Updated &lt;i&gt;in silico&lt;/i&gt; prediction methods for fractions absorbed and absorption rate constants of 372 disparate chemicals for use in physiologically based pharmacokinetic models for estimating internal concentrations in rats

Adachi, Koichiro; Shimizu, Makiko; Yamazaki, Hiroshi

doi:10.2131/jts.47.453

Cited by 3 publications

(3 citation statements)

References 7 publications

(33 reference statements)

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“…The pharmacokinetic parameters of orally administered diazepam, phenytoin, and nicotine in rats were previously established based on individual in vivo time-dependent concentration data. 20,21) Input parameters for hexobarbital, fingolimod, and pentazocine were estimated using machine learning systems under considerations of a wide variety of chemical space [22][23][24] without any reference to experimental pharmacokinetic data.…”

Section: Pbpk Modelingmentioning

confidence: 99%

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Modeled Rat Hepatic and Plasma Concentrations of Chemicals after Virtual Administrations Using Two Sets of in Silico Liver-to-Plasma Partition Coefficients

Adachi

Utsumi

Sato

et al. 2023

Biological & Pharmaceutical Bulletin

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The hepatic elimination of chemical substances in pharmacokinetic models requires hepatic intrinsic clearance (CLh,int) parameters for unbound drug in the liver, and these are regulated by the liver-to-plasma partition coefficients (Kp,h). Both Poulin and Theil and Rodgers and Rowland have proposed in silico expressions for Kp,h for a variety of chemicals. In this study, two sets of in silico Kp,h values for 14 model substances were assessed using experimentally reported in vivo steady-state Kp,h data and time-dependent virtual internal exposures in the liver and plasma modeled by forward dosimetry in rats. The Kp,h values for 14 chemicals independently calculated using the primary Poulin and Theil method in this study were significantly correlated with those obtained using the updated Rodgers and Rowland method and with reported in vivo steady-state Kp,h data in rats. When pharmacokinetic parameters were derived based on individual in vivo time-dependent data for diazepam, phenytoin, and nicotine in rats, the modeled liver and plasma concentrations after intravenous administration of the selected substrates in rats using two sets of in silico Kp,h values were mostly similar to the reported time-dependent in vivo internal exposures. Similar results for modeled liver and plasma concentrations were observed with input parameters estimated by machine-learning systems for hexobarbital, fingolimod, and pentazocine, with no reference to experimental pharmacokinetic data. These results suggest that the output values from rat pharmacokinetic models based on in silico Kp,h values derived from the primary Poulin and Theil model would be applicable for estimating toxicokinetics or internal exposure to substances.

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Section: Pbpk Modelingmentioning

confidence: 99%

“…20,21) The in silico derived input parameters for rat PBPK models of hexobarbital, fingolimod, and pentazocine were generated using a previously reported machine learning system. [22][23][24]…”

Section: Biological and Pharmaceutical Bulletin Advance Publicationmentioning

confidence: 99%

Modeled Rat Hepatic and Plasma Concentrations of Chemicals after Virtual Administrations Using Two Sets of in Silico Liver-to-Plasma Partition Coefficients

Adachi

Utsumi

Sato

et al. 2023

Biological & Pharmaceutical Bulletin

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“…We previously used machine learning to predict the pharmacokinetic parameters of chemical substances in humans and rats. We managed to progressively improve the prediction accuracy (Adachi et al, 2022a(Adachi et al, , 2022bKamiya et al, 2022;Kamiya et al, 2021;Kamiya et al, 2019) by using a previously proposed two-dimensional data plot consisting of 25 blocks to illustrate the similarity/differences of chemical structures in the chemical space; the coordinates of substances in this two-dimensional plot were determined using in silico chemical descriptors. The rates at which substances cross membranes are highly dependent on the logP values (Adachi et al, 2023b;Poulin and Theil, 2002;Rodgers et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Octanol/water partition coefficients estimated using retention times in reverse-phase liquid chromatography and calculated in silico as one of the determinant factors for pharmacokinetic parameter estimations of general chemical substances

Adachi,

Shimizu,

Shono

et al. 2024

J. Toxicol. Sci.

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The octanol/water partition coefficient P (logP) is a hydrophobicity index and is one of the determining factors for the pharmacokinetics of orally administered substances because it influences membrane permeability. To illustrate the wide-ranging variety of compounds in the chemical space, a two-dimensional data plot consisting of 25 blocks was previously proposed based on a substance's in silico chemical descriptors. The logP values of approximately 200 diverse chemicals (test plus reference compounds covering all 25 blocks of the chemical space) were estimated experimentally using retention times in reverse-phase liquid chromatography; these values were compared with those of authentic reference compounds with established logP values (available for 17 of 60 reference substances in the Organization for Economic Co-operation and Development Test Guideline 117). The logP values of 140 of 165 chemicals successfully estimated using four different mobile phase conditions (pH 2, 4, 7, and 10 for molecular forms) correlated significantly with those calculated using the in silico packages ChemDraw and ACD/Percepta (r > 0.72). Although substances that neighbored authentic compounds in the chemical space had precisely correlated logP values estimated experimentally and in silico, some compounds that were more distant from authentic substances showed lower logP values than those estimated in silico. These results indicate that additional authentic reference materials with wider ranging chemical diversity and their logP values from reverse-phase liquid chromatography should be included in the international test guidance to promote simple and reliable estimation of octanol/water partition coefficients, which are important determinant factors for the pharmacokinetics of general chemicals.

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Liver and Plasma Concentrations of Food Chemicals after Virtual Oral Doses Extrapolated Using in Silico Estimated Input Pharmacokinetic Parameters to Confirm Reported Liver Toxicity in Rats

Adachi

Nakano

Sato

et al. 2023

Biological & Pharmaceutical Bulletin

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The estimation of health risks of chemical substances was historically investigated using animal studies; however, current research focuses on reducing the number of animal experiments. The toxicity of chemicals in fish screening systems is reportedly correlated with their hydrophobicity. The inverse relationship between absorption rates (intestinal cell permeability) and virtual hepatic/plasma pharmacokinetics of diverse chemicals has been previously evaluated by modeling oral administration in rats. In the current study, internal exposures, i.e., virtual maximum plasma concentrations (Cmax) and areas under the concentration-time curves (AUC), of 56 food chemicals with reported hepatic lowest-observed-effect levels (LOELs) of ≤1000 mg/kg/day in rats were pharmacokinetically modeled using in silico estimated input pharmacokinetic parameters. After a virtual single oral dose of 1.0 mg/kg of 56 food chemicals, the output Cmax and AUC values in rat plasma generated by modeling using the corresponding in silico estimated input parameters were not significantly correlated with the reported hepatic LOEL values. However, significant inverse relationships between hepatic/plasma concentrations of selected lipophilic food chemicals (i.e., octanol-water partition coefficient logP >1) using forward dosimetry and reported LOEL values (≤300 mg/kg/day) were observed (n = 14, r = -0.52-0.66, p ≤ 0.05). This simple modeling approach, which uses no experimental pharmacokinetic data, has the potential to play a significant role in reducing the use of animals to estimate toxicokinetics or internal exposures of lipophilic food components after oral doses.Therefore, these methods are valuable for estimating hepatic toxicity by using forward dosimetry in animal toxicity experiments.

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Updated <i>in silico</i> prediction methods for fractions absorbed and absorption rate constants of 372 disparate chemicals for use in physiologically based pharmacokinetic models for estimating internal concentrations in rats

Cited by 3 publications

References 7 publications

Modeled Rat Hepatic and Plasma Concentrations of Chemicals after Virtual Administrations Using Two Sets of <i>in Silico</i> Liver-to-Plasma Partition Coefficients

Modeled Rat Hepatic and Plasma Concentrations of Chemicals after Virtual Administrations Using Two Sets of <i>in Silico</i> Liver-to-Plasma Partition Coefficients

Octanol/water partition coefficients estimated using retention times in reverse-phase liquid chromatography and calculated <i>in silico</i> as one of the determinant factors for pharmacokinetic parameter estimations of general chemical substances

Liver and Plasma Concentrations of Food Chemicals after Virtual Oral Doses Extrapolated Using <i>in Silico</i> Estimated Input Pharmacokinetic Parameters to Confirm Reported Liver Toxicity in Rats

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