On the Nature of Physiologically-Based Pharmacokinetic Models –A Priori or A Posteriori? Mechanistic or Empirical?

Korzekwa, Kenneth R.; Nagar, Swati

doi:10.1007/s11095-016-2089-8

Cited by 18 publications

(12 citation statements)

References 24 publications

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“…The discussion is necessarily limited to conventional non-permeabilitylimited models of hepatic clearance for two main reasons: the historical predominance of drugs not limited by permeability in their hepatic uptake and the lack of distinction of nonmetabolic rate-limiting processes within the available in vitro data. Extended liver clearance models may be appropriate for an increasing number of drugs due to reliance on uptake transport, and indeed lack of in vitro distinction of such processes has been suggested as a reason for underprediction of clearance (Chiba et al, 2009;Patilea-Vrana and Unadkat, 2016;Korzekwa and Nagar, 2017). However, this report attempts to focus on more general prediction trends.…”

Section: Downloaded Frommentioning

confidence: 97%

Clearance Prediction Methodology Needs Fundamental Improvement: Trends Common to Rat and Human Hepatocytes/Microsomes and Implications for Experimental Methodology

2017

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Although prediction of clearance using hepatocytes and liver microsomes has long played a decisive role in drug discovery, it is widely acknowledged that reliably accurate prediction is not yet achievable despite the predominance of hepatically cleared drugs. Physiologically mechanistic methodology tends to underpredict clearance by several fold, and empirical correction of this bias is confounded by imprecision across drugs. Understanding the causes of prediction uncertainty has been slow, possibly reflecting poor resolution of variables associated with donor source and experimental methods, particularly for the human situation. It has been reported that among published human hepatocyte predictions there was a tendency for underprediction to increase with increasing in vivo intrinsic clearance, suggesting an inherent limitation using this particular system. This implied an artifactual rate limitation in vitro, although preparative effects on cell stability and performance were not yet resolved from assay design limitations. Here, to resolve these issues further, we present an up-to-date and comprehensive examination of predictions from published rat as well as human studies (where = 128 and 101 hepatocytes and = 71 and 83 microsomes, respectively) to assess system performance more independently. We report a clear trend of increasing underprediction with increasing in vivo intrinsic clearance, which is similar both between species and between in vitro systems. Hence, prior concerns arising specifically from human in vitro systems may be unfounded and the focus of investigation in the future should be to minimize the potential in vitro assay limitations common to whole cells and subcellular fractions.

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Section: Downloaded Frommentioning

confidence: 97%

Clearance Prediction Methodology Needs Fundamental Improvement: Trends Common to Rat and Human Hepatocytes/Microsomes and Implications for Experimental Methodology

2017

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“…As discussed previously (Korzekwa and Nagar, 2017b), eqs. 5-7 indicate that the K pu,tissue value, and ultimately the unbound V ss value, should be proportional to K pu,BC (eq.…”

Section: Resultsmentioning

confidence: 79%

“…The K p,dPL method considers binding to neutral lipids such as triglycerides and neutral phospholipids in membranes, with acidic phospholipids considered separately (Rodgers et al, 2005;Rodgers and Rowland, 2006). The method assumes that neutral molecules only interact with neutral phospholipids, and only ionized bases interact with APs, an assumption questioned previously (Korzekwa and Nagar, 2017b). The major acidic phospholipid is phosphatidylserine and the major neutral phospholipid is phosphatidylcholine.…”

Section: Discussionmentioning

confidence: 99%

Prediction of Tissue-Plasma Partition Coefficients Using Microsomal Partitioning: Incorporation into Physiologically based Pharmacokinetic Models and Steady-State Volume of Distribution Predictions

Holt

Nagar

et al. 2019

Drug Metab Dispos

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Drug distribution is a necessary component of models to predict human pharmacokinetics. A new membrane-based tissue-plasma partition coefficient (K p) method (K p,mem) to predict unbound tissue to plasma partition coefficients (K pu) was developed using in vitro membrane partitioning [fraction unbound in microsomes (f um)], plasma protein binding, and log P. The resulting K p values were used in a physiologically based pharmacokinetic (PBPK) model to predict the steady-state volume of distribution (V ss) and concentrationtime (C-t) profiles for 19 drugs. These results were compared with K p predictions using a standard method [the differential phospholipid K p prediction method (K p,dPL)], which differentiates between acidic and neutral phospholipids. The K p,mem method was parameterized using published rat K pu data and tissue lipid composition. The K pu values were well predicted with R 2 5 0.8. When used in a PBPK model, the V ss predictions were within 2-fold error for 12 of 19 drugs for K p,mem versus 11 of 19 for K p,dPL. With one outlier removed for K p,mem and two for K p,dPL , the V ss predictions for R 2 were 0.80 and 0.79 for the K p,mem and K p,dPL methods, respectively. The C-t profiles were also predicted and compared. Overall, the K p,mem method predicted the V ss and C-t profiles equally or better than the K p,dPL method. An advantage of using f um to parameterize membrane partitioning is that f um data are used for clearance prediction and are, therefore, generated early in the discovery/development process. Also, the method provides a mechanistically sound basis for membrane partitioning and permeability for further improving PBPK models. SIGNIFICANCE STATEMENT A new method to predict tissue-plasma partition coefficients was developed. The method provides a more mechanistic basis to model membrane partitioning.

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“…Although the plausibility of species-specific differences in binding to acidic phospholipids has not been investigated for Compound 2, this example highlights the impact and thus the requirement of measuring BPR for compounds with basic centres to inform PBPK models. A recent publication, although critiquing some assumptions behind PBPK models, stated that K p s for bases are well predicted, possibly because of the use of BPR to calculate acidic phospholipid binding constants [79].…”

Section: Power Of Blood/plasma Ratiomentioning

confidence: 99%

Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

et al. 2019

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Physiologically based pharmacokinetic modelling is well established in the pharmaceutical industry and is accepted by regulatory agencies for the prediction of drug-drug interactions. However, physiologically based pharmacokinetic modelling is valuable to address a much wider range of pharmaceutical applications, and new regulatory impact is expected as its full power is leveraged. As one example, physiologically based pharmacokinetic modelling is already routinely used during drug discovery for in-vitro to in-vivo translation and pharmacokinetic modelling in preclinical species, and this leads to the application of verified models for first-inhuman pharmacokinetic predictions. A consistent cross-industry strategy in this application area would increase confidence in the approach and facilitate further learning. With this in mind, this article aims to enhance a previously published first-inhuman physiologically based pharmacokinetic model-building strategy. Based on the experience of scientists from multiple companies participating in the GastroPlus™ User Group Steering Committee, new Absorption, Distribution, Metabolism and Excretion knowledge is integrated and decision trees proposed for each essential component of a first-inhuman prediction. We have reviewed many relevant scientific publications to identify new findings and highlight gaps that need to be addressed. Finally, four industry case studies for more challenging compounds illustrate and highlight key components of the strategy.

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On the Nature of Physiologically-Based Pharmacokinetic Models –A Priori or A Posteriori? Mechanistic or Empirical?

Cited by 18 publications

References 24 publications

Clearance Prediction Methodology Needs Fundamental Improvement: Trends Common to Rat and Human Hepatocytes/Microsomes and Implications for Experimental Methodology

Clearance Prediction Methodology Needs Fundamental Improvement: Trends Common to Rat and Human Hepatocytes/Microsomes and Implications for Experimental Methodology

Prediction of Tissue-Plasma Partition Coefficients Using Microsomal Partitioning: Incorporation into Physiologically based Pharmacokinetic Models and Steady-State Volume of Distribution Predictions

Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

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