Interpretation of Non-Clinical Data for Prediction of Human Pharmacokinetic Parameters: In Vitro-In Vivo Extrapolation and Allometric Scaling

Choi, Go-Wun; Lee, Yong-Bok; Cho, Hea-Young

doi:10.3390/pharmaceutics11040168

Cited by 55 publications

(48 citation statements)

References 115 publications

(145 reference statements)

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“…CL h was predicted by parallel tube and well-stirred model. The parallel tube model describes the liver as a set of tubes representing a sinusoid, with the drug concentration exponentially decreasing in the direction of the hepatic vein (Choi et al 2019). However, the liver is considered as a single, well-mixed compartment with a fixed drug concentration in the well-stirred model (Segers et al 2019).…”

Section: Discussionmentioning

confidence: 99%

Toxicokinetics and toxicodynamics of the fentanyl homologs cyclopropanoyl-1-benzyl-4´-fluoro-4-anilinopiperidine and furanoyl-1-benzyl-4-anilinopiperidine

et al. 2020

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The two fentanyl homologs cyclopropanoyl-1-benzyl-4´-fluoro-4-anilinopiperidine (4F-Cy-BAP) and furanoyl-1-benzyl-4-anilinopiperidine (Fu-BAP) have recently been seized as new psychoactive substances (NPS) on the drugs of abuse market. As their toxicokinetic and toxicodynamic characteristics are completely unknown, this study focused on elucidating their in vitro metabolic stability in pooled human liver S9 fraction (pHLS9), their qualitative in vitro (pHLS9), and in vivo (zebrafish larvae) metabolism, and their in vitro isozyme mapping using recombinant expressed isoenzymes. Their maximum-tolerated concentration (MTC) in zebrafish larvae was studied from 0.01 to 100 µM. Their µ-opioid receptor (MOR) activity was analyzed in engineered human embryonic kidney (HEK) 293 T cells. In total, seven phase I and one phase II metabolites of 4F-Cy-BAP and 15 phase I and four phase II metabolites of Fu-BAP were tentatively identified by means of liquid chromatography high-resolution tandem mass spectrometry, with the majority detected in zebrafish larvae. N-Dealkylation, N-deacylation, hydroxylation, and N-oxidation were the most abundant metabolic reactions and the corresponding metabolites are expected to be promising analytical targets for toxicological analysis. Isozyme mapping revealed the main involvement of CYP3A4 in the phase I metabolism of 4F-Cy-BAP and in terms of Fu-BAP additionally CYP2D6. Therefore, drug-drug interactions by CYP3A4 inhibition may cause elevated drug levels and unwanted adverse effects. MTC experiments revealed malformations and changes in the behavior of larvae after exposure to 100 µM Fu-BAP. Both substances were only able to produce a weak activation of MOR and although toxic effects based on MOR activation seem unlikely, activity at other receptors cannot be excluded. Keywords In vitro and in vivo metabolism • Metabolic stability • LC-HRMS/MS • Zebrafish larvae • In vitro µ-opioid receptor activity Electronic supplementary material The online version of this article (

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Section: Discussionmentioning

confidence: 99%

Toxicokinetics and toxicodynamics of the fentanyl homologs cyclopropanoyl-1-benzyl-4´-fluoro-4-anilinopiperidine and furanoyl-1-benzyl-4-anilinopiperidine

et al. 2020

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“…Allometric scaling: Traditionally, prediction of human V D,ss has relied on scaling of V D,ss obtained from preclinical species using allometric equations (Jones et al, 2011). While allometry has some limitations in predicting distribution of highly protein bound drugs, it has been a valuable technique to predict human PK parameters to determine first-time-in-human (FTIH) dose (Choi et al, 2019 (Zou et al, 2012). As the V D,ss predictions inversely proportional to fup in preclinical species (see Methods for equations), errors in the predictions of fup values will have significant impact on This article has not been copyedited and formatted.…”

Section: Discussionmentioning

confidence: 99%

Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds

Murad

Pasikanti

Madej

et al. 2021

Drug Metabolism and Disposition

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Volume of distribution at steady state (V D,ss) is one of the key pharmacokinetic parameters estimated during the drug discovery process. Despite considerable efforts to predict V D,ss , accuracy and choice of prediction methods remain a challenge, with evaluations constrained to a small set (<150) of compounds. To address these issues, a series of in silico methods for predicting human V D,ss directly from structure were evaluated using a large set of clinical compounds. Machine learning (ML) models were built to predict V D,ss directly, and to predict input parameters required for mechanistic and empirical V D,ss predictions. In addition, LogD, fraction unbound in plasma (fup) and blood to plasma partition ratio (BPR) were measured on 254 compounds to estimate impact of measured data on predictive performance of mechanistic models. Furthermore, impact of novel methodologies such as measuring partition (Kp) in adipocytes and myocytes (n=189) on V D,ss predictions was also investigated. In predicting V D,ss directly from chemical structures, both mechanistic or empirical scaling using a combination of predicted rat and dog V D,ss demonstrated comparable performance (62-71% within 3-fold). The direct ML model outperformed other in silico methods (75% within 3-fold, r 2 =0.5, AAFE=2.2) when built from a larger dataset. Scaling to human either from predicted V D,ss of rat or dog yielded poor results (<47% within 3-fold). Measured fup and BPR improved performance of mechanistic V D,ss predictions significantly (81% within 3-fold, r 2 =0.6, AAFE=2.0). Adipocyte intracellular Kp showed good correlation to the V D,ss , but was limited in estimating the compounds with low V D,ss. Significance Statement: This work advances the in-silico prediction of V D,ss directly from structure and with the aid of in vitro data. Rigorous and comprehensive evaluation of various methods using a large set of clinical compounds (n=956) is presented. The scale of both techniques and number of compounds evaluated is far beyond any previously presented. The This article has not been copyedited and formatted. The final version may differ from this version.

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“…Given these structural characteristics it can be foreseen that biliary excretion may not only be relevant for drugs but also for other chemicals, including new chemicals (Choi et al 2019). For these substances, active excretion should be included in the PBK-models to obtain an adequate description of their kinetics and subsequent prediction of in vivo effective dose levels.…”

Section: Introductionmentioning

confidence: 99%

“…To be of value for novel non-animal based testing strategies, parameters required for the PBK-models should preferably be defined using in silico and in vitro approaches. When using in vitro models for biliary excretion, important challenges relate to the type of in vitro model to be used and the subsequent translation of the in vitro data to the in vivo situation using adequate scaling factors (Choi et al 2019). When using for example a cell model with overexpression of a transporter of interest, proper scaling depends on the expression level of the transporter in the cell model compared to its expression level in the organ in vivo.…”

Section: Introductionmentioning

confidence: 99%

Novel testing strategy for prediction of rat biliary excretion of intravenously administered estradiol-17β glucuronide

et al. 2020

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The aim of the present study was to develop a generic rat physiologically based kinetic (PBK) model that includes a novel testing strategy where active biliary excretion is incorporated using estradiol-17β glucuronide (E217βG) as the model substance. A major challenge was the definition of the scaling factor for the in vitro to in vivo conversion of the PBK-model parameter Vmax. In vitro values for the Vmax and Km for transport of E217βG were found in the literature in four different studies based on experiments with primary rat hepatocytes. The required scaling factor was defined based on fitting the PBK model-based predicted values to reported experimental data on E217βG blood levels and cumulative biliary E217βG excretion. This resulted in a scaling factor of 129 mg protein/g liver. With this scaling factor the PBK model predicted the in vivo data for blood and cumulative biliary E217βG levels with on average of less than 1.8-fold deviation. The study provides a proof of principle on how biliary excretion can be included in a generic PBK model using primary hepatocytes to define the kinetic parameters that describe the biliary excretion.

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Interpretation of Non-Clinical Data for Prediction of Human Pharmacokinetic Parameters: In Vitro-In Vivo Extrapolation and Allometric Scaling

Cited by 55 publications

References 115 publications

Toxicokinetics and toxicodynamics of the fentanyl homologs cyclopropanoyl-1-benzyl-4´-fluoro-4-anilinopiperidine and furanoyl-1-benzyl-4-anilinopiperidine

Toxicokinetics and toxicodynamics of the fentanyl homologs cyclopropanoyl-1-benzyl-4´-fluoro-4-anilinopiperidine and furanoyl-1-benzyl-4-anilinopiperidine

Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds

Novel testing strategy for prediction of rat biliary excretion of intravenously administered estradiol-17β glucuronide

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