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Alsmadi MM. Salivary Therapeutic Monitoring of Buprenorphine in Neonates After Maternal Sublingual Dosing Guided by Physiologically Based Pharmacokinetic Modeling. Ther Drug Monit 2024; 46:512-521. [PMID: 38366333 DOI: 10.1097/ftd.0000000000001172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 11/08/2023] [Indexed: 02/18/2024]
Abstract
BACKGROUND Opioid use disorder (OUD) during pregnancy is associated with high mortality rates and neonatal opioid withdrawal syndrome (NOWS). Buprenorphine, an opioid, is used to treat OUD and NOWS. Buprenorphine active metabolite (norbuprenorphine) can cross the placenta and cause neonatal respiratory depression (EC 50 = 35 ng/mL) at high brain extracellular fluid (bECF) levels. Neonatal therapeutic drug monitoring using saliva decreases the likelihood of distress and infections associated with frequent blood sampling. METHODS An adult physiologically based pharmacokinetic model for buprenorphine and norbuprenorphine after intravenous and sublingual administration was constructed, vetted, and scaled to newborn and pregnant populations. The pregnancy model predicted that buprenorphine and norbuprenorphine doses would be transplacentally transferred to the newborns. The newborn physiologically based pharmacokinetic model was used to estimate the buprenorphine and norbuprenorphine levels in newborn plasma, bECF, and saliva after these doses. RESULTS After maternal sublingual administration of buprenorphine (4 mg/d), the estimated plasma concentrations of buprenorphine and norbuprenorphine in newborns exceeded the toxicity thresholds for 8 and 24 hours, respectively. However, the norbuprenorphine bECF levels were lower than the respiratory depression threshold. Furthermore, the salivary buprenorphine threshold levels in newborns for buprenorphine analgesia, norbuprenorphine analgesia, and norbuprenorphine hypoventilation were observed to be 22, 2, and 162 ng/mL. CONCLUSIONS Using neonatal saliva for buprenorphine therapeutic drug monitoring can facilitate newborn safety during the maternal treatment of OUD using sublingual buprenorphine. Nevertheless, the suitability of using adult values of respiratory depression EC 50 for newborns must be confirmed.
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Affiliation(s)
- Mo'tasem M Alsmadi
- Department of Pharmaceutical Technology, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan; and
- Nanotechnology Institute, Jordan University of Science and Technology, Irbid, Jordan
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Wu YE, Zheng YY, Li QY, Yao BF, Cao J, Liu HX, Hao GX, van den Anker J, Zheng Y, Zhao W. Model-informed drug development in pediatric, pregnancy and geriatric drug development: States of the art and future. Adv Drug Deliv Rev 2024; 211:115364. [PMID: 38936664 DOI: 10.1016/j.addr.2024.115364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 06/09/2024] [Accepted: 06/19/2024] [Indexed: 06/29/2024]
Abstract
The challenges of drug development in pediatric, pregnant and geriatric populations are a worldwide concern shared by regulatory authorities, pharmaceutical companies, and healthcare professionals. Model-informed drug development (MIDD) can integrate and quantify real-world data of physiology, pharmacology, and disease processes by using modeling and simulation techniques to facilitate decision-making in drug development. In this article, we reviewed current MIDD policy updates, reflected on the integrity of physiological data used for MIDD and the effects of physiological changes on the drug PK, as well as summarized current MIDD strategies and applications, so as to present the state of the art of MIDD in pediatric, pregnant and geriatric populations. Some considerations are put forth for the future improvements of MIDD including refining regulatory considerations, improving the integrity of physiological data, applying the emerging technologies, and exploring the application of MIDD in new therapies like gene therapies for special populations.
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Affiliation(s)
- Yue-E Wu
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yuan-Yuan Zheng
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Qiu-Yue Li
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Bu-Fan Yao
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Jing Cao
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Hui-Xin Liu
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Guo-Xiang Hao
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - John van den Anker
- Division of Clinical Pharmacology, Children's National Medical Center, Washington, DC, USA; Departments of Pediatrics, Pharmacology & Physiology, George Washington University, School of Medicine and Health Sciences, Washington, DC, USA; Department of Paediatric Pharmacology and Pharmacometrics, University Children's Hospital Basel, Basel, Switzerland
| | - Yi Zheng
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Wei Zhao
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
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Johnson TN, Batchelor HK, Goelen J, Horniblow RD, Dinh J. Combining data on the bioavailability of midazolam and physiologically-based pharmacokinetic modeling to investigate intestinal CYP3A4 ontogeny. CPT Pharmacometrics Syst Pharmacol 2024. [PMID: 38923249 DOI: 10.1002/psp4.13192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 06/06/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024] Open
Abstract
Pediatric physiologically-based modeling in drug development has grown in the past decade and optimizing the underlying systems parameters is important in relation to overall performance. In this study, variation of clinical oral bioavailability of midazolam as a function of age is used to assess the underlying ontogeny models for intestinal CYP3A4. Data on midazolam bioavailability in adults and children and different ontogeny patterns for intestinal CYP3A4 were first collected from the literature. A pediatric PBPK model was then used to assess six different ontogeny models in predicting bioavailability from preterm neonates to adults. The average fold error ranged from 0.7 to 1.38, with the rank order of least to most biased model being No Ontogeny < Upreti = Johnson < Goelen < Chen < Kiss. The absolute average fold error ranged from 1.17 to 1.64 with the rank order of most to least precise being Johnson > Upreti > No Ontogeny > Goelen > Kiss > Chen. The optimal ontogeny model is difficult to discern when considering the possible influence of CYP3A5 and other population variability; however, this study suggests that from term neonates and older a faster onset Johnson model with a lower fraction at birth may be close to this. For inclusion in other PBPK models, independent verification will be needed to confirm these results. Further research is needed in this area both in terms of age-related changes in midazolam and similar drug bioavailability and intestinal CYP3A4 ontogeny.
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Affiliation(s)
| | - Hannah K Batchelor
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK
| | - Jan Goelen
- Centre for Neonatal and Paediatric Infection, Antimicrobial Resistance Research Group, St George's, University of London, London, UK
| | - Richard D Horniblow
- School of Biomedical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
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Allegaert K, Smits A, Annaert P. Interdisciplinary Collaboration on Real World Data to Close the Knowledge Gap: A Reflection on "De Sutter et al. Predicting Volume of Distribution in Neonates: Performance of Physiologically Based Pharmacokinetic Modelling". Pharmaceutics 2024; 16:128. [PMID: 38276498 PMCID: PMC10819087 DOI: 10.3390/pharmaceutics16010128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 12/28/2023] [Accepted: 01/16/2024] [Indexed: 01/27/2024] Open
Abstract
This commentary further reflects on the paper of De Sutter et al. on predicting volume of distribution in neonates, and the performance of physiologically based pharmacokinetic models We hereby stressed the add on value to collaborate on real world data to further close this knowledge gap. We illustrated this by weight distribution characteristics in breastfed (physiology) and in asphyxiated (pathophysiology), with additional reflection on their kidney and liver function.
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Affiliation(s)
- Karel Allegaert
- Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
- Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium;
- Department of Hospital Pharmacy, Erasmus University Medical Center, 3000 CA Rotterdam, The Netherlands
| | - Anne Smits
- Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium;
- Neonatal Intensive Care Unit, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Pieter Annaert
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium;
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de Hoop-Sommen MA, van der Heijden JEM, Freriksen JJM, Greupink R, de Wildt SN. Pragmatic physiologically-based pharmacokinetic modeling to support clinical implementation of optimized gentamicin dosing in term neonates and infants: proof-of-concept. Front Pediatr 2023; 11:1288376. [PMID: 38078320 PMCID: PMC10702772 DOI: 10.3389/fped.2023.1288376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 11/02/2023] [Indexed: 02/12/2024] Open
Abstract
Introduction Modeling and simulation can support dosing recommendations for clinical practice, but a simple framework is missing. In this proof-of-concept study, we aimed to develop neonatal and infant gentamicin dosing guidelines, supported by a pragmatic physiologically-based pharmacokinetic (PBPK) modeling approach and a decision framework for implementation. Methods An already existing PBPK model was verified with data of 87 adults, 485 children and 912 neonates, based on visual predictive checks and predicted-to-observed pharmacokinetic (PK) parameter ratios. After acceptance of the model, dosages now recommended by the Dutch Pediatric Formulary (DPF) were simulated, along with several alternative dosing scenarios, aiming for recommended peak (i.e., 8-12 mg/L for neonates and 15-20 mg/L for infants) and trough (i.e., <1 mg/L) levels. We then used a decision framework to weigh benefits and risks for implementation. Results The PBPK model adequately described gentamicin PK. Simulations of current DPF dosages showed that the dosing interval for term neonates up to 6 weeks of age should be extended to 36-48 h to reach trough levels <1 mg/L. For infants, a 7.5 mg/kg/24 h dose will reach adequate peak levels. The benefits of these dose adaptations outweigh remaining uncertainties which can be minimized by routine drug monitoring. Conclusion We used a PBPK model to show that current DPF dosages for gentamicin in term neonates and infants needed to be optimized. In the context of potential uncertainties, the risk-benefit analysis proved positive; the model-informed dose is ready for clinical implementation.
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Affiliation(s)
- Marika A. de Hoop-Sommen
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, Netherlands
| | - Joyce E. M. van der Heijden
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, Netherlands
| | - Jolien J. M. Freriksen
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, Netherlands
| | - Rick Greupink
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, Netherlands
| | - Saskia N. de Wildt
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, Netherlands
- Department for Intensive Care, Radboud University Medical Center, Nijmegen, Netherlands
- Intensive Care and Pediatric Surgery, Erasmus MC, Rotterdam, Netherlands
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Dinh J, Johnson TN, Grimstein M, Lewis T. Physiologically Based Pharmacokinetics Modeling in the Neonatal Population-Current Advances, Challenges, and Opportunities. Pharmaceutics 2023; 15:2579. [PMID: 38004559 PMCID: PMC10675397 DOI: 10.3390/pharmaceutics15112579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/24/2023] [Accepted: 10/29/2023] [Indexed: 11/26/2023] Open
Abstract
Physiologically based pharmacokinetic (PBPK) modeling is an approach to predicting drug pharmacokinetics, using knowledge of the human physiology involved and drug physiochemical properties. This approach is useful when predicting drug pharmacokinetics in under-studied populations, such as pediatrics. PBPK modeling is a particularly important tool for dose optimization for the neonatal population, given that clinical trials rarely include this patient population. However, important knowledge gaps exist for neonates, resulting in uncertainty with the model predictions. This review aims to outline the sources of variability that should be considered with developing a neonatal PBPK model, the data that are currently available for the neonatal ontogeny, and lastly to highlight the data gaps where further research would be needed.
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Affiliation(s)
- Jean Dinh
- Certara UK Limited, Sheffield S1 2BJ, UK; (J.D.); (T.N.J.)
| | | | - Manuela Grimstein
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD 20903, USA
| | - Tamorah Lewis
- Pediatric Clinical Pharmacology & Toxicology, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
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De Sutter PJ, Rossignol P, Breëns L, Gasthuys E, Vermeulen A. Predicting Volume of Distribution in Neonates: Performance of Physiologically Based Pharmacokinetic Modelling. Pharmaceutics 2023; 15:2348. [PMID: 37765316 PMCID: PMC10536587 DOI: 10.3390/pharmaceutics15092348] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 09/12/2023] [Accepted: 09/17/2023] [Indexed: 09/29/2023] Open
Abstract
The volume of distribution at steady state (Vss) in neonates is still often estimated through isometric scaling from adult values, disregarding developmental changes beyond body weight. This study aimed to compare the accuracy of two physiologically based pharmacokinetic (PBPK) Vss prediction methods in neonates (Poulin & Theil with Berezhkovskiy correction (P&T+) and Rodgers & Rowland (R&R)) with isometrical scaling. PBPK models were developed for 24 drugs using in-vitro and in-silico data. Simulations were done in Simcyp (V22) using predefined populations. Clinical data from 86 studies in neonates (including preterms) were used for comparison, and accuracy was assessed using (absolute) average fold errors ((A)AFEs). Isometric scaling resulted in underestimated Vss values in neonates (AFE: 0.61), and both PBPK methods reduced the magnitude of underprediction (AFE: 0.82-0.83). The P&T+ method demonstrated superior overall accuracy compared to isometric scaling (AAFE of 1.68 and 1.77, respectively), while the R&R method exhibited lower overall accuracy (AAFE: 2.03). Drug characteristics (LogP and ionization type) and inclusion of preterm neonates did not significantly impact the magnitude of error associated with isometric scaling or PBPK modeling. These results highlight both the limitations and the applicability of PBPK methods for the prediction of Vss in the absence of clinical data.
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Alsmadi MM. Evaluating the Pharmacokinetics of Fentanyl in the Brain Extracellular Fluid, Saliva, Urine, and Plasma of Newborns from Transplacental Exposure from Parturient Mothers Dosed with Epidural Fentanyl Utilizing PBPK Modeling. Eur J Drug Metab Pharmacokinet 2023; 48:567-586. [PMID: 37563443 DOI: 10.1007/s13318-023-00842-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/26/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND AND OBJECTIVE Fentanyl can mitigate the mother and newborn complications resulting from labor pain. However, fentanyl shows a narrow therapeutic index between its respiratory depressive and analgesic effects. Thus, prenatally acquired high fentanyl levels in the newborn brain extracellular fluid (bECF) may induce respiratory depression which requires therapeutic drug monitoring (TDM). TDM using saliva and urine in newborns can reduce the possibility of infections and distress associated with TDM using blood. The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict fentanyl concentrations in different newborn tissues due to intrauterine exposure. METHODS A fentanyl PBPK model in adults after intravenous and epidural administration was built, validated, and scaled to pregnancy and newborn populations. The dose that the newborn received transplacentally at birth was calculated using the pregnancy model. Then, the newborn bECF, saliva, plasma, and urine concentrations after such a dose were predicted using the newborn PBPK model. RESULTS After a maternal epidural dose of fentanyl 245 µg, the predicted newborn plasma and bECF levels were below the toxicity thresholds. Furthermore, the salivary threshold levels in newborns for fentanyl analgesic and respiratory depression effects were estimated to be 0.39 and 14.7-18.2 ng/ml, respectively. CONCLUSION The salivary TDM of fentanyl in newborns can be useful in newborns exposed to intrauterine exposure from parturient females dosed with epidural fentanyl. However, newborn-specific values of µ-opioid receptors IC50 for respiratory depression are needed.
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Affiliation(s)
- Mo'tasem M Alsmadi
- Department of Pharmaceutical Technology, Faculty of Pharmacy, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
- Nanotechnology Institute, Jordan University of Science and Technology, Irbid, Jordan.
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Algharably EA, Kreutz R, Gundert-Remy U. Infant Exposure to Antituberculosis Drugs via Breast Milk and Assessment of Potential Adverse Effects in Breastfed Infants: Critical Review of Data. Pharmaceutics 2023; 15:pharmaceutics15041228. [PMID: 37111713 PMCID: PMC10143885 DOI: 10.3390/pharmaceutics15041228] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/04/2023] [Accepted: 04/07/2023] [Indexed: 04/29/2023] Open
Abstract
Infants of mothers treated for tuberculosis might be exposed to drugs via breast milk. The existing information on the exposure of breastfed infants lacks a critical review of the published data. We aimed to evaluate the quality of the existing data on antituberculosis (anti-TB) drug concentrations in the plasma and milk as a methodologically sound basis for the potential risk of breastfeeding under therapy. We performed a systematic search in PubMed for bedaquiline, clofazimine, cycloserine/terizidone, levofloxacin, linezolid, pretomanid/pa824, pyrazinamide, streptomycin, ethambutol, rifampicin and isoniazid, supplemented with update references found in LactMed®. We calculated the external infant exposure (EID) for each drug and compared it with the recommended WHO dose for infants (relative external infant dose) and assessed their potential to elicit adverse effects in the breastfed infant. Breast milk concentration data were mainly not satisfactory to properly estimate the EID. Most of the studies suffer from limitations in the sample collection, quantity, timing and study design. Infant plasma concentrations are extremely scarce and very little data exist documenting the clinical outcome in exposed infants. Concerns for potential adverse effects in breastfed infants could be ruled out for bedaquiline, cycloserine/terizidone, linezolid and pyrazinamide. Adequate studies should be performed covering the scenario in treated mothers, breast milk and infants.
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Affiliation(s)
- Engi Abdelhady Algharably
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Clinical Pharmacology and Toxicology, Charitéplatz 1, 10117 Berlin, Germany
| | - Reinhold Kreutz
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Clinical Pharmacology and Toxicology, Charitéplatz 1, 10117 Berlin, Germany
| | - Ursula Gundert-Remy
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Clinical Pharmacology and Toxicology, Charitéplatz 1, 10117 Berlin, Germany
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Alsmadi MM, Idkaidek N. The Analysis of Pethidine Pharmacokinetics in Newborn Saliva, Plasma, and Brain Extracellular Fluid After Prenatal Intrauterine Exposure from Pregnant Mothers Receiving Intramuscular Dose Using PBPK Modeling. Eur J Drug Metab Pharmacokinet 2023; 48:281-300. [PMID: 37017867 DOI: 10.1007/s13318-023-00823-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2023] [Indexed: 04/06/2023]
Abstract
BACKGROUND AND OBJECTIVE Pethidine (meperidine) can decrease labor pain-associated mother's hyperventilation and high cortisol-induced newborn complications. However, prenatal transplacentally acquired pethidine can cause side effects in newborns. High pethidine concentrations in the newborn brain extracellular fluid (bECF) can cause a serotonin crisis. Therapeutic drug monitoring (TDM) in newborns' blood distresses them and increases infection incidence, which can be overcome by using salivary TDM. Physiologically based pharmacokinetic (PBPK) modeling can predict drug concentrations in newborn plasma, saliva, and bECF after intrauterine pethidine exposure. METHODS A healthy adult PBPK model was constructed, verified, and scaled to newborn and pregnant populations after intravenous and intramuscular pethidine administration. The pregnancy PBPK model was used to predict the newborn dose received transplacentally at birth, which was used as input to the newborn PBPK model to predict newborn plasma, saliva, and bECF pethidine concentrations and set correlation equations between them. RESULTS Pethidine can be classified as a Salivary Excretion Classification System class II drug. The developed PBPK model predicted that, after maternal pethidine intramuscular doses of 100 mg and 150 mg, the newborn plasma and bECF concentrations were below the toxicity thresholds. Moreover, it was estimated that newborn saliva concentrations of 4.7 µM, 11.4 µM, and 57.7 µM can be used as salivary threshold concentrations for pethidine analgesic effects, side effects, and the risk for serotonin crisis, respectively, in newborns. CONCLUSION It was shown that saliva can be used for pethidine TDM in newborns during the first few days after delivery to mothers receiving pethidine.
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Affiliation(s)
- Mo'tasem M Alsmadi
- Department of Pharmaceutical Technology, Faculty of Pharmacy, Jordan University of Science and Technology, P.O.Box 3030, Irbid, 22110, Jordan.
- Nanotechnology Institute, Jordan University of Science and Technology, P.O.Box 3030, Irbid, 22110, Jordan.
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Freriksen JJM, van der Heijden JEM, de Hoop-Sommen MA, Greupink R, de Wildt SN. Physiologically Based Pharmacokinetic (PBPK) Model-Informed Dosing Guidelines for Pediatric Clinical Care: A Pragmatic Approach for a Special Population. Paediatr Drugs 2023; 25:5-11. [PMID: 36201128 PMCID: PMC9534738 DOI: 10.1007/s40272-022-00535-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/05/2022] [Indexed: 01/06/2023]
Abstract
Physiologically based pharmacokinetic (PBPK) modeling can be an attractive tool to increase the evidence base of pediatric drug dosing recommendations by making optimal use of existing pharmacokinetic (PK) data. A pragmatic approach of combining available compound models with a virtual pediatric physiology model can be a rational solution to predict PK and hence support dosing guidelines for children in real-life clinical care, when it can also be employed by individuals with little experience in PBPK modeling. This comes within reach as user-friendly PBPK modeling platforms exist and, for many drugs and populations, models are ready for use. We have identified a list of drugs that can serve as a starting point for pragmatic PBPK modeling to address current clinical dosing needs.
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Affiliation(s)
- Jolien J M Freriksen
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Joyce E M van der Heijden
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marika A de Hoop-Sommen
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Rick Greupink
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Saskia N de Wildt
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
- Intensive Care and Department of Pediatrics Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
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Bouazza N, Dokoumetzidis A, Knibbe CAJ, de Wildt SN, Ambery C, De Cock PA, Gasthuys E, Foissac F, Urien S, Hamberg AK, Poggesi I, Zhao W, Vermeulen A, Standing JF, Tréluyer JM. General clinical and methodological considerations on the extrapolation of pharmacokinetics and optimization of study protocols for small molecules and monoclonal antibodies in children. Br J Clin Pharmacol 2022; 88:4985-4996. [PMID: 36256514 DOI: 10.1111/bcp.15571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 09/05/2022] [Accepted: 09/20/2022] [Indexed: 12/01/2022] Open
Abstract
Pharmacometric modelling plays a key role in both the design and analysis of regulatory trials in paediatric drug development. Studies in adults provide a rich source of data to inform the paediatric investigation plans, including knowledge on drug pharmacokinetics (PK), safety and efficacy. In children, drug disposition differs widely from birth to adolescence but extrapolating adult to paediatric PK, safety and efficacy either with pharmacometric or physiologically based approaches can help design or in some cases reduce the need for clinical studies. Aspects to consider when extrapolating PK include the maturation of drug metabolizing enzyme expression, glomerular filtration, drug excretory systems, and the expression and activity of specific transporters in conjunction with other drug properties such as fraction unbound. Knowledge of these can be used to develop extrapolation tools such as allometric scaling plus maturation functions or physiologically based PK. PK/pharmacodynamic approaches and well-designed clinical trials in children are of key importance in paediatric drug development. In this white paper, state-of-the-art of current methods used for paediatric extrapolation will be discussed. This paper is part of a conect4children implementation of innovative methodologies including pharmacometric and physiologically based PK modelling in clinical trial design/paediatric drug development through dissemination of expertise and expert advice. The suggestions arising from this white paper should define a minimum set of standards in paediatric modelling and contribute to the regulatory science.
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Affiliation(s)
- Naïm Bouazza
- Pediatric and Perinatal Drug Evaluation and Pharmacology, Université Paris Cité, Paris, France.,Unité de Recherche Clinique Université Paris Cité Necker-Cochin, AP-HP, Paris, France.,CIC-1419 Inserm, Cochin-Necker, Paris, France
| | | | - Catherijne A J Knibbe
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.,Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - Saskia N de Wildt
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.,Department of Intensive Care and Paediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Claire Ambery
- Clinical Pharmacology Modelling and Simulation, GlaxoSmithKline plc, London, UK
| | - Pieter A De Cock
- Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium.,Department of Pharmacy, Ghent University Hospital, Ghent, Belgium.,Department of Pediatric Intensive Care, Ghent University Hospital, Ghent, Belgium
| | - Elke Gasthuys
- Department of Bioanalysis, Faculty of Pharmaceutical Sciences, University of Ghent, Ghent, Belgium
| | - Frantz Foissac
- Pediatric and Perinatal Drug Evaluation and Pharmacology, Université Paris Cité, Paris, France.,Unité de Recherche Clinique Université Paris Cité Necker-Cochin, AP-HP, Paris, France.,CIC-1419 Inserm, Cochin-Necker, Paris, France
| | - Saïk Urien
- Pediatric and Perinatal Drug Evaluation and Pharmacology, Université Paris Cité, Paris, France.,Unité de Recherche Clinique Université Paris Cité Necker-Cochin, AP-HP, Paris, France.,CIC-1419 Inserm, Cochin-Necker, Paris, France
| | - Anna-Karin Hamberg
- Department of Clinical Pharmacology, Uppsala University Hospital, Uppsala, Sweden
| | - Italo Poggesi
- Clinical Pharmacology and Pharmacometrics, Janssen Research & Development, Beerse, Belgium
| | - Wei Zhao
- Department of Clinical Pharmacy, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.,Department of Pharmacy, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China.,Clinical Research Centre, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - An Vermeulen
- Department of Bioanalysis, Faculty of Pharmaceutical Sciences, University of Ghent, Ghent, Belgium
| | - Joseph F Standing
- Infection, Inflammation and Immunology, UCL Great Ormond Street Institute of Child Health, London, UK.,Department of Pharmacy, Great Ormond Street Hospital for Children, London, UK
| | - Jean-Marc Tréluyer
- Pediatric and Perinatal Drug Evaluation and Pharmacology, Université Paris Cité, Paris, France.,Unité de Recherche Clinique Université Paris Cité Necker-Cochin, AP-HP, Paris, France.,CIC-1419 Inserm, Cochin-Necker, Paris, France
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13
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Dai HR, Liu Y, Lu KY, He X, Guo HL, Hu YH, Xu J, Ding XS, Chen F, Cheng R, Jiao Z. Population pharmacokinetic modeling of caffeine in preterm infants with apnea of prematurity: New findings from concomitant erythromycin and AHR genetic polymorphisms. Pharmacol Res 2022; 184:106416. [PMID: 36029933 DOI: 10.1016/j.phrs.2022.106416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/04/2022] [Accepted: 08/21/2022] [Indexed: 11/26/2022]
Abstract
Current standard-dose caffeine therapy results in significant intersubject variability. The aims of this study were to develop and evaluate population pharmacokinetic (PPK) models of caffeine in preterm infants through comprehensive screening of covariates and then to propose model-informed precision dosing of caffeine for this population. A total of 129 caffeine concentrations from 96 premature neonates were incorporated into this study. Comprehensive medical record and genotype data of these neonates were collected for analysis. PPK modeling was performed by a nonlinear mixed effects modeling program (NONMEM). Final models based on the current weight (CW) or body surface area (BSA) were evaluated via multiple graphic and statistical methods. The model-informed dosing regimen was performed through Monte Carlo simulations. In addition to CW or BSA, postnatal age, coadministration with erythromycin (ERY), and aryl hydrocarbon receptor coding gene (AHR) variant (rs2158041) were incorporated into the final PPK models. Multiple evaluation results showed satisfactory prediction performance and stability of the CW- and BSA-based models. Monte Carlo simulations demonstrated that trough concentrations of caffeine in preterm infants would be affected by concomitant ERY therapy and rs2158041 under varying dose regimens. For the first time, ERY and rs2158041 were found to be associated with the clearance of caffeine in premature infants. Similar predictive performance and stability were obtained for both CW- and BSA-based PPK models. These findings provide novel insights into caffeine precision therapy for preterm infants.
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Affiliation(s)
- Hao-Ran Dai
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing 210008, China; School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, China
| | - Yun Liu
- Neonatal Intensive Care Unit, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - Ke-Yu Lu
- Neonatal Intensive Care Unit, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - Xin He
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - Hong-Li Guo
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - Ya-Hui Hu
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - Jing Xu
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - Xuan-Sheng Ding
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, China
| | - Feng Chen
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing 210008, China.
| | - Rui Cheng
- Neonatal Intensive Care Unit, Children's Hospital of Nanjing Medical University, Nanjing 210008, China.
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, China.
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14
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Allegaert K, Abbasi MY, Annaert P, Olafuyi O. Current and future physiologically based pharmacokinetic (PBPK) modeling approaches to optimize pharmacotherapy in preterm neonates. Expert Opin Drug Metab Toxicol 2022; 18:301-312. [PMID: 35796504 DOI: 10.1080/17425255.2022.2099836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION There is a need for structured approaches to inform on pharmacotherapy in preterm neonates. With their proven track record up to regulatory acceptance, physiologically based pharmacokinetic (PBPK) modeling and simulation provide such a structured approach, and hold the promise to support drug development in preterm neonates. AREAS COVERED Compared to the general and pediatric use of PBPK modeling, its use to inform pharmacotherapy in preterms is limited. Using a systematic search (PBPK + preterm), we retained 25 records (20 research papers, 2 letters, 3 abstracts). We subsequently collated the published information on PBPK software packages (PK-Sim®, Simcyp®), and their applications and optimization efforts in preterm neonates. It is encouraging that these applications cover a broad range of scenarios (pharmacokinetic-dynamic analyses, drug-drug interactions, developmental pharmacogenetics, lactation related exposure) and compounds (small molecules, proteins). Furthermore, specific compartments (cerebrospinal fluid, tissue) or (patho)physiologic processes (cardiac output, biliary excretion, first pass metabolism) are considered. EXPERT OPINION Knowledge gaps exist, giving rise to various levels of model uncertainty in PBPK applications in preterm neonates. To improve this setting, we need cross talk between clinicians and modelers to generate and integrate knowledge (PK datasets, system knowledge, maturational physiology and pathophysiology) to further refine PBPK models.
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Affiliation(s)
- Karel Allegaert
- Department of Pharmaceutical and Pharmacological Sciences.,Department of Development and Regeneration, and.,Leuven Child and Youth Institute, KU Leuven, Leuven Belgium.,Department of Clinical Pharmacy, Erasmus MC, Rotterdam, the Netherlands
| | - Mohammad Yaseen Abbasi
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Pieter Annaert
- Department of Pharmaceutical and Pharmacological Sciences
| | - Olusola Olafuyi
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
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15
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Yamada T, Emoto C, Fukuda T, Motomura Y, Inoue H, Ohga S, Ieiri I. Optimal Teicoplanin Dosing Regimen in Neonates and Children Developed by Leveraging Real-World Clinical Information. Ther Drug Monit 2022; 44:404-413. [PMID: 34629445 DOI: 10.1097/ftd.0000000000000930] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 09/15/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Teicoplanin is a glycopeptide antibiotic used for the treatment of methicillin-resistant Staphylococcus aureus infections. To ensure successful target attainment, therapeutic drug monitoring-informed dosage adjustment is recommended. However, it relies on the experience of the clinician and the frequency of drug measurements. This study aimed to design a new optimal dosing regimen of teicoplanin with a maintenance dosing strategy for neonates and children based on their physiological characteristics. METHODS Data from teicoplanin-treated patients (n = 214) were collected from electronic medical records. Covariate analyses were performed using population pharmacokinetic (PK) modeling with 399 serum teicoplanin concentrations from 48 neonates and 166 children. Multiple PK simulations were conducted to explore optimal dosing regimens that would allow control of the trough concentration to the target of 15-30 mg/L quicker than the current standard regimen. RESULTS Allometrically scaled body weight, postmenstrual age (PMA), renal function, and serum albumin were implemented as substantial covariates for teicoplanin clearance in a two-compartment PK model. Covariate analyses and comprehensive simulation assessments recommended the following modifications to the current regimen: (1) decreased dose for premature babies (PMA ≤28 weeks), (2) decreased dose for children with renal dysfunction, and (3) increased dose for children (0.5-11 years) with an estimated glomerular filtration rate of ≥90 mL/min/1.73 m2. CONCLUSIONS This study leverages real-world clinical information and proposes new optimal dosing regimens for teicoplanin in neonates and children through PK modeling and simulation analyses, taking into account the age, including PMA, and renal function of patients.
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Affiliation(s)
- Takaaki Yamada
- Department of Pharmacy, Kyushu University Hospital, Fukuoka, Japan
| | - Chie Emoto
- Laboratory of Drug Metabolism and Pharmacokinetics, Showa Pharmaceutical University
| | - Tsuyoshi Fukuda
- Laboratory of Drug Metabolism and Pharmacokinetics, Showa Pharmaceutical University
- National Center for Child Health and Development, Tokyo, Japan; and
| | - Yoshitomo Motomura
- Department of Pediatrics, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hirosuke Inoue
- Department of Pediatrics, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shouichi Ohga
- Department of Pediatrics, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Ichiro Ieiri
- Department of Pharmacy, Kyushu University Hospital, Fukuoka, Japan
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16
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Abstract
To truly attain effective and safe pharmacotherapy, the similarities and dissimilarities in physiology between micro-preemies and extreme preterm infants should be explored. The higher incidence of pulmonary hypertension and presence of adrenal insufficiency of prematurity in micro-preemies hereby serve as illustrations. The current limited data on pharmacokinetics, -dynamics and safety reflect the obvious need to collect such data, and to tailor modelling tools to their physiology and needs. Drug utilization hereby mirrors different needs and practices and may serve to guide prioritization decisions. Physiological data, combined with even limited observations on pharmacokinetics and -dynamics can be translated to effective modelling tools to attain effective and safe pharmacotherapy. We therefore discuss how valid research tools in pharmacology like physiology-based pharmacokinetic models can be developed, and how clinicians can contribute to such efforts, with the overarching aim to enable this shift from immature pharmacotherapy to pharmacotherapy for the immature.
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17
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Wu Y, Allegaert K, Flint RB, Simons SHP, Krekels EHJ, Knibbe CAJ, Völler S. Prediction of glomerular filtration rate maturation across preterm and term neonates and young infants using inulin as marker. AAPS J 2022; 24:38. [PMID: 35212832 DOI: 10.1208/s12248-022-00688-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 01/30/2022] [Indexed: 11/30/2022] Open
Abstract
Describing glomerular filtration rate (GFR) maturation across the heterogeneous population of preterm and term neonates and infants is important to predict the clearance of renally cleared drugs. This study aims to describe the GFR maturation in (pre)term neonates and young infants (PNA < 90 days) using individual inulin clearance data (CLinulin). To this end, published GFR maturation models were evaluated by comparing their predicted GFR with CLinulin retrieved from literature. The best model was subsequently optimized in NONMEM V7.4.3 to better fit the CLinulin values. Our study evaluated seven models and collected 381 individual CLinulin values from 333 subjects with median (range) birthweight (BWb) 1880 g (580-4950), gestational age (GA) 34 weeks (25-43), current weight (CW) 1890 g (480-6200), postnatal age (PNA) 3 days (0-75), and CLinulin 2.20 ml/min (0.43-17.90). The De Cock 2014 model (covariates: BWb and PNA) performed the best in predicting CLinulin, followed by the Rhodin 2009 model (covariates: CW and postmenstrual age). The final optimized model shows that GFR at birth is determined by BWb, thereafter the maturation rate of GFR is dependent on PNA and GA, with a higher GA showing an overall faster maturation. To conclude, using individual CLinulin data, we found that a model for neonatal GFR requires a distinction between prenatal maturation quantified by BWb and postnatal maturation. To capture postnatal GFR maturation in (pre)term neonates and young infants, we developed an optimized model in which PNA-related maturation was dependent on GA.
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Affiliation(s)
- Yunjiao Wu
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Karel Allegaert
- Department of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands.,Departments of Development and Regeneration and Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Robert B Flint
- Department of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands.,Department of Pediatrics, Division of Neonatology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Sinno H P Simons
- Department of Pediatrics, Division of Neonatology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Elke H J Krekels
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Catherijne A J Knibbe
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.,Department of Pediatrics, Division of Neonatology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands.,Department of Clinical Pharmacy, St Antonius Hospital, Nieuwegein, The Netherlands
| | - Swantje Völler
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands. .,Department of Pediatrics, Division of Neonatology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands. .,Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
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18
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Abduljalil K, Pansari A, Ning J, Jamei M. Prediction of Maternal and Fetal Acyclovir, Emtricitabine, Lamivudine, and Metformin Concentrations during Pregnancy Using a Physiologically Based Pharmacokinetic Modeling Approach. Clin Pharmacokinet 2022; 61:725-748. [DOI: 10.1007/s40262-021-01103-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/16/2021] [Indexed: 12/20/2022]
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19
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van Rongen A, Krekels EH, Calvier EA, de Wildt SN, Vermeulen A, Knibbe CA. An update on the use of allometric and other scaling methods to scale drug clearance in children: towards decision tables. Expert Opin Drug Metab Toxicol 2022; 18:99-113. [PMID: 35018879 DOI: 10.1080/17425255.2021.2027907] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION When pediatric data are not available for a drug, allometric and other methods are applied to scale drug clearance across the pediatric age-range from adult values. This is applied when designing first-in-child studies, but also for off-label drug prescription. AREAS COVERED This review provides an overview of the systematic accuracy of allometric and other pediatric clearance scaling methods compared to gold-standard PBPK predictions. The findings are summarized in decision tables to provide a priori guidance on the selection of appropriate pediatric clearance scaling methods for both novel drugs for which no pediatric data are available and existing drugs in clinical practice. EXPERT OPINION While allometric scaling principles are commonly used to scale pediatric clearance, there is no universal allometric exponent (i.e., 1, 0.75 or 0.67) that can accurately scale clearance for all drugs from adults to children of all ages. Therefore, pediatric scaling decision tables based on age, drug elimination route, binding plasma protein, fraction unbound, extraction ratio, and/or isoenzyme maturation are proposed to a priori select the appropriate (allometric) clearance scaling method, thereby reducing the need for full PBPK-based clearance predictions. Guidance on allometric scaling when estimating pediatric clearance values is provided as well.
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Affiliation(s)
- Anne van Rongen
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Elke Hj Krekels
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Elisa Am Calvier
- Sanofi Pharmacokinetics-Dynamics and Metabolism (PKDM), Translational Medicine and Early Development, Sanofi R&D, Montpellier, France
| | - Saskia N de Wildt
- Department of Pharmacology and Toxicology, Radboud University Medical Center, Nijmegen, The Netherlands.,Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - An Vermeulen
- Laboratory of Medical Biochemistry and Clinical Analysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium.,Janssen R&D, a division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Catherijne Aj Knibbe
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.,Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands
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20
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van der Heijden JEM, Freriksen JJM, de Hoop-Sommen MA, van Bussel LPM, Driessen SHP, Orlebeke AEM, Verscheijden LFM, Greupink R, de Wildt SN. Feasibility of a Pragmatic PBPK Modeling Approach: Towards Model-Informed Dosing in Pediatric Clinical Care. Clin Pharmacokinet 2022; 61:1705-1717. [PMID: 36369327 PMCID: PMC9651907 DOI: 10.1007/s40262-022-01181-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND AND OBJECTIVE More than half of all drugs are still prescribed off-label to children. Pharmacokinetic (PK) data are needed to support off-label dosing, however for many drugs such data are either sparse or not representative. Physiologically-based pharmacokinetic (PBPK) models are increasingly used to study PK and guide dosing decisions. Building compound models to study PK requires expertise and is time-consuming. Therefore, in this paper, we studied the feasibility of predicting pediatric exposure by pragmatically combining existing compound models, developed e.g. for studies in adults, with a pediatric and preterm physiology model. METHODS Seven drugs, with various PK characteristics, were selected (meropenem, ceftazidime, azithromycin, propofol, midazolam, lorazepam, and caffeine) as a proof of concept. Simcyp® v20 was used to predict exposure in adults, children, and (pre)term neonates, by combining an existing compound model with relevant virtual physiology models. Predictive performance was evaluated by calculating the ratios of predicted-to-observed PK parameter values (0.5- to 2-fold acceptance range) and by visual predictive checks with prediction error values. RESULTS Overall, model predicted PK in infants, children and adolescents capture clinical data. Confidence in PBPK model performance was therefore considered high. Predictive performance tends to decrease when predicting PK in the (pre)term neonatal population. CONCLUSION Pragmatic PBPK modeling in pediatrics, based on compound models verified with adult data, is feasible. A thorough understanding of the model assumptions and limitations is required, before model-informed doses can be recommended for clinical use.
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Affiliation(s)
- Joyce E. M. van der Heijden
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Jolien J. M. Freriksen
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Marika A. de Hoop-Sommen
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands ,Royal Dutch Pharmacist Association, The Hague, The Netherlands
| | - Lianne P. M. van Bussel
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Sander H. P. Driessen
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Anne E. M. Orlebeke
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Laurens F. M. Verscheijden
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Rick Greupink
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Saskia N. de Wildt
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands ,Intensive Care and Department of Paediatric Surgery, Erasmus MC-Sophia Children’s Hospital, Rotterdam, The Netherlands
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21
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Abduljalil K, Gardner I, Jamei M. Application of a Physiologically Based Pharmacokinetic Approach to Predict Theophylline Pharmacokinetics Using Virtual Non-Pregnant, Pregnant, Fetal, Breast-Feeding, and Neonatal Populations. Front Pediatr 2022; 10:840710. [PMID: 35652056 PMCID: PMC9150776 DOI: 10.3389/fped.2022.840710] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 04/11/2022] [Indexed: 12/23/2022] Open
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 (Cavg,ss) and maximum (Cmax,ss) concentration in milk at steady state. The maximum RID of 17% corresponds to an absolute infant daily dose of 1.4 ± 0.5 mg/kg/day. This dose, when administered as 0.233 mg/kg every 4 h, to resemble breastfeeding frequency, resulted in plasma concentrations as high as 3.9 (1.9-6.8) mg/L and 2.8 (1.3-5.3) (5th-95th percentiles) on day 7 in preterm (32 GW) and full-term neonatal populations.
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Affiliation(s)
| | - Iain Gardner
- Certara UK Limited (Simcyp Division), Sheffield, United Kingdom
| | - Masoud Jamei
- Certara UK Limited (Simcyp Division), Sheffield, United Kingdom
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22
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Lenoir C, Niederer A, Rollason V, Desmeules JA, Daali Y, Samer CF. Prediction of cytochromes P450 3A and 2C19 modulation by both inflammation and drug interactions using physiologically based pharmacokinetics. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2021; 11:30-43. [PMID: 34791831 PMCID: PMC8752107 DOI: 10.1002/psp4.12730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 09/16/2021] [Accepted: 10/01/2021] [Indexed: 12/22/2022]
Abstract
Xenobiotics can interact with cytochromes P450 (CYPs), resulting in drug-drug interactions, but CYPs can also contribute to drug-disease interactions, especially in the case of inflammation, which downregulates CYP activities through pretranscriptional and posttranscriptional mechanisms. Interleukin-6 (IL-6), a key proinflammatory cytokine, is mainly responsible for this effect. The aim of our study was to develop a physiologically based pharmacokinetic (PBPK) model to foresee the impact of elevated IL-6 levels in combination with drug interactions with esomeprazole on CYP3A and CYP2C19. Data from a cohort of elective hip surgery patients whose CYP3A and CYP2C19 activities were measured before and after surgery were used to validate the accurate prediction of the developed models. Successive steps were to fit models for IL-6, esomeprazole, and omeprazole and its metabolite from the literature and to validate them. The models for midazolam and its metabolite were obtained from the literature. When appropriate, a correction factor was applied to convert drug concentrations from whole blood to plasma. Mean ratios between simulated and observed areas under the curve for omeprazole/5-hydroxy omeprazole, esomeprazole, and IL-6 were 1.53, 1.06, and 0.69, respectively, indicating an accurate prediction of the developed models. The impact of IL-6 and esomeprazole on the exposure to CYP3A and CYP2C19 probe substrates and respective metabolites were correctly predicted. Indeed, the ratio between predicted and observed mean concentrations were <2 for all observations (ranging from 0.51 to 1.7). The impact of IL-6 and esomeprazole on CYP3A and CYP2C19 activities after a hip surgery were correctly predicted with the developed PBPK models.
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Affiliation(s)
- Camille Lenoir
- Division of Clinical Pharmacology and Toxicology, Department of Anaesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland
| | - Amine Niederer
- Division of Clinical Pharmacology and Toxicology, Department of Anaesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland
| | - Victoria Rollason
- Division of Clinical Pharmacology and Toxicology, Department of Anaesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Jules Alexandre Desmeules
- Division of Clinical Pharmacology and Toxicology, Department of Anaesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Youssef Daali
- Division of Clinical Pharmacology and Toxicology, Department of Anaesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Caroline Flora Samer
- Division of Clinical Pharmacology and Toxicology, Department of Anaesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Geneva, Switzerland
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23
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Abstract
Almost 50% of prescription drugs lack age-appropriate dosing guidelines and therefore are used "off-label." Only ~10% drugs prescribed to neonates and infants have been studied for safety or efficacy. Immaturity of drug metabolism in children is often associated with drug toxicity. This chapter summarizes data on the ontogeny of major human metabolizing enzymes involved in oxidation, reduction, hydrolysis, and conjugation of drugs. The ontogeny data of individual drug-metabolizing enzymes are important for accurate prediction of drug pharmacokinetics and toxicity in children. This information is critical for designing clinical studies to appropriately test pharmacological hypotheses and develop safer pediatric drugs, and to replace the long-standing practice of body weight- or surface area-normalized drug dosing. The application of ontogeny data in physiologically based pharmacokinetic model and regulatory submission are discussed.
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Olafuyi O, Abbasi MY, Allegaert K. Physiologically based pharmacokinetic modelling of acetaminophen in preterm neonates-The impact of metabolising enzyme ontogeny and reduced cardiac output. Biopharm Drug Dispos 2021; 42:401-417. [PMID: 34407204 DOI: 10.1002/bdd.2301] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 06/14/2021] [Accepted: 07/19/2021] [Indexed: 12/20/2022]
Abstract
In preterm neonates, physiologically based pharmacokinetic (PBPK) models are suited for studying the effects of maturational and non-maturational factors on the pharmacokinetics of drugs with complex age-dependent metabolic pathways like acetaminophen (APAP). The aim of this study was to determine the impact of drug metabolising enzymes ontogeny on the pharmacokinetics of APAP in preterm neonates and to study the effect of reduced cardiac output (CO) on its PK using PBPK modelling. A PBPK model for APAP was first developed and validated in adults and then scaled to paediatric age groups to account for the effect of enzyme ontogeny. In preterm neonates, CO was reduced by 10%, 20%, and 30% to determine how this might affect APAP PK in preterm neonates. In all age groups, the predicted concentration-time profiles of APAP were within 5th and 95th percentile of the clinically observed concentration-time profiles and the predicted Cmax and AUC were within 2-folds of the reported parameters in clinical studies. Sulfation accounted for most of APAP metabolism in children, with the highest contribution of 68% in preterm neonates. A reduction in CO by up to 30% did not significantly alter the clearance of APAP in preterm neonates. The model successfully incorporated the ontogeny of drug metabolising enzymes involved in APAP metabolism and adequately predicted the PK of APAP in preterm neonates. A reduction in hepatic perfusion as a result of up to 30% reduction in CO has no effect on the PK of APAP in preterm neonates.
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Affiliation(s)
- Olusola Olafuyi
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | | | - Karel Allegaert
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium.,Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.,Department of Hospital Pharmacy, Erasmus MC University Medical Center, Rotterdam, the Netherlands
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25
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Wang J, van den Anker JN, Burckart GJ. Progress in Drug Development-Pediatric Dose Selection: Workshop Summary. J Clin Pharmacol 2021; 61 Suppl 1:S13-S21. [PMID: 34185909 DOI: 10.1002/jcph.1828] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 01/30/2021] [Indexed: 12/20/2022]
Abstract
The "Pediatric Dose Selection" workshop was held in October 2020 and sponsored by the U.S. Food and Drug Administration and the University of Maryland Center for Excellence in Regulatory Science and Innovation. A summary of the presentations in the context of pediatric drug development is summarized in this article.
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Affiliation(s)
- Jian Wang
- Office of Specialty Medicine, Office of New Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - John N van den Anker
- Division of Clinical Pharmacology, Children's National Hospital, Washington, DC, USA
| | - Gilbert J Burckart
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
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26
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van den Anker J, Allegaert K. Considerations for Drug Dosing in Premature Infants. J Clin Pharmacol 2021; 61 Suppl 1:S141-S151. [PMID: 34185893 DOI: 10.1002/jcph.1884] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 04/21/2021] [Indexed: 12/13/2022]
Abstract
In premature infants, effective and safe drug therapy depends on optimal dose selection and requires a thorough understanding of the underlying disease(s) of these fragile infants as well as the pharmacokinetics and pharmacodynamics of the drugs selected to treat their diseases. Differences in gestational and postnatal age or weight are the major determinants of the observed variability in drug disposition and effect in these infants. This article presents an outline on how to translate the results of a population pharmacokinetic/pharmacodynamic study into rational dosing regimens, and how physiologically based pharmacokinetic modeling, electronic health records, and the abundantly available data of vital functions of premature infants during their stay in the neonatal intensive care unit for evaluation of their pharmacotherapy can be used to tailor the most safe and effective dose in these infants.
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Affiliation(s)
- John van den Anker
- Division of Clinical Pharmacology, Children's National Hospital, Washington, DC, USA.,Division of Paediatric Pharmacology and Pharmacometrics, University Children's Hospital Basel, University of Basel, Basel, Switzerland.,Intensive Care and Department of Pediatric Surgery, Erasmus Medical Center-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Karel Allegaert
- Department of Hospital Pharmacy, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.,Department of Development and Regeneration, KU Leuven, Leuven, Belgium.,Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
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27
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Preterm Physiologically Based Pharmacokinetic Model. Part II: Applications of the Model to Predict Drug Pharmacokinetics in the Preterm Population. Clin Pharmacokinet 2021; 59:501-518. [PMID: 31587145 DOI: 10.1007/s40262-019-00827-4] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Preterm neonates are usually not part of a traditional drug development programme, however they are frequently administered medicines. Developing modelling and simulation tools, such as physiologically based pharmacokinetic (PBPK) models that incorporate developmental physiology and maturation of drug metabolism, can be used to predict drug exposure in this group of patients, and may help to optimize drug dose adjustment. OBJECTIVE The aim of this study was to assess and verify the predictability of a preterm PBPK model using compounds that undergo diverse renal and/or hepatic clearance based on the knowledge of their disposition in adults. METHODS A PBPK model was developed in the Simcyp Simulator V17 to predict the pharmacokinetics (PK) of drugs in preterm neonates. Drug parameters for alfentanil, midazolam, caffeine, ibuprofen, gentamicin and vancomycin were collated from the literature. Predicted PK parameters and profiles were compared against the observed data. RESULTS The preterm PBPK model predicted the PK changes of the six compounds using ontogeny functions for cytochrome P450 (CYP) 1A2, CYP2C9 and CYP3A4 after oral and intravenous administrations. For gentamicin and vancomycin, the maturation of renal function was able to predict the exposure of these two compounds after intravenous administration. All PK parameter predictions were within a twofold error criteria. CONCLUSION While the developed preterm model for the prediction of PK behaviour in preterm patients is not intended to replace clinical studies, it can potentially help with deciding on first-time dosing in this population and study design in the absence of clinical data.
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28
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Yao X, Liu X, Tu S, Li X, Lei Z, Hou Z, Yu Z, Cui C, Dong Z, Salem F, Li H, Liu D. Development of a Virtual Chinese Pediatric Population Physiological Model Targeting Specific Metabolism and Kidney Elimination Pathways. Front Pharmacol 2021; 12:648697. [PMID: 34045960 PMCID: PMC8145459 DOI: 10.3389/fphar.2021.648697] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Accepted: 03/23/2021] [Indexed: 12/18/2022] Open
Abstract
Background: Physiologically based pharmacokinetic (PBPK) modeling and simulating may be a powerful tool in predicting drug behaviors in specific populations. It is a mathematical model that relates the pharmacokinetic (PK) profile of a compound with human anatomical characteristics, physiological characteristics, and biochemical parameters. Predictions using PBPK models offer a promising way to guide drug development and can be used to optimize clinical dosing regimens. However, PK data of new drugs in the pediatric population are too limited to guide clinical therapy, which may lead to frequent adverse events or insufficient efficacy for pediatric patients, particularly in neonates and infants. Objective: The objective of this study was to establish a virtual Chinese pediatric population based on the physiological parameters of Chinese children that could be utilized in PBPK models. Methods: A Chinese pediatric PBPK model was developed in Simcyp Simulator by collecting published Chinese pediatric physiological and anthropometric data to use as system parameters. This pediatric population model was then evaluated in the Chinese pediatric population by predicting the pharmacokinetic characteristics of four probe drugs: theophylline (major CYP1A2 substrate), fentanyl (major CYP3A4 substrate), vancomycin, and ceftazidime (renal-eliminated). Results: The predicted maximum concentration (Cmax), area under the curve of concentration-time (AUC), and clearance (CL) for theophylline (CYP1A2 metabolism pathway) and fentanyl (CYP3A4 metabolism pathway) were within two folds of the observed data. For drugs mainly eliminated by renal clearance (vancomycin and ceftazidime) in the Chinese pediatric population, the ratio of prediction to observation for major PK parameters was within a 2-fold error range. Conclusion: The model is a supplement to the previous Chinese population PBPK model. We anticipate the model to be a better representative of the pediatric Chinese population for drugs PK, offering greater clinical precision for medication given to the pediatric population, ultimately advancing clinical development of pediatric drugs. We can refine this model further by collecting more physiological parameters of Chinese children.
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Affiliation(s)
- Xueting Yao
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | - Xuanlin Liu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Siqi Tu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Pharmaceutical Sciences, Peking University Health Science Center, Peking University, Beijing, China
| | - Xiaobei Li
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Pharmaceutical Sciences, Peking University Health Science Center, Peking University, Beijing, China
| | - Zihan Lei
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Zhe Hou
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Zhiheng Yu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | - Cheng Cui
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | | | - Farzaneh Salem
- Certara UK Limited, Simcyp Division, Sheffield, United Kingdom
| | - Haiyan Li
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Beijing, China
| | - Dongyang Liu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
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29
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Chang HP, Kim SJ, Wu D, Shah K, Shah DK. Age-Related Changes in Pediatric Physiology: Quantitative Analysis of Organ Weights and Blood Flows. AAPS JOURNAL 2021; 23:50. [DOI: 10.1208/s12248-021-00581-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 03/11/2021] [Indexed: 02/08/2023]
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30
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Abduljalil K, Pan X, Pansari A, Jamei M, Johnson TN. Authors' Reply to Völler et al: "Comment on: Preterm Physiologically Based Pharmacokinetic Model, Part I and Part II". Clin Pharmacokinet 2021; 60:681-683. [PMID: 33713304 DOI: 10.1007/s40262-021-00995-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/28/2021] [Indexed: 11/26/2022]
Affiliation(s)
- Khaled Abduljalil
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK.
| | - Xian Pan
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK
| | - Amita Pansari
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK
| | - Masoud Jamei
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK
| | - Trevor N Johnson
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK
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31
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Völler S, Flint RB, Simons SHP, Knibbe CAJ. Comment on: "Preterm Physiologically Based Pharmacokinetic Model, Part I and Part II". Clin Pharmacokinet 2021; 60:677-679. [PMID: 33713305 PMCID: PMC8113170 DOI: 10.1007/s40262-021-00993-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/28/2021] [Indexed: 02/06/2023]
Affiliation(s)
- Swantje Völler
- Leiden Academic Centre for Drug Research, Pharmacy, Leiden University, Leiden, The Netherlands.
| | - Robert B Flint
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, The Netherlands.,Department of Hospital Pharmacy, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Sinno H P Simons
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Catherijne A J Knibbe
- Leiden Academic Centre for Drug Research, Systems Biomedicine and Pharmacology, Leiden University, Leiden, The Netherlands.,Department of Clinical Pharmacy, St Antonius Hospital, Nieuwegein, The Netherlands
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32
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Verscheijden LFM, Litjens CHC, Koenderink JB, Mathijssen RHJ, Verbeek MM, de Wildt SN, Russel FGM. Physiologically based pharmacokinetic/pharmacodynamic model for the prediction of morphine brain disposition and analgesia in adults and children. PLoS Comput Biol 2021; 17:e1008786. [PMID: 33661919 PMCID: PMC7963108 DOI: 10.1371/journal.pcbi.1008786] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 03/16/2021] [Accepted: 02/12/2021] [Indexed: 12/20/2022] Open
Abstract
Morphine is a widely used opioid analgesic, which shows large differences in clinical response in children, even when aiming for equivalent plasma drug concentrations. Age-dependent brain disposition of morphine could contribute to this variability, as developmental increase in blood-brain barrier (BBB) P-glycoprotein (Pgp) expression has been reported. In addition, age-related pharmacodynamics might also explain the variability in effect. To assess the influence of these processes on morphine effectiveness, a multi-compartment brain physiologically based pharmacokinetic/pharmacodynamic (PB-PK/PD) model was developed in R (Version 3.6.2). Active Pgp-mediated morphine transport was measured in MDCKII-Pgp cells grown on transwell filters and translated by an in vitro-in vivo extrapolation approach, which included developmental Pgp expression. Passive BBB permeability of morphine and its active metabolite morphine-6-glucuronide (M6G) and their pharmacodynamic parameters were derived from experiments reported in literature. Model simulations after single dose morphine were compared with measured and published concentrations of morphine and M6G in plasma, brain extracellular fluid (ECF) and cerebrospinal fluid (CSF), as well as published drug responses in children (1 day– 16 years) and adults. Visual predictive checks indicated acceptable overlays between simulated and measured morphine and M6G concentration-time profiles and prediction errors were between 1 and -1. Incorporation of active Pgp-mediated BBB transport into the PB-PK/PD model resulted in a 1.3-fold reduced brain exposure in adults, indicating only a modest contribution on brain disposition. Analgesic effect-time profiles could be described reasonably well for older children and adults, but were largely underpredicted for neonates. In summary, an age-appropriate morphine PB-PK/PD model was developed for the prediction of brain pharmacokinetics and analgesic effects. In the neonatal population, pharmacodynamic characteristics, but not brain drug disposition, appear to be altered compared to adults and older children, which may explain the reported differences in analgesic effect. Developmental processes in children can affect pharmacokinetics: “what the body does to the drug” as well as pharmacodynamics: “what the drug does to the body”. A typical example is morphine, of which the analgesic response is variable and particularly neonates suffer more often from respiratory depression, even when receiving doses corrected for differences in elimination. One way to mathematically incorporate developmental processes is by employing physiologically based pharmacokinetic/pharmacodynamic (PB-PK/PD) models, where physiological differences between individuals are incorporated. In this study, we developed a morphine PB-PK/PD model to predict brain drug disposition as well as analgesic response in adults and children, as both processes could potentially contribute to developmental variability in the effect of morphine. We found that age-related variation in BBB expression of the main morphine efflux transporter P-glycoprotein was not responsible for differences in brain exposure. In contrast, pharmacodynamic modelling suggested an increased sensitivity to morphine in neonates.
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Affiliation(s)
- Laurens F. M. Verscheijden
- Department of Pharmacology and Toxicology, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands
| | - Carlijn H. C. Litjens
- Department of Pharmacology and Toxicology, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands
- Department of Pharmacy, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, The Netherlands
| | - Jan B. Koenderink
- Department of Pharmacology and Toxicology, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands
| | - Ron H. J. Mathijssen
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Marcel M. Verbeek
- Departments of Neurology and Laboratory Medicine, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Saskia N. de Wildt
- Department of Pharmacology and Toxicology, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands
- Intensive Care and Department of Paediatric Surgery, Erasmus MC-Sophia Children’s Hospital, Rotterdam, The Netherlands
| | - Frans G. M. Russel
- Department of Pharmacology and Toxicology, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands
- * E-mail:
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33
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Salem F, Johnson TN, Hodgkinson ABJ, Ogungbenro K, Rostami‐Hodjegan A. Does "Birth" as an Event Impact Maturation Trajectory of Renal Clearance via Glomerular Filtration? Reexamining Data in Preterm and Full-Term Neonates by Avoiding the Creatinine Bias. J Clin Pharmacol 2020; 61:159-171. [PMID: 32885464 PMCID: PMC7818478 DOI: 10.1002/jcph.1725] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 07/30/2020] [Indexed: 12/12/2022]
Abstract
Glomerular filtration rate (GFR) is an important measure of renal function. Various models for its maturation have recently been compared; however, these have used markers, which are subject to different renal elimination processes. Inulin clearance data (a purer probe of GFR) collected from the literature were used to determine age‐related changes in GFR aspects of renal drug excretion in pediatrics. An ontogeny model was derived using a best‐fit model with various combinations of covariates such as postnatal age, gestational age at birth, and body weight. The model was applied to the prediction of systemic clearance of amikacin, gentamicin, vancomycin, and gadobutrol. During neonatal life, GFR increased as a function of both gestational age at birth and postnatal age, hence implying an impact of birth and a discrepancy in GFR for neonates with the same postmenstrual age depending on gestational age at birth (ie, neonates who were outside the womb longer had higher GFR, on average). The difference in GFR between pre‐term and full‐term neonates with the same postmenstrual age was negligible from beyond 1.25 years. Considering both postnatal age and gestational age at birth in GFR ontogeny models is important because postmenstrual age alone ignores the impact of birth. Most GFR models use covariates of body size in addition to age. Therefore, prediction from these models will also depend on the change in anthropometric characteristics with age. The latter may not be similar in various ethnic groups, and this makes the head‐to‐head comparison of models very challenging.
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Affiliation(s)
| | | | | | - Kayode Ogungbenro
- Centre for Applied Pharmacokinetic ResearchDivision of Pharmacy and OptometrySchool of Health SciencesFaculty of BiologyMedicine and HealthManchester Academic Health Science CentreUniversity of ManchesterManchesterUK
| | - Amin Rostami‐Hodjegan
- Certara UK Ltd, Simcyp DivisionSheffieldUK
- Centre for Applied Pharmacokinetic ResearchDivision of Pharmacy and OptometrySchool of Health SciencesFaculty of BiologyMedicine and HealthManchester Academic Health Science CentreUniversity of ManchesterManchesterUK
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34
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Physiologically-based pharmacokinetic models for children: Starting to reach maturation? Pharmacol Ther 2020; 211:107541. [DOI: 10.1016/j.pharmthera.2020.107541] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 03/19/2020] [Indexed: 12/13/2022]
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35
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Adiwidjaja J, Boddy AV, McLachlan AJ. Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide Optimal Dosing Regimens for Imatinib and Potential Drug Interactions in Paediatrics. Front Pharmacol 2020; 10:1672. [PMID: 32082165 PMCID: PMC7002565 DOI: 10.3389/fphar.2019.01672] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Accepted: 12/23/2019] [Indexed: 12/18/2022] Open
Abstract
Long-term use of imatinib is effective and well-tolerated in children with chronic myeloid leukaemia (CML) yet defining an optimal dosing regimen for imatinib in younger patients is a challenge. The potential interactions between imatinib and coadministered drugs in this "special" population also remains largely unexplored. This study implements a physiologically based pharmacokinetic (PBPK) modeling approach to investigate optimal dosing regimens and potential drug interactions with imatinib in the paediatric population. A PBPK model for imatinib was developed in the Simcyp Simulator (version 17) utilizing in silico, in vitro drug metabolism, and in vivo pharmacokinetic data and verified using an independent set of published clinical pharmacokinetic data. The model was then extrapolated to children and adolescents (aged 2-18 years) by incorporating developmental changes in organ size and maturation of drug-metabolising enzymes and plasma protein responsible for imatinib disposition. The PBPK model described imatinib pharmacokinetics in adult and paediatric populations and predicted drug interaction with carbamazepine, a cytochrome P450 (CYP)3A4 and 2C8 inducer, with a good accuracy (evaluated by visual inspections of the simulation results and predicted pharmacokinetic parameters that were within 1.25-fold of the clinically observed values). The PBPK simulation suggests that the optimal dosing regimen range for imatinib is 230-340 mg/m2/d in paediatrics, which is supported by the recommended initial dose for treatment of childhood CML. The simulations also highlighted that children and adults being treated with imatinib have similar vulnerability to CYP modulations. A PBPK model for imatinib was successfully developed with an excellent performance in predicting imatinib pharmacokinetics across age groups. This PBPK model is beneficial to guide optimal dosing regimens for imatinib and predict drug interactions with CYP modulators in the paediatric population.
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Affiliation(s)
- Jeffry Adiwidjaja
- Sydney Pharmacy School, The University of Sydney, Sydney, NSW, Australia
| | - Alan V. Boddy
- School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, SA, Australia
- University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, Australia
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