A Paradigm Shift in Pharmacokinetic–Pharmacodynamic (PKPD) Modeling: Rule of Thumb for Estimating Free Drug Level in Tissue Compared with Plasma to Guide Drug Design

doi:10.1002/jps.24468

Journal of Pharmaceutical Sciences

Volume 104, Issue 7, July 2015, Pages 2359-2368

https://doi.org/10.1002/jps.24468 Get rights and content

ABSTRACT

A basic assumption in pharmacokinetics-pharmacodynamics research is that the free drug concentration is similar in plasma and tissue, and, hence, in vitro plasma data can be used to estimate the in vivo condition in tissue. However, in a companion manuscript, it has been demonstrated that this assumption is violated for the ionized drugs. Nonetheless, these observations focus on in vitro static environments and do not challenge data with an in vivo dynamic system. Therefore, an extension from an in vitro to an in vivo system becomes the necessary next step. The objective of this study was to perform theoretical simulations of the free drug concentration in tissue and plasma by using a physiologically based pharmacokinetics (PBPK) model reproducing the in vivo conditions in human. Therefore, the effects of drug ionization, lipophilicity, and clearance have been taken into account in a dynamic system. This modeling exercise was performed as a proof of concept to demonstrate that free drug concentration in tissue and plasma may also differ in a dynamic system for passively permeable drugs that are ionized at the physiological pH. The PBPK model simulations indicated that free drug concentrations in tissue cells and plasma significantly differ for the ionized drugs because of the pH gradient effect between cells and interstitial space. Hence, a rule of thumb for potentially performing more accurate PBPK/PD modeling is suggested, which states that the free drug concentration in tissue and plasma will differ for the ionizable drugs in contrast to the neutral drugs. In addition to the pH gradient effect for the ionizable drugs, lipophilicity and clearance effects will increase or decrease the free drug concentration in tissue and plasma for each class of drugs; thus, higher will be the drug lipophilicity and clearance, lower would be the free drug concentration in plasma, and, hence, in tissue, in a dynamic in vivo system. Therefore, only considering the value of free fraction in plasma derived from a static in vitro environment might be biased to guide drug design (the old paradigm), and, hence, it is recommended to use a PBPK model to reproduce more accurately the in vivo condition in tissue (the new paradigm). This newly developed approach can be used to predict free drug concentration in diverse tissue compartments for small molecules in toxicology and pharmacology studies, which can be leveraged to optimize the pharmacokinetics drivers of tissue distribution based upon physicochemical and physiological input parameters in an attempt to optimize free drug level in tissue. Overall, this present study provides guidance on the application of plasma and tissue concentration information in PBPK/PD research in preclinical and clinical studies, which is in accordance with the recent literature.

Section snippets

INTRODUCTION

In preclinical and clinical studies, total drug concentrations in plasma or tissue are often correlated with pharmacodynamics (PD). However, the use of total tissue levels (e.g., tissue concentrations derived from homogenates) or biopsies to draw direct conclusions on drug activity is unwarranted and/or unreliable.1., 2., 3., 4. This is in contrast with the unbound (free) drug concentration at the target site, which should be more pharmacologically relevant.1., 2., 3., 4. Related to this,

METHOD

Theoretical PBPK modeling simulations in humans were made for diverse scenarios to compare the resulting free drug concentration in plasma and tissue. As said, the dissimilarities in the binding and ionization on both sides of the membrane were investigated first. Hence, for passively permeable compounds either ionized or not at the physiological pH, the maximal dissimilarity between the interstitial and intracellular (free) drug concentrations were quantified.

RESULTS

A total of 14 simulation scenarios were evaluated in the present study for the comparison of the simulated C_max and AUC_last for the unbound drug (used as a measured of free drug concentrations in plasma and heart cells in humans). The comparative assessment is presented in Table 1, Table 2. As expected, the results indicate that free drug concentrations in plasma and tissue cells are not equal as observed by the dissimilarities in the simulated values of C_max and AUC_last for the unbound drug.

DISCUSSION

Data from in vitro plasma protein-binding experiments that determine the fraction of protein-bound drug are frequently used in drug discovery to guide structure design and to prioritize compounds for in vivo studies.² Therefore, this old paradigm (using only fup derived from an in vitro static environment) is usually misleading, because this practice yields no enhancement of the in vivo free drug concentration in a dynamic system. Hence, in vivo efficacy should be determined by the free drug

CONCLUSION

This present study is a first step toward the comparison of free drug concentration in tissue and plasma under dynamic in vivo condition either after nonsteady-state and steady-state intravenous administrations in humans for passively permeable drugs that can be ionized at the physiological pH. Therefore, these observations provide much more relevant information compared with the traditional approach based only upon in vitro fup value. In other words, the current PBPK model simulations indicate

ACKNOWLEGMENTS

This work represents an initiative undertaken as a part of Dr Poulin’s research program. The author wishes to thank Conrad Housand at Aegies Technologies Inc. in Orlando, Florida, for the simulation software ADME Workbench® (www.admewb.com) that has facilitated the conduct of this study.

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Citation Excerpt :
For example, a low bioavailability effect after oral administration will reduce drug exposure, and, hence, will reduce Cfreecells and Cfreeinterstitial compared with a higher bioavailability effect.5 The same is true for a low or high CL effect2. And as the ionization state of both the drug and the target binding site potentially change as a function of pH, this would necessitate knowing the necessary pH value.
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RESEARCH ARTICLE : Pharmacokinetics, Pharmacodynamics and Drug Transport and MetabolismA Paradigm Shift in Pharmacokinetic–Pharmacodynamic (PKPD) Modeling: Rule of Thumb for Estimating Free Drug Level in Tissue Compared with Plasma to Guide Drug Design

ABSTRACT

Section snippets

INTRODUCTION

METHOD

RESULTS

DISCUSSION

CONCLUSION

ACKNOWLEGMENTS

J Pharm Sci

J Pharm Sci

J Pharm Sci

J Pharm Sci

Curr Opinion Pharmacol

J Pharm Sci

J Pharm Sci

J Pharm Sci

J Pharm Sci

J Pharm Sci

Insight into tissue free concentration: Utility in drug discovery and development

Curr Drug Metab

The effect of plasma protein binding on in vivo efficacy: Misconceptions in drug discovery

Nat Rev

Issues in pharmacokinetics and pharmacodynamics of anti-infective agents: Distribution in tissue

Antimicrob Agents Chemother

Tissue concentrations: Do we ever learn?

J Antimicrob Chemother

RESEARCH ARTICLE : Pharmacokinetics, Pharmacodynamics and Drug Transport and Metabolism
A Paradigm Shift in Pharmacokinetic–Pharmacodynamic (PKPD) Modeling: Rule of Thumb for Estimating Free Drug Level in Tissue Compared with Plasma to Guide Drug Design