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Prospective Predictions of Human Pharmacokinetics for Eighteen Compounds.
J Pharm Sci. 2015 Sep; 104(9):2795-806.JP

Abstract

Quantitative predictions of pharmacokinetics (PKs) and concentration-time profiles using in vitro and in vivo preclinical data are critical to estimate systemic exposures for first-in-human studies. Prospective prediction accuracies of human PKs for 18 compounds across all Biopharmaceutics Classification System/Biopharmaceutics Drug Disposition Classification System classes were evaluated. The a priori predicted profiles were then compared with clinical profiles. Predictions were conducted using advanced compartmental absorption and transit (ACAT) physiology based PK models. Human intravenous profiles were predicted with in vivo preclinical intravenous data using Wajima formulas. Human oral profiles were generated by combining intravenous PKs together with either physiologically based oral ACAT models utilizing solubility and permeability data or by using the average bioavailability (F) and absorption rate constant (ka) from preclinical species. Key PK parameters evaluated were the maximum plasma concentration (Cmax), the area under the plasma concentration-time curve (AUC), CL/F, and Vdss /F. A decision tree was provided to guide human PK and ACAT predictions. Our prospective human PK prediction methods yielded good prediction results. The predictions were within a twofold error for 80% (Cmax), 65% (AUC), 65% (CL/F), and 80% (Vz /F) of the compounds. The methods described can be readily implemented with available in vitro and in vivo data during early drug development.

Authors+Show Affiliations

Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, New Jersey, 07936.Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, New Jersey, 07936.Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, New Jersey, 07936.Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, New Jersey, 07936.Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, New Jersey, 07936.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

25690565

Citation

Zhang, Tao, et al. "Prospective Predictions of Human Pharmacokinetics for Eighteen Compounds." Journal of Pharmaceutical Sciences, vol. 104, no. 9, 2015, pp. 2795-806.
Zhang T, Heimbach T, Lin W, et al. Prospective Predictions of Human Pharmacokinetics for Eighteen Compounds. J Pharm Sci. 2015;104(9):2795-806.
Zhang, T., Heimbach, T., Lin, W., Zhang, J., & He, H. (2015). Prospective Predictions of Human Pharmacokinetics for Eighteen Compounds. Journal of Pharmaceutical Sciences, 104(9), 2795-806. https://doi.org/10.1002/jps.24373
Zhang T, et al. Prospective Predictions of Human Pharmacokinetics for Eighteen Compounds. J Pharm Sci. 2015;104(9):2795-806. PubMed PMID: 25690565.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Prospective Predictions of Human Pharmacokinetics for Eighteen Compounds. AU - Zhang,Tao, AU - Heimbach,Tycho, AU - Lin,Wen, AU - Zhang,Jin, AU - He,Handan, Y1 - 2015/02/17/ PY - 2014/08/26/received PY - 2015/01/02/revised PY - 2015/01/08/accepted PY - 2015/2/19/entrez PY - 2015/2/19/pubmed PY - 2016/5/11/medline KW - ADME KW - bioavailability KW - biopharmaceutics classification system (BCS) KW - clearance KW - clinical pharmacokinetics KW - formulation KW - oral absorption KW - physiological model KW - preclinical pharmacokinetics KW - solubility SP - 2795 EP - 806 JF - Journal of pharmaceutical sciences JO - J Pharm Sci VL - 104 IS - 9 N2 - Quantitative predictions of pharmacokinetics (PKs) and concentration-time profiles using in vitro and in vivo preclinical data are critical to estimate systemic exposures for first-in-human studies. Prospective prediction accuracies of human PKs for 18 compounds across all Biopharmaceutics Classification System/Biopharmaceutics Drug Disposition Classification System classes were evaluated. The a priori predicted profiles were then compared with clinical profiles. Predictions were conducted using advanced compartmental absorption and transit (ACAT) physiology based PK models. Human intravenous profiles were predicted with in vivo preclinical intravenous data using Wajima formulas. Human oral profiles were generated by combining intravenous PKs together with either physiologically based oral ACAT models utilizing solubility and permeability data or by using the average bioavailability (F) and absorption rate constant (ka) from preclinical species. Key PK parameters evaluated were the maximum plasma concentration (Cmax), the area under the plasma concentration-time curve (AUC), CL/F, and Vdss /F. A decision tree was provided to guide human PK and ACAT predictions. Our prospective human PK prediction methods yielded good prediction results. The predictions were within a twofold error for 80% (Cmax), 65% (AUC), 65% (CL/F), and 80% (Vz /F) of the compounds. The methods described can be readily implemented with available in vitro and in vivo data during early drug development. SN - 1520-6017 UR - https://www.unboundmedicine.com/medline/citation/25690565/Prospective_Predictions_of_Human_Pharmacokinetics_for_Eighteen_Compounds_ DB - PRIME DP - Unbound Medicine ER -