug metabolism and disposition: the biological fate of chemicals

2022 Volume 50, Issue 4, Page(s) 386–400

Abstract: Concerns over maternal and fetal drug exposures highlight the need for a better understanding of drug distribution into the fetus through the placental barrier. This study aimed to predict maternal and fetal drug disposition using physiologically based ... ...

Abstract	Concerns over maternal and fetal drug exposures highlight the need for a better understanding of drug distribution into the fetus through the placental barrier. This study aimed to predict maternal and fetal drug disposition using physiologically based pharmacokinetic (PBPK) modeling. The detailed maternal-placental-fetal PBPK model within the Simcyp Simulator V20 was used to predict the maternal and fetoplacental exposure of cefazolin, cefuroxime, and amoxicillin during pregnancy and at delivery. The mechanistic dynamic model includes physiologic changes of the maternal, fetal, and placental parameters over the course of pregnancy. Placental kinetics were parametrized using permeability parameters determined from the physicochemical properties of these compounds. Then, the PBPK predictions were compared with the observed data. Fully bottom-up fetoplacental PBPK models were developed for cefuroxime, cefazolin, and amoxicillin without any parameter fitting. Predictions in nonpregnant subjects and in pregnant subjects fall within 2-fold of the observed values. Predictions matched observed pharmacokinetic data reported in nine maternal (five fetoplacental) studies for cefuroxime, 10 maternal (five fetoplacental) studies for cefazolin, and six maternal (two fetoplacental) studies for amoxicillin. Integration of the fetal and maternal system parameters within PBPK models, together with compound-related parameters used to calculate placental permeability, facilitates and extends the applications of the maternal-placental-fetal PBPK model. The developed model can also be used for designing clinical trials and prospectively used for maternal-fetal risk assessment after maternally administered drugs or unintended exposure to environmental toxicants. SIGNIFICANCE STATEMENT: This study investigates the performance of an integrated maternal-placental-fetal PBPK model to predict maternal and fetal tissue exposure of renally eliminated antibiotics that cross the placenta through a passive diffusion mechanism. The transplacental permeability clearance was predicted from the drug physicochemical properties. Results demonstrate that the PBPK approach can facilitate the prediction of maternal and fetal drug exposure simultaneously at any gestational age to support its use in the maternal-fetal exposure assessments.
MeSH term(s)	Amoxicillin ; Cefazolin/pharmacokinetics ; Cefuroxime/pharmacokinetics ; Female ; Humans ; Maternal-Fetal Exchange/physiology ; Models, Biological ; Placenta ; Pregnancy
Chemical Substances	Amoxicillin (804826J2HU) ; Cefazolin (IHS69L0Y4T) ; Cefuroxime (O1R9FJ93ED)
Language	English
Publishing date	2022-01-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	186795-7
ISSN	1521-009X ; 0090-9556
ISSN (online)	1521-009X
ISSN	0090-9556
DOI	10.1124/dmd.121.000711
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Zs.A 1014: Show issues

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Article ; Online: Incorporation and Performance Verification of Hepatic Portal Blood Flow Shunting in Minimal and Full PBPK Models of Liver Cirrhosis.

Small, Ben G / Hatley, Oliver / Jamei, Masoud / Gardner, Iain / Johnson, Trevor N

Clinical pharmacology and therapeutics

2023 Volume 114, Issue 6, Page(s) 1264–1273

Abstract: Patho-physiological changes in liver cirrhosis create portacaval shunts that allow blood flow to bypass the hepatic portal vein into the systemic circulation affecting drug pharmacokinetics (PKs). The objectives of this work were to implement a ... ...

Abstract	Patho-physiological changes in liver cirrhosis create portacaval shunts that allow blood flow to bypass the hepatic portal vein into the systemic circulation affecting drug pharmacokinetics (PKs). The objectives of this work were to implement a physiologically-based pharmacokinetic (PBPK) framework describing shunted blood flows in virtual patients with differing degrees of liver cirrhosis; and to assess the minimal and full PBPK model's performance using drugs with intermediate to high hepatic extraction. Single dose concentration-time profiles and PK parameters for oral ibrutinib, midazolam, propranolol, and buspirone were simulated in healthy volunteers (HVs) and subjects with cirrhosis (Child-Pugh severity score (CP-A, CP-B, or CP-C)). Model performance was verified by comparing predicted to observed fold-changes in PK parameters between HVs and cirrhotic subjects. The verified model was used to simulate the PK changes for simvastatin in patients with cirrhosis. The predicted area under the curve ratios (AUC
MeSH term(s)	Humans ; Propranolol ; Buspirone ; Midazolam ; Liver Cirrhosis/drug therapy ; Simvastatin ; Models, Biological
Chemical Substances	Propranolol (9Y8NXQ24VQ) ; Buspirone (TK65WKS8HL) ; Midazolam (R60L0SM5BC) ; Simvastatin (AGG2FN16EV)
Language	English
Publishing date	2023-09-09
Publishing country	United States
Document type	Journal Article
ZDB-ID	123793-7
ISSN	1532-6535 ; 0009-9236
ISSN (online)	1532-6535
ISSN	0009-9236
DOI	10.1002/cpt.3032
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Zs.A 20: Show issues

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Article ; Online: Prediction of maternal pharmacokinetics using physiologically based pharmacokinetic models: assessing the impact of the longitudinal changes in the activity of CYP1A2, CYP2D6 and CYP3A4 enzymes during pregnancy.

Abduljalil, Khaled / Pansari, Amita / Jamei, Masoud

Journal of pharmacokinetics and pharmacodynamics

2020 Volume 47, Issue 4, Page(s) 361–383

Abstract: Concerns over gestational effects on the disposition of drugs has highlighted the need for a better understanding of drug distribution and elimination during pregnancy. This study aimed at predicting maternal drug kinetics using a physiologically based ... ...

Abstract	Concerns over gestational effects on the disposition of drugs has highlighted the need for a better understanding of drug distribution and elimination during pregnancy. This study aimed at predicting maternal drug kinetics using a physiologically based pharmacokinetic (PBPK) modelling approach focusing on the observed gestational changes in three important Cytochrome P450 metabolizing enzymes, namely, CYP1A2, CYP2D6 and CYP3A4 at different gestational weeks (GWs). The Pregnancy PBPK model within the Simcyp Simulator V19 was used to predict the pharmacokinetics of sensitive probes to these enzymes; namely caffeine, theophylline, metoprolol, propranolol, paroxetine, midazolam, nifedipine and rilpivirine. PBPK model predictions were compared against clinical data collated from multiple studies for each compound to cover a wide spectrum of gestational ages. Pregnancy PBPK model predictions were within 2-fold error and indicated that CYP1A2 activity is approximately 0.70, 0.44 and 0.30 fold of the non-pregnant level at the end of the first, second and third trimesters, respectively. On the other hand, CYP2D6 activity increases by 1.36, 2.16 and 3.10 fold of the non-pregnant level at the end of the first, second and third trimesters, respectively. Likewise, CYP3A4 activity increases by 1.25, 1.75 and 2.32 fold of the non-pregnant level at the end of the first, second and third trimesters, respectively. The enzymes activity have been qualified throughout pregnancy. Quantified changes in drug dosing are most relevant during the third trimester, especially for drugs that are mainly eliminated by CYP1A2, CYP2D6 and CYP3A4 enzymes. The provided functions describing the continuous changes to the activity of these enzymes during pregnancy are important when modelling long term pharmacokinetic studies where longitudinal modelling or time-varying covariates are used.
Language	English
Publishing date	2020-08-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	2041601-5
ISSN	1573-8744 ; 1567-567X
ISSN (online)	1573-8744
ISSN	1567-567X
DOI	10.1007/s10928-020-09711-2
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