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Showing 1 to 12 of 32 entries
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Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model.

Frontiers in immunology

Chetty M, Li L, Rose R, Machavaram K, Jamei M, Rostami-Hodjegan A, Gardner I.
PMID: 25601866
Front Immunol. 2015 Jan 05;5:670. doi: 10.3389/fimmu.2014.00670. eCollection 2014.

Although advantages of physiologically based pharmacokinetic models (PBPK) are now well established, PBPK models that are linked to pharmacodynamic (PD) models to predict pharmacokinetics (PK), PD, and efficacy of monoclonal antibodies (mAbs) in humans are uncommon. The aim of...

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Chetty M, Li L, Rose R, et al. Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model. Front Immunol. 2015;5:670doi: 10.3389/fimmu.2014.00670.
Chetty, M., Li, L., Rose, R., Machavaram, K., Jamei, M., Rostami-Hodjegan, A., & Gardner, I. (2014). Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model. Frontiers in immunology, 5670. https://doi.org/10.3389/fimmu.2014.00670
Chetty, Manoranjenni, et al. "Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model." Frontiers in immunology vol. 5 (2014): 670. doi: https://doi.org/10.3389/fimmu.2014.00670
Chetty M, Li L, Rose R, Machavaram K, Jamei M, Rostami-Hodjegan A, Gardner I. Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model. Front Immunol. 2015 Jan 05;5:670. doi: 10.3389/fimmu.2014.00670. eCollection 2014. PMID: 25601866; PMCID: PMC4283607.
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Virtual Twins: Understanding the Data Required for Model-Informed Precision Dosing.

Clinical pharmacology and therapeutics

Polasek TM, Rostami-Hodjegan A.
PMID: 32056199
Clin Pharmacol Ther. 2020 Apr;107(4):742-745. doi: 10.1002/cpt.1778. Epub 2020 Feb 14.

No abstract available.

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Polasek TM, Rostami-Hodjegan A. Virtual Twins: Understanding the Data Required for Model-Informed Precision Dosing. Clin Pharmacol Ther. 2020;107(4):742-745doi: 10.1002/cpt.1778.
Polasek, T. M., & Rostami-Hodjegan, A. (2020). Virtual Twins: Understanding the Data Required for Model-Informed Precision Dosing. Clinical pharmacology and therapeutics, 107(4), 742-745. https://doi.org/10.1002/cpt.1778
Polasek, Thomas M, and Rostami-Hodjegan, Amin. "Virtual Twins: Understanding the Data Required for Model-Informed Precision Dosing." Clinical pharmacology and therapeutics vol. 107,4 (2020): 742-745. doi: https://doi.org/10.1002/cpt.1778
Polasek TM, Rostami-Hodjegan A. Virtual Twins: Understanding the Data Required for Model-Informed Precision Dosing. Clin Pharmacol Ther. 2020 Apr;107(4):742-745. doi: 10.1002/cpt.1778. Epub 2020 Feb 14. PMID: 32056199.
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Proteomics of colorectal cancer liver metastasis: A quantitative focus on drug elimination and pharmacodynamics effects.

British journal of clinical pharmacology

Vasilogianni AM, Al-Majdoub ZM, Achour B, Peters SA, Rostami-Hodjegan A, Barber J.
PMID: 34599518
Br J Clin Pharmacol. 2021 Oct 01; doi: 10.1111/bcp.15098. Epub 2021 Oct 01.

AIMS: This study aims to quantify drug-metabolising enzymes, transporters, receptor tyrosine kinases (RTKs) and protein markers (involved in pathways affected in cancer) in pooled healthy, histologically normal and matched cancerous liver microsomes from colorectal cancer liver metastasis (CRLM) patients.METHODS:...

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Vasilogianni AM, Al-Majdoub ZM, Achour B, et al. Proteomics of colorectal cancer liver metastasis: A quantitative focus on drug elimination and pharmacodynamics effects. Br J Clin Pharmacol. 2021;doi: 10.1111/bcp.15098.
Vasilogianni, A. M., Al-Majdoub, Z. M., Achour, B., Peters, S. A., Rostami-Hodjegan, A., & Barber, J. (2021). Proteomics of colorectal cancer liver metastasis: A quantitative focus on drug elimination and pharmacodynamics effects. British journal of clinical pharmacology, . https://doi.org/10.1111/bcp.15098
Vasilogianni, Areti-Maria, et al. "Proteomics of colorectal cancer liver metastasis: A quantitative focus on drug elimination and pharmacodynamics effects." British journal of clinical pharmacology vol. (2021). doi: https://doi.org/10.1111/bcp.15098
Vasilogianni AM, Al-Majdoub ZM, Achour B, Peters SA, Rostami-Hodjegan A, Barber J. Proteomics of colorectal cancer liver metastasis: A quantitative focus on drug elimination and pharmacodynamics effects. Br J Clin Pharmacol. 2021 Oct 01; doi: 10.1111/bcp.15098. Epub 2021 Oct 01. PMID: 34599518.
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Proteomic Quantification of Changes in Abundance of Drug-Metabolizing Enzymes and Drug Transporters in Human Liver Cirrhosis: Different Methods, Similar Outcomes.

Drug metabolism and disposition: the biological fate of chemicals

El-Khateeb E, Al-Majdoub ZM, Rostami-Hodjegan A, Barber J, Achour B.
PMID: 34045218
Drug Metab Dispos. 2021 Aug;49(8):610-618. doi: 10.1124/dmd.121.000484. Epub 2021 May 27.

Model-based assessment of the effects of liver disease on drug pharmacokinetics requires quantification of changes in enzymes and transporters responsible for drug metabolism and disposition. Different proteomic methods are currently used for protein quantification in tissues and in vitro...

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El-Khateeb E, Al-Majdoub ZM, Rostami-Hodjegan A, et al. Proteomic Quantification of Changes in Abundance of Drug-Metabolizing Enzymes and Drug Transporters in Human Liver Cirrhosis: Different Methods, Similar Outcomes. Drug Metab Dispos. 2021;49(8):610-618doi: 10.1124/dmd.121.000484.
El-Khateeb, E., Al-Majdoub, Z. M., Rostami-Hodjegan, A., Barber, J., & Achour, B. (2021). Proteomic Quantification of Changes in Abundance of Drug-Metabolizing Enzymes and Drug Transporters in Human Liver Cirrhosis: Different Methods, Similar Outcomes. Drug metabolism and disposition: the biological fate of chemicals, 49(8), 610-618. https://doi.org/10.1124/dmd.121.000484
El-Khateeb, Eman, et al. "Proteomic Quantification of Changes in Abundance of Drug-Metabolizing Enzymes and Drug Transporters in Human Liver Cirrhosis: Different Methods, Similar Outcomes." Drug metabolism and disposition: the biological fate of chemicals vol. 49,8 (2021): 610-618. doi: https://doi.org/10.1124/dmd.121.000484
El-Khateeb E, Al-Majdoub ZM, Rostami-Hodjegan A, Barber J, Achour B. Proteomic Quantification of Changes in Abundance of Drug-Metabolizing Enzymes and Drug Transporters in Human Liver Cirrhosis: Different Methods, Similar Outcomes. Drug Metab Dispos. 2021 Aug;49(8):610-618. doi: 10.1124/dmd.121.000484. Epub 2021 May 27. PMID: 34045218.
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Pharmacokinetics under the COVID-19 storm.

British journal of clinical pharmacology

Pilla Reddy V, El-Khateeb E, Jo H, Giovino N, Lythgoe E, Sharma S, Tang W, Jamei M, Rastomi-Hodjegan A.
PMID: 33226664
Br J Clin Pharmacol. 2020 Nov 23; doi: 10.1111/bcp.14668. Epub 2020 Nov 23.

AIMS: The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing subgroups of populations...

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Pilla Reddy V, El-Khateeb E, Jo H, et al. Pharmacokinetics under the COVID-19 storm. Br J Clin Pharmacol. 2020;doi: 10.1111/bcp.14668.
Pilla Reddy, V., El-Khateeb, E., Jo, H., Giovino, N., Lythgoe, E., Sharma, S., Tang, W., Jamei, M., & Rastomi-Hodjegan, A. (2020). Pharmacokinetics under the COVID-19 storm. British journal of clinical pharmacology, . https://doi.org/10.1111/bcp.14668
Pilla Reddy, Venkatesh, et al. "Pharmacokinetics under the COVID-19 storm." British journal of clinical pharmacology vol. (2020). doi: https://doi.org/10.1111/bcp.14668
Pilla Reddy V, El-Khateeb E, Jo H, Giovino N, Lythgoe E, Sharma S, Tang W, Jamei M, Rastomi-Hodjegan A. Pharmacokinetics under the COVID-19 storm. Br J Clin Pharmacol. 2020 Nov 23; doi: 10.1111/bcp.14668. Epub 2020 Nov 23. PMID: 33226664; PMCID: PMC7753415.
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Application of Physiologically Based Pharmacokinetic (PBPK) Modeling Within a Bayesian Framework to Identify Poor Metabolizers of Efavirenz (PM), Using a Test Dose of Efavirenz.

Frontiers in pharmacology

Chetty M, Cain T, Wedagedera J, Rostami-Hodjegan A, Jamei M.
PMID: 29636682
Front Pharmacol. 2018 Mar 27;9:247. doi: 10.3389/fphar.2018.00247. eCollection 2018.

Poor metabolisers of CYP2B6 (PM) require a lower dose of efavirenz because of serious adverse reactions resulting from the higher plasma concentrations associated with a standard dose. Treatment discontinuation is a common consequence in patients experiencing these adverse reactions....

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Chetty M, Cain T, Wedagedera J, et al. Application of Physiologically Based Pharmacokinetic (PBPK) Modeling Within a Bayesian Framework to Identify Poor Metabolizers of Efavirenz (PM), Using a Test Dose of Efavirenz. Front Pharmacol. 2018;9:247doi: 10.3389/fphar.2018.00247.
Chetty, M., Cain, T., Wedagedera, J., Rostami-Hodjegan, A., & Jamei, M. (2018). Application of Physiologically Based Pharmacokinetic (PBPK) Modeling Within a Bayesian Framework to Identify Poor Metabolizers of Efavirenz (PM), Using a Test Dose of Efavirenz. Frontiers in pharmacology, 9247. https://doi.org/10.3389/fphar.2018.00247
Chetty, Manoranjenni, et al. "Application of Physiologically Based Pharmacokinetic (PBPK) Modeling Within a Bayesian Framework to Identify Poor Metabolizers of Efavirenz (PM), Using a Test Dose of Efavirenz." Frontiers in pharmacology vol. 9 (2018): 247. doi: https://doi.org/10.3389/fphar.2018.00247
Chetty M, Cain T, Wedagedera J, Rostami-Hodjegan A, Jamei M. Application of Physiologically Based Pharmacokinetic (PBPK) Modeling Within a Bayesian Framework to Identify Poor Metabolizers of Efavirenz (PM), Using a Test Dose of Efavirenz. Front Pharmacol. 2018 Mar 27;9:247. doi: 10.3389/fphar.2018.00247. eCollection 2018. PMID: 29636682; PMCID: PMC5881162.
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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.

Journal of clinical pharmacology

Salem F, Johnson TN, Hodgkinson ABJ, Ogungbenro K, Rostami-Hodjegan A.
PMID: 32885464
J Clin Pharmacol. 2021 Feb;61(2):159-171. doi: 10.1002/jcph.1725. Epub 2020 Sep 03.

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...

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Salem F, Johnson TN, Hodgkinson ABJ, et al. 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(2):159-171doi: 10.1002/jcph.1725.
Salem, F., Johnson, T. N., Hodgkinson, A. B. J., Ogungbenro, K., & Rostami-Hodjegan, A. (2021). 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. Journal of clinical pharmacology, 61(2), 159-171. https://doi.org/10.1002/jcph.1725
Salem, Farzaneh, et al. "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." Journal of clinical pharmacology vol. 61,2 (2021): 159-171. doi: https://doi.org/10.1002/jcph.1725
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. 2021 Feb;61(2):159-171. doi: 10.1002/jcph.1725. Epub 2020 Sep 03. PMID: 32885464; PMCID: PMC7818478.
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Physiologically Based Pharmacokinetics Is Impacting Drug Development and Regulatory Decision Making.

CPT: pharmacometrics & systems pharmacology

Rowland M, Lesko LJ, Rostami-Hodjegan A.
PMID: 26225258
CPT Pharmacometrics Syst Pharmacol. 2015 Jun;4(6):313-5. doi: 10.1002/psp4.52. Epub 2015 Jun 15.

It is no coincidence that the reports of two meetings, one organized by the US Food and Drug Administration (FDA), in March 2014, and the other by the UK Medicines and Healthcare Products Regulatory (MHRA), in collaboration with ABPI...

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Rowland M, Lesko LJ, Rostami-Hodjegan A. Physiologically Based Pharmacokinetics Is Impacting Drug Development and Regulatory Decision Making. CPT Pharmacometrics Syst Pharmacol. 2015;4(6):313-5doi: 10.1002/psp4.52.
Rowland, M., Lesko, L. J., & Rostami-Hodjegan, A. (2015). Physiologically Based Pharmacokinetics Is Impacting Drug Development and Regulatory Decision Making. CPT: pharmacometrics & systems pharmacology, 4(6), 313-5. https://doi.org/10.1002/psp4.52
Rowland, M, et al. "Physiologically Based Pharmacokinetics Is Impacting Drug Development and Regulatory Decision Making." CPT: pharmacometrics & systems pharmacology vol. 4,6 (2015): 313-5. doi: https://doi.org/10.1002/psp4.52
Rowland M, Lesko LJ, Rostami-Hodjegan A. Physiologically Based Pharmacokinetics Is Impacting Drug Development and Regulatory Decision Making. CPT Pharmacometrics Syst Pharmacol. 2015 Jun;4(6):313-5. doi: 10.1002/psp4.52. Epub 2015 Jun 15. PMID: 26225258; PMCID: PMC4505824.
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Application of proteomic data in the translation of in vitro observations to associated clinical outcomes.

Drug discovery today. Technologies

Neuhoff S, Harwood MD, Rostami-Hodjegan A, Achour B.
PMID: 34906322
Drug Discov Today Technol. 2021 Dec;39:13-22. doi: 10.1016/j.ddtec.2021.06.002. Epub 2021 Jun 25.

Translation of information on drug exposure and effect is facilitated by in silico models that enable extrapolation of in vitro measurements to in vivo clinical outcomes. These models integrate drug-specific data with information describing physiological processes and pathological changes,...

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Neuhoff S, Harwood MD, Rostami-Hodjegan A, et al. Application of proteomic data in the translation of in vitro observations to associated clinical outcomes. Drug Discov Today Technol. 2021;39:13-22doi: 10.1016/j.ddtec.2021.06.002.
Neuhoff, S., Harwood, M. D., Rostami-Hodjegan, A., & Achour, B. (2021). Application of proteomic data in the translation of in vitro observations to associated clinical outcomes. Drug discovery today. Technologies, 3913-22. https://doi.org/10.1016/j.ddtec.2021.06.002
Neuhoff, Sibylle, et al. "Application of proteomic data in the translation of in vitro observations to associated clinical outcomes." Drug discovery today. Technologies vol. 39 (2021): 13-22. doi: https://doi.org/10.1016/j.ddtec.2021.06.002
Neuhoff S, Harwood MD, Rostami-Hodjegan A, Achour B. Application of proteomic data in the translation of in vitro observations to associated clinical outcomes. Drug Discov Today Technol. 2021 Dec;39:13-22. doi: 10.1016/j.ddtec.2021.06.002. Epub 2021 Jun 25. PMID: 34906322.
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Non-uniformity of Changes in Drug-Metabolizing Enzymes and Transporters in Liver Cirrhosis: Implications for Drug Dosage Adjustment.

Molecular pharmaceutics

El-Khateeb E, Achour B, Al-Majdoub ZM, Barber J, Rostami-Hodjegan A.
PMID: 34428046
Mol Pharm. 2021 Sep 06;18(9):3563-3577. doi: 10.1021/acs.molpharmaceut.1c00462. Epub 2021 Aug 24.

Liver cirrhosis is a chronic disease that affects the liver structure, protein expression, and overall metabolic function. Abundance data for drug-metabolizing enzymes and transporters (DMET) across all stages of disease severity are scarce. Levels of these proteins are crucial...

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El-Khateeb E, Achour B, Al-Majdoub ZM, et al. Non-uniformity of Changes in Drug-Metabolizing Enzymes and Transporters in Liver Cirrhosis: Implications for Drug Dosage Adjustment. Mol Pharm. 2021;18(9):3563-3577doi: 10.1021/acs.molpharmaceut.1c00462.
El-Khateeb, E., Achour, B., Al-Majdoub, Z. M., Barber, J., & Rostami-Hodjegan, A. (2021). Non-uniformity of Changes in Drug-Metabolizing Enzymes and Transporters in Liver Cirrhosis: Implications for Drug Dosage Adjustment. Molecular pharmaceutics, 18(9), 3563-3577. https://doi.org/10.1021/acs.molpharmaceut.1c00462
El-Khateeb, Eman, et al. "Non-uniformity of Changes in Drug-Metabolizing Enzymes and Transporters in Liver Cirrhosis: Implications for Drug Dosage Adjustment." Molecular pharmaceutics vol. 18,9 (2021): 3563-3577. doi: https://doi.org/10.1021/acs.molpharmaceut.1c00462
El-Khateeb E, Achour B, Al-Majdoub ZM, Barber J, Rostami-Hodjegan A. Non-uniformity of Changes in Drug-Metabolizing Enzymes and Transporters in Liver Cirrhosis: Implications for Drug Dosage Adjustment. Mol Pharm. 2021 Sep 06;18(9):3563-3577. doi: 10.1021/acs.molpharmaceut.1c00462. Epub 2021 Aug 24. PMID: 34428046; PMCID: PMC8424631.
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Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy.

Annual review of pharmacology and toxicology

Darwich AS, Polasek TM, Aronson JK, Ogungbenro K, Wright DFB, Achour B, Reny JL, Daali Y, Eiermann B, Cook J, Lesko L, McLachlan AJ, Rostami-Hodjegan A.
PMID: 33035445
Annu Rev Pharmacol Toxicol. 2021 Jan 06;61:225-245. doi: 10.1146/annurev-pharmtox-033020-113257. Epub 2020 Oct 09.

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current...

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Darwich AS, Polasek TM, Aronson JK, et al. Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy. Annu Rev Pharmacol Toxicol. 2020;61:225-245doi: 10.1146/annurev-pharmtox-033020-113257.
Darwich, A. S., Polasek, T. M., Aronson, J. K., Ogungbenro, K., Wright, D. F. B., Achour, B., Reny, J. L., Daali, Y., Eiermann, B., Cook, J., Lesko, L., McLachlan, A. J., & Rostami-Hodjegan, A. (2021). Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy. Annual review of pharmacology and toxicology, 61225-245. https://doi.org/10.1146/annurev-pharmtox-033020-113257
Darwich, Adam S, et al. "Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy." Annual review of pharmacology and toxicology vol. 61 (2021): 225-245. doi: https://doi.org/10.1146/annurev-pharmtox-033020-113257
Darwich AS, Polasek TM, Aronson JK, Ogungbenro K, Wright DFB, Achour B, Reny JL, Daali Y, Eiermann B, Cook J, Lesko L, McLachlan AJ, Rostami-Hodjegan A. Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy. Annu Rev Pharmacol Toxicol. 2021 Jan 06;61:225-245. doi: 10.1146/annurev-pharmtox-033020-113257. Epub 2020 Oct 09. PMID: 33035445.
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Opening a debate on open-source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate.

CPT: pharmacometrics & systems pharmacology

Rostami-Hodjegan A, Bois FY.
PMID: 33793084
CPT Pharmacometrics Syst Pharmacol. 2021 May;10(5):420-427. doi: 10.1002/psp4.12615. Epub 2021 May 01.

As model-informed drug development becomes an integral part of modern approaches to the discovery of new therapeutic entities and showing their safety and effectiveness, modalities of incorporating the paradigm into widespread practice require a revisit. Traditionally, modeling and simulation...

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Rostami-Hodjegan A, Bois FY. Opening a debate on open-source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate. CPT Pharmacometrics Syst Pharmacol. 2021;10(5):420-427doi: 10.1002/psp4.12615.
Rostami-Hodjegan, A., & Bois, F. Y. (2021). Opening a debate on open-source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate. CPT: pharmacometrics & systems pharmacology, 10(5), 420-427. https://doi.org/10.1002/psp4.12615
Rostami-Hodjegan, Amin, and Bois, Frederic Y. "Opening a debate on open-source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate." CPT: pharmacometrics & systems pharmacology vol. 10,5 (2021): 420-427. doi: https://doi.org/10.1002/psp4.12615
Rostami-Hodjegan A, Bois FY. Opening a debate on open-source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate. CPT Pharmacometrics Syst Pharmacol. 2021 May;10(5):420-427. doi: 10.1002/psp4.12615. Epub 2021 May 01. PMID: 33793084; PMCID: PMC8129708.
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Showing 1 to 12 of 32 entries