An Evaluation of the Utility of Physiologically Based Models of Pharmacokinetics in Early Drug Discovery

Parrott, Neil; Paquereau, Nicolas; Coassolo, Philippe; Lavé, Thierry

doi:10.1002/jps.20419

Cited by 103 publications

(87 citation statements)

References 41 publications

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“…Metrics of external validation were R 2 test and geometric mean fold error (GMFE), where the former indicates the extent of linearity between observed and predicted values of CL R and the latter indicates the fold-overprediction or fold-under-prediction of CL R values. GMFE gives equal weight to (Parrott et al, 2005). GMFE was calculated suing the equation:…”

Section: Methodsmentioning

confidence: 99%

Quantitative Structure-Pharmacokinetic Relationships for the Prediction of Renal Clearance in Humans

Dave

Morris

2014

Drug Metab Dispos

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Renal clearance (CL R ), a major route of elimination for many drugs and drug metabolites, represents the net result of glomerular filtration, active secretion and reabsorption, and passive reabsorption. The aim of this study was to develop quantitative structurepharmacokinetic relationships (QSPKR) to predict CL R of drugs or drug-like compounds in humans. Human CL R data for 382 compounds were obtained from the literature.Step-wise multiple linear regression was used to construct QSPKR models for training sets and their predictive performance was evaluated using internal validation (leave-one-out method). All qualified models were validated externally using test sets. QSPKR models were also constructed for compounds in accordance with their 1) net elimination pathways (net secretion, extensive net secretion, net reabsorption, and extensive net reabsorption), 2) net elimination clearances (net secretion clearance, CL SEC ; or net reabsorption clearance, CL REAB ), 3) ion status, and 4) substrate/inhibitor specificity for renal transporters. We were able to predict 1) CL REAB Moreover, compounds undergoing net reabsorption/extensive net reabsorption predominantly belonged to Biopharmaceutics Drug Disposition Classification System classes 1 and 2. In conclusion, constructed parsimonious QSPKR models can be used to predict CL R of compounds that 1) undergo net reabsorption/extensive net reabsorption and 2) are substrates and/or inhibitors of human renal transporters.

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Section: Methodsmentioning

confidence: 99%

Quantitative Structure-Pharmacokinetic Relationships for the Prediction of Renal Clearance in Humans

Dave

Morris

2014

Drug Metab Dispos

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“…A mean fold error ≤2 is generally considered successful, indicating that most of the predicted values fall within the twofold range of the observed ones (between 0.5 and 2.0) (19). For the PD b data, the mean error and the root mean squared error (RMSE) were used for assessment of the bias and accuracy of predictions, respectively, as previously used to evaluate error for % bioavailability data (30).…”

Section: Stepwise Mlr and Assessment Of Predictionsmentioning

confidence: 99%

Prediction of Biliary Excretion in Rats and Humans Using Molecular Weight and Quantitative Structure–Pharmacokinetic Relationships

Yang

Gandhi

Duignan

et al. 2009

AAPS J

107

101

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Abstract. The aims were (1) to evaluate the molecular weight (MW) dependence of biliary excretion and (2) to develop quantitative structure-pharmacokinetic relationships (QSPKR) to predict biliary clearance (CL b ) and percentage of administered dose excreted in bile as parent drug (PD b ) in rats and humans. CL b and PD b data were collected from the literature for rats and humans. Receiver operating characteristic curve analysis was utilized to determine whether a MW threshold exists for PD b . Stepwise multiple linear regression (MLR) was used to derive QSPKR models. The predictive performance of the models was evaluated by internal validation using the leave-one-out method and external test groups. A MW threshold of 400 Da was determined for PD b for anions in rats, while 475 Da was the cutoff for anions in humans. MW thresholds were not present for cations or cations/neutral compounds in either rats or humans. The QSPKR model for human CL b showed a significant correlation (R 2 =0.819) with good prediction performance (Q 2 =0.722). The model was further assessed using a test group, yielding a geometric mean fold-error of 2.68. QSPKR models with significant correlation and good predictability were also developed for CL b in rats and PD b data for anions or cation/neutral compounds in rats and humans. Both CL b and PD b data were further evaluated for subsets of MRP2 or P-glycoprotein substrates, and significant relationships were derived. QSPKR models were successfully developed for biliary excretion of non-congeneric compounds in rats and humans, providing a quantitative prediction of biliary clearance of compounds.

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“…transit, dissolution, release, permeation, transport and metabolism (15,16). Given the complex nature of these drug-physiology interactions, prospective predictions of oral bioavailability within the PBPK framework are still a challenging task (17)(18)(19). Nevertheless, significant efforts have recently been made in order to improve our understanding of such a complex interplay.…”

Section: Introductionmentioning

confidence: 99%

Development of a Novel Simplified PBPK Absorption Model to Explain the Higher Relative Bioavailability of the OROS® Formulation of Oxybutynin

Olivares‐Morales

Ghosh

Aarons

et al. 2016

AAPS J

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Abstract.A new minimal Segmented Transit and Absorption model (mSAT) model has been recently proposed and combined with intrinsic intestinal effective permeability (P eff,int ) to predict the regional gastrointestinal (GI) absorption (f abs ) of several drugs. Herein, this model was extended and applied for the prediction of oral bioavailability and pharmacokinetics of oxybutynin and its enantiomers to provide a mechanistic explanation of the higher relative bioavailability observed for oxybutynin's modified-release OROS® formulation compared to its immediate-release (IR) counterpart. The expansion of the model involved the incorporation of mechanistic equations for the prediction of release, transit, dissolution, permeation and first-pass metabolism. The predicted pharmacokinetics of oxybutynin enantiomers after oral administration for both the IR and OROS® formulations were in close agreement with the observed data. The predicted absolute bioavailability for the IR formulation was within 5% of the observed value, and the model adequately predicted the higher relative bioavailability observed for the OROS® formulation vs. the IR counterpart. From the model predictions, it can be noticed that the higher bioavailability observed for the OROS® formulation was mainly attributable to differences in the intestinal availability (F G ) rather than due to a higher colonic f abs , thus confirming previous hypotheses. The predicted f abs was almost 70% lower for the OROS® formulation compared to the IR formulation, whereas the F G was almost eightfold higher than in the IR formulation. These results provide further support to the hypothesis of an increased F G as the main factor responsible for the higher bioavailability of oxybutynin's OROS® formulation vs. the IR.

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An Evaluation of the Utility of Physiologically Based Models of Pharmacokinetics in Early Drug Discovery

Cited by 103 publications

References 41 publications

Quantitative Structure-Pharmacokinetic Relationships for the Prediction of Renal Clearance in Humans

Quantitative Structure-Pharmacokinetic Relationships for the Prediction of Renal Clearance in Humans

Prediction of Biliary Excretion in Rats and Humans Using Molecular Weight and Quantitative Structure–Pharmacokinetic Relationships

Development of a Novel Simplified PBPK Absorption Model to Explain the Higher Relative Bioavailability of the OROS® Formulation of Oxybutynin

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