Exploring molecular fragments for fraction unbound in human plasma of chemicals: a fragment-based cheminformatics approach.

Fraction unbound in plasma (fu,p) of drugs is an significant factor for drug delivery and other biological incidences related to the pharmacokinetic behaviours of drugs. Exploration of different molecular fragments for fu,p of different small molecules/agents can facilitate in identification of suitable candidates in the preliminary stage of drug discovery. Different researchers have implemented strategies to build several prediction models for fu,p of different drugs. However, these studies did not focus on the identification of responsible molecular fragments to determine the fraction unbound in plasma. In the current work, we tried to focus on the development of robust classification-based QSAR models and evaluated these models with multiple statistical metrics to identify essential molecular fragments/structural attributes for fractions unbound in plasma. The study unequivocally suggests various N-containing aromatic rings and aliphatic groups have positive influences and sulphur-containing thiadiazole rings have negative influences for the fu,p values. The molecular fragments may help for the assessment of the fu,p values of different small molecules/drugs in a speedy way in comparison to experiment-based in vivo and in vitro studies.

A validated LC-MS/MS method for determination of neuro-pharmacokinetic behavior of niraparib in brain tumor patients.

Niraparib is a potent and orally bioavailable inhibitor of poly (ADP-ribose) polymerase (PARP) with high specificity for isoforms 1 and 2. It has been approved by the U.S. Food and Drug Administration for ovarian cancer maintenance therapy and is currently under development for various cancers, including glioblastoma. To assess central nervous system (CNS) penetration of niraparib in glioblastoma patients, a novel bioanalytical method was developed to measure total and unbound niraparib levels in human brain tumor tissue and cerebrospinal fluid (CSF). The method was validated using plasma as a surrogate matrix over the concentration range of 1-10,000 nM on an LC-MS/MS system. The MS/MS detection was conducted in positive electrospray ionization mode, while chromatography was performed using a Kinetex™ PS C18 column with a total 3.5-minute gradient elution run time. The maximum coefficient of variation for both intra- and inter-day precision was 10.6%, with accuracy ranging from 92.8% - 118.5% across all matrices. Niraparib was stable in human brain homogenate for at least 6 hours at room temperature (RT) and 32 days at -20°C, as well as in stock and working solutions for at least 21 hours (RT) and 278 days (4°C). Equilibrium dialysis experiments revealed the fractions unbound of 0.05 and 0.16 for niraparib in human brain and plasma, respectively. The validated method is currently employed to assess niraparib levels in human glioblastoma tissue, CSF, and plasma in an ongoing trial on newly diagnosed glioblastoma and recurrent IDH1/2(+) ATRX mutant glioma patients (NCT05076513). Initial results of calculated total (Kp) and unbound (Kp,uu) tumor-to-plasma partition coefficients indicate significant brain penetration ability of niraparib in glioblastoma patients.

Human Serum Albumin Immobilized On Magnetizable Beads: A Rapid Method for Compound HSA Binding Study.

Immobilized human serum albumin (HSA) was developed by coupling His-tagged HSA onto Ni2+-coupled magnetizable beads (HSA-beads), allowing the HSA to be easily removed from incubation components. The HSA-beads system provides a rapid and convenient method to study HSA compound binding. In this study, the HSA-beads system was characterized and evaluated as a tool for assessing compound HSA binding properties. The free fraction (fu) values of test compounds measured using HSA-beads were comparable to those determined by equilibrium dialysis (ED), which is commonly used to evaluate albumin binding in vitro. The equilibrium dissociation constant (Kd) values determined for a series of compounds using the HSA-beads method demonstrated good correlation with literature data. This good correlation also suggests that the binding of His-HSA to the beads does not impact the conformations of the two compound binding sites of HSA, as the range of compounds tested encompassed binding to both sites. Furthermore, the Kd values of representative compounds itraconazole and BIRT2584 that were difficult to assess using ED, due to significant cellulose membrane adsorption, were successfully determined. The HSA-beads provide several advantages over ED, such as simple preparation, short assay incubation duration, and the ability to quantify both free and HSA-bound species of the test compound, facilitated by the simple separation of HSA-beads from the solution phase using a magnetic field. These properties render the HSA-beads method suitable for high-throughput studies on compound HSA binding.

Interspecies variability in protein binding of antibiotics basis for translational PK/PD studies-a case study using cefazolin.

For antimicrobial agents in particular, plasma protein binding (PPB) plays a pivotal role in deciphering key properties of drug candidates. Animal models are generally used in the preclinical development of new drugs to predict their effects in humans using translational pharmacokinetics/pharmacodynamics (PK/PD). Thus, we compared the protein binding (PB) of cefazolin as well as bacterial growth under various conditions in vitro. The PB extent of cefazolin was studied in human, bovine, and rat plasmas at different antibiotic concentrations in buffer and media containing 20-70% plasma or pure plasma using ultrafiltration (UF) and equilibrium dialysis (ED). Moreover, bacterial growth and time-kill assays were performed in Mueller Hinton Broth (MHB) containing various plasma percentages. The pattern for cefazolin binding to plasma proteins was found to be similar for both UF and ED. There was a significant decrease in cefazolin binding to bovine plasma compared to human plasma, whereas the pattern in rat plasma was more consistent with that in human plasma. Our growth curve analysis revealed considerable growth inhibition of Escherichia coli at 70% bovine or rat plasma compared with 70% human plasma or pure MHB. As expected, our experiments with cefazolin at low concentrations showed that E. coli grew slightly better in 20% human and rat plasma compared to MHB, most probably due to cefazolin binding to proteins in the plasma. Based on the example of cefazolin, our study highlights the interspecies differences of PB with potential impact on PK/PD. These findings should be considered before preclinical PK/PD data can be extrapolated to human patients.

Comparison of Tumor Binding Across Tumor Types and Cell Lines to Support Free Drug Considerations for Oncology Drug Discovery.

Tumor binding is an important parameter to derive unbound tumor concentration to explore pharmacokinetics (PK) and pharmacodynamics (PD) relationships for oncology disease targets. Tumor binding was evaluated using eleven matrices, including various commonly used ex vivo human and mouse xenograft and syngeneic tumors, tumor cell lines and liver as a surrogate tissue. The results showed that tumor binding is highly correlated among the different tumors and tumor cell lines except for the mouse melanoma (B16F10) tumor type. Liver fraction unbound (fu) has a good correlation with B16F10 tumor binding. Liver also demonstrates a two-fold equivalency, on average, with binding of other tumor types when a scaling factor is applied. Predictive models were developed for tumor binding, with correlations established with LogD (acids), predicted muscle fu (neutrals) and measured plasma protein binding (bases) to estimate tumor fu when experimental data are not available. Many approaches can be applied to obtain and estimate tumor binding values. One strategy proposed is to use a surrogate tumor tissue, such as mouse xenograft ovarian cancer (OVCAR3) tumor, as a surrogate for tumor binding (except for B16F10) to provide an early assessment of unbound tumor concentrations for development of PK/PD relationships.

Descriptor-Free Deep Learning QSAR Model for the Fraction Unbound in Human Plasma.

Chemical-specific parameters are either measured in vitro or estimated using quantitative structure-activity relationship (QSAR) models. The existing body of QSAR work relies on extracting a set of descriptors or fingerprints, subset selection, and training a machine learning model. In this work, we used a state-of-the-art natural language processing model, Bidirectional Encoder Representations from Transformers, which allowed us to circumvent the need for calculation of these chemical descriptors. In this approach, simplified molecular-input line-entry system (SMILES) strings were embedded in a high-dimensional space using a two-stage training approach. The model was first pre-trained on a masked SMILES token task and then fine-tuned on a QSAR prediction task. The pre-training task learned meaningful high-dimensional embeddings based upon the relationships between the chemical tokens in the SMILES strings derived from the "in-stock" portion of the ZINC 15 dataset─a large dataset of commercially available chemicals. The fine-tuning task then perturbed the pre-trained embeddings to facilitate prediction of a specific QSAR endpoint of interest. The power of this model stems from the ability to reuse the pre-trained model for multiple different fine-tuning tasks, reducing the computational burden of developing multiple models for different endpoints. We used our framework to develop a predictive model for fraction unbound in human plasma (fu,p). This approach is flexible, requires minimum domain expertise, and can be generalized for other parameters of interest for rapid and accurate estimation of absorption, distribution, metabolism, excretion, and toxicity.

Determination of furosemide and its glucuronide metabolite in plasma, plasma ultrafiltrate and urine by HPLC-MS/MS with application to secretion and metabolite formation clearances in non-pregnant and pregnant women.

Furosemide (FUR) has been used in probe drugs cocktails for in vivo evaluation of the renal transporters OAT1 and OAT3 activities in studies of drug-drug interactions (generally using probenecid as an inhibitor) and drug-disease interactions. The objective of this study was to develop and validate methods for FUR and its glucuronide metabolite (FUR-GLU) analysis in plasma, plasma ultrafiltrate and urine for application in pharmacokinetics studies: a pilot drug-drug interaction study in pregnant women (n = 2), who received a single oral dose of FUR (40 mg) and in another occasion a single oral dose of probenecid (750 mg) before a single oral dose of FUR (40 mg), and in non-pregnant women participants (n = 12), who only received a single oral dose of FUR (40 mg). The samples preparation for FUR in 50 µL of plasma and plasma lysate were carried by acidified liquid-liquid extraction, while 50 µL of urine and 200 µL of plasma ultrafiltrate were simply diluted with the mobile phase. The methods presented linearities in the range of 0.50 - 2500 ng/mL of plasma and plasma lysate, 0.125 - 250 ng/mL of plasma ultrafiltrate, and 50 - 20,000 ng/mL of urine. FUR-GLU methods presented linearities in the range of 0.125 - 250 ng/mL of plasma ultrafiltrate and 50 - 20,000 ng/mL of urine. Precision and accuracy evaluations showed coefficients of variation and relative errors < 15%. In the pregnant women participants, the mean values of FUR CLrenal, CLsecretion, CLformation. FUR-GLU and CLnon-renal were all reduced when probenecid was administered with FUR (8.24 vs 2.89 L/h, 8.15 vs 2.80 L/h, 3.86 vs 1.75 L/h, 48.26 vs 22.10 L/h, respectively). Non-pregnant women presented similar values of FUR CLrenal, CLsecretion, CLformation. FUR-GLU to the pregnant women who received FUR only. Finally, FUR fraction unbound (fu) resulted in values of approximately 1% in pregnant women and to 0.22% in non-pregnant women. These developed and validated methods for FUR and FUR-GLU quantification in multiple matrices can allow the further investigation of UGT1A9/1A1 and the fu when FUR is administered as an OAT 1 and 3 in vivo probe.

Prediction of the Time to Reach Equilibrium for Improved Estimation of the Unbound Fraction of Compounds in Equilibrium Dialysis Using kinetic Modeling.

Equilibrium dialysis (ED) is widely used in pharmacokinetics to determine the fraction of unbound (fu) compounds in plasma; however, the kinetics of drugs in the ED system with respect to their permeation across semi-permeable membranes has not been systemically studied. Here, the kinetics of the ED system, including the binding of drugs to plasma proteins, non-specific binding, and permeation across the membrane, was described to enable verification of the equilibrium, prediction of the time to reach equilibrium, and estimations of fu with data obtained during pre-equilibrium. Using data obtained during pre-equilibrium, the time to reach 90% equilibrium (t90%) and fu were estimated with reasonable accuracy. Notably, fu could be estimated reasonably well using one-time-point data for the calculation. Furthermore, the current modeling approach allowed concurrent estimations of fu and the decomposition rate of compounds that were metabolically unstable in the plasma. Reasonable metabolic rate constants were determined for cefadroxil and diltiazem, demonstrating the practicality of this method for determining kinetics related to fu characterization. Because the determination of fu of compounds with 'unfavorable' physicochemical properties is known to be experimentally challenging, the current method may be useful in determining the fu of compounds in vitro.

Using Counter Equilibrium Dialysis (CED) to Increase Confidence in the Measurement of Free Fraction for Challenging Compounds.

The confidence in fraction unbound (ƒu) using equilibrium dialysis (ED) is often questioned (e.g., highly bound, labile compounds) due to uncertainty in whether true equilibrium is achieved. Different methods have been developed to increase confidence in ƒu measurements, such as the presaturation, dilution, and bi-directional ED methods. However, confidence in ƒu measurement can still suffer due to non-specific binding and inter-run variations introduced during equilibrium and analysis. To address this concern, we introduce an orthogonal approach called counter equilibrium dialysis (CED) in which non-labeled and isotope-labeled compounds are dosed counter-directionally in rapid equilibrium dialysis (RED). ƒu values of both non-labeled and labeled compounds are measured simultaneously in the same run. These tactics not only minimize non-specific binding and inter-run variability but also enable the confirmation of true equilibrium. If equilibrium is reached in both dialysis directions, the ƒu for the non-labeled compound and the labeled compound will converge. The refined methodology was extensively tested with various compounds of diverse physicochemical properties and plasma binding characteristics. Our results demonstrated that, by using the CED method, ƒu values for a wide range of compounds could be accurately determined with significantly improved confidence, including the challenging highly bound and labile compounds.

In Vitro-In Vivo Extrapolation and Scaling Factors for Clearance of Human and Preclinical Species with Liver Microsomes and Hepatocytes.

In vitro-in vivo extrapolation ((IVIVE) and empirical scaling factors (SF) of human intrinsic clearance (CLint) were developed using one of the largest dataset of 455 compounds with data from human liver microsomes (HLM) and human hepatocytes (HHEP). For extended clearance classification system (ECCS) class 2/4 compounds, linear SFs (SFlin) are approximately 1, suggesting enzyme activities in HLM and HHEP are similar to those in vivo under physiological conditions. For ECCS class 1A/1B compounds, a unified set of SFs was developed for CLint. These SFs contain both SFlin and an exponential SF (SFß) of fraction unbound in plasma (fu,p). The unified SFs for class 1A/1B eliminate the need to identify the transporters involved prior to clearance prediction. The underlying mechanisms of these SFs are not entirely clear at this point, but they serve practical purposes to reduce biases and increase prediction accuracy. Similar SFs have also been developed for preclinical species. For HLM-HHEP disconnect (HLM > HHEP) ECCS class 2/4 compounds that are mainly metabolized by cytochrome P450s/FMO, HLM significantly overpredicted in vivo CLint, while HHEP slightly underpredicted and geometric mean of HLM and HHEP slightly overpredicted in vivo CLint. This observation is different than in rats, where rat liver microsomal CLint correlates well with in vivo CLint for compounds demonstrating permeability-limited metabolism. The good CLint IVIVE developed using HLM and HHEP helps build confidence for prospective predictions of human clearance and supports the continued utilization of these assays to guide structure-activity relationships to improve metabolic stability.

Rapid equilibrium dialysis, ultrafiltration or ultracentrifugation? Evaluation of methods to quantify the unbound fraction of substances in plasma.

In pharmacokinetics plasma protein binding (PPB) is a well-established parameter impacting drug disposition. The unbound fraction (fu) is arguably regarded the effective concentration at the target site. Pharmacology and toxicology, increasingly use in vitro models. The translation of in vitro concentrations to in vivo doses can be supported by toxicokinetic modelling, e.g. physiologically based toxicokinetic models (PBTK). PPB of a test substance is an input parameter for PBTK. We compared three methods to quantify fu: rapid equilibrium dialysis (RED), ultrafiltration (UF) and ultracentrifugation (UC) using twelve substances covering a wide range of Log Pow (-0.1 to 6.8) and molecular weights (151 and 531 g/mol): Acetaminophen, Bisphenol A, Caffeine, Colchicine, Fenarimol, Flutamide, Genistein, Ketoconazole, α-Methyltestosterone, Tamoxifen, Trenbolone and Warfarin. After RED and UF separation, three polar substances (Log Pow < 2) were largely unbound (fu > 70%), while more lipophilic substances were largely bound (fu < 33%). Compared to RED or UF, UC resulted in a generally higher fu of lipophilic substances. fu obtained after RED and UF were more consistent with published data. For half of the substances, UC resulted in fu higher than the reference data. UF, RED and both UF and UC, resulted in lower fu of Flutamide, Ketoconazole and Colchicine, respectively. For fu quantifications, the separation method should be selected according to the test substance's properties. Based on our data, RED is suitable for a broader range of substances while UC and UF are suitable for polar substances.

Addressing the Accuracy of Plasma Protein Binding Measurement for Highly Bound Compounds Using the Dilution Method.

Currently, regulatory guidelines recommend using 0.01 as the lower limit of plasma fraction unbound (fu) for prediction of drug-drug interactions (DDI) to err on the conservative side. One way to increase experimental fu of highly bound compounds is to dilute the plasma. With the dilution method, a diluted fu, or fu,d, of ≥ 0.01 can be achieved by adjusting the dilution factor. The undiluted fu can be calculated from fu,d and be used for DDI prediction. In this study, the dilution method was evaluated, and the results showed that it gave similar fu values as those determined using the pre-saturation method without plasma dilution. The dilution method enables generation of accurate fu values and alignment with the regulatory recommendation of reportable fu values of ≥ 0.01 for DDI prediction. We recommend using the dilution method to bridge the regulatory recommended fu limit of 0.01 for DDI prediction and the pre-saturation or equivalent methods for definitive plasma protein binding studies. As the pharmaceutical industry continues to generate high quality PPB data, regulatory agencies will gain confidence in the accuracy of fu measurements for highly bound compounds, and the fu lower limit may no longer be needed in the future.

Factors Affecting the Binding of Diltiazem to Rainbow Trout Plasma: Implications for the Risk Assessment of Pharmaceuticals in Aquatic Systems.

The accumulation of organic toxicants in fish plasma, and how they partition between the bound and unbound fraction once absorbed, are important metrics in models that seek to predict the risk of such contaminants in aquatic settings. Rapid equilibrium dialysis of diltiazem, an ionizable weak base and important human pharmaceutical contaminant of freshwaters, was conducted with rainbow trout (Oncorhynchus mykiss) plasma. The effect of fed state, fish sex, fish strain/size, and dialysis buffer pH on the binding of radiolabeled diltiazem (9 ng ml-1 ) was assessed. In fed fish, 24.6%-29.5% of diltiazem was free, unbound to plasma proteins. Although starvation of fish resulted in a decrease in plasma protein, the bound fraction of diltiazem remained relatively constant. Consequently, the protein-bound concentration of diltiazem increased with length of starvation. In general, rainbow trout strain was a significant factor affecting plasma binding, although the two strains tested also differed markedly in size. Dialysis buffer pH significantly influenced plasma binding, with a higher unbound diltiazem fraction at pH 6.8 than pH 8.0. These data indicate that empirical measures of plasma binding in fish are important for accurate risk assessment and that the physiological status of a fish is likely to impact its sensitivity to toxicants such as diltiazem. Environ Toxicol Chem 2022;41:3125-3133. © 2022 SETAC.

Development and validation of a liquid chromatography coupled with tandem mass spectrometry method for determining total and unbound pamiparib in human plasma and brain tumors.

Pamiparib (BGB-290) is an orally bioavailable, small molecule inhibitor of poly (ADP-ribose) polymerase 1 (PARP1) and PARP2. A reversed-phase LC with tandem mass spectrometry method was developed and fully validated for determining total and unbound pamiparib concentrations in human plasma and brain tumor tissue. Plasma and tissue homogenate samples were prepared by methanol protein precipitation. Pamiparib and the internal standard [13 C2 ,15 N2 ]pamiparib were separated on a Waters BEH C18 (50 × 2.1 mm, 1.7 µm) column, with a gradient elution consisting of mobile phases A (0.1% formic acid in water) and B (0.1% formic acid in acetonitrile) at a flow rate of 0.25 mL/min. The analytes were monitored with multiple reaction monitoring mode under positive electrospray ionization. The method was fully validated for specificity, linearity, accuracy and precision, matrix effect and recovery, and short- and long-term stability. The lower limit of quantitation was 0.5 nM of pamiparib in plasma or tissue homogenate. The calibration curve was linear over the pamiparib concentration range of 0.5-1000 nM in plasma. The intra- and inter-day precision and accuracy were within the generally accepted criteria for bioanalytical method. Pamiparib was stable in plasma at -80°C for at least 6 months. The method was successfully applied to assess the plasma and tumor pharmacokinetics of total and unbound pamiparib in patients with glioma.

Protein Binding in Translational Antimicrobial Development-Focus on Interspecies Differences.

BACKGROUND/INTRODUCTION: Plasma protein binding (PPB) continues to be a key aspect of antibiotic development and clinical use. PPB is essential to understand several properties of drug candidates, including antimicrobial activity, drug-drug interaction, drug clearance, volume of distribution, and therapeutic index. Focus areas of the review: In this review, we discuss the basics of PPB, including the main drug binding proteins i.e., Albumin and α-1-acid glycoprotein (AAG). Furthermore, we present the effects of PPB on the antimicrobial activity of antibiotics and the current role of PPB in in vitro pharmacodynamic (PD) models of antibiotics. Moreover, the effect of PPB on the PK/PD of antibiotics has been discussed in this review. A key aspect of this paper is a concise evaluation of PPB between animal species (dog, rat, mouse, rabbit and monkey) and humans. Our statistical analysis of the data available in the literature suggests a significant difference between antibiotic binding in humans and that of dogs or mice, with the majority of measurements from the pre-clinical species falling within five-fold of the human plasma value. Conversely, no significant difference in binding was found between humans and rats, rabbits, or monkeys. This information may be helpful for drug researchers to select the most relevant animal species in which the metabolism of a compound can be studied for extrapolating the results to humans. Furthermore, state-of-the-art methods for determining PPB such as equilibrium dialysis, ultracentrifugation, microdialysis, gel filtration, chromatographic methods and fluorescence spectroscopy are highlighted with their advantages and disadvantages.

Prediction Models for Brain Distribution of Drugs Based on Biomimetic Chromatographic Data.

The development of high-throughput approaches for the valid estimation of brain disposition is of great importance in the early drug screening of drug candidates. However, the complexity of brain tissue, which is protected by a unique vasculature formation called the blood−brain barrier (BBB), complicates the development of robust in silico models. In addition, most computational approaches focus only on brain permeability data without considering the crucial factors of plasma and tissue binding. In the present study, we combined experimental data obtained by HPLC using three biomimetic columns, i.e., immobilized artificial membranes, human serum albumin, and α1-acid glycoprotein, with molecular descriptors to model brain disposition of drugs. Kp,uu,brain, as the ratio between the unbound drug concentration in the brain interstitial fluid to the corresponding plasma concentration, brain permeability, the unbound fraction in the brain, and the brain unbound volume of distribution, was collected from literature. Given the complexity of the investigated biological processes, the extracted models displayed high statistical quality (R2 > 0.6), while in the case of the brain fraction unbound, the models showed excellent performance (R2 > 0.9). All models were thoroughly validated, and their applicability domain was estimated. Our approach highlighted the importance of phospholipid, as well as tissue and protein, binding in balance with BBB permeability in brain disposition and suggests biomimetic chromatography as a rapid and simple technique to construct models with experimental evidence for the early evaluation of CNS drug candidates.

The importance of plasma protein and tissue binding in a drug discovery program to successfully deliver a preclinical candidate.

Plasma protein binding and tissue binding are arguably two of the most critical parameters that are measured as part of a drug discovery program since, according to the free drug hypothesis, it is the free drug that is responsible for both efficacy and toxicity. This chapter aims to deconstruct the role of plasma protein and tissue binding in drug discovery programs, and to consider the conclusion made by Pfizer and Genentech/Depomed a decade ago that optimising plasma protein binding as an independent parameter does not significantly influence efficacy. This chapter will also examine how binding metrics are applied in drug discovery programs and explore circumstances where optimising plasma protein or tissue binding can be an effective strategy to deliver a candidate molecule for preclinical development with an early indication of sufficient therapeutic index.

An update on the importance of plasma protein binding in drug discovery and development.

Introduction: Plasma protein binding (PPB) remains a controversial topic in drug discovery and development. Fraction unbound (fu) is a critical parameter that needs to be measured accurately, because it has significant impacts on the predictions of drug-drug interactions (DDI), estimations of therapeutic indices (TI), and developments of PK/PD relationships.  However, it is generally not advisable to change PPB through structural modifications, because PPB on its own has little relevance for in vivo efficacy.Areas covered: PPB fundamentals are discussed including the three main classes of drug binding proteins (i.e., albumin, alpha1-acid glycoprotein, and lipoproteins) and their physicochemical properties, in vivo half-life, and synthesis rate.  State-of-the-art methodologies for PPB are highlighted. Applications of PPB in drug discovery and development are presented.Expert opinion: PPB is an old topic in pharmacokinetics, but there are still many misconceptions. Improving the accuracy of PPB for highly bound compounds is an ongoing effort in the field with high priority. As the field continues to generate high quality data, the regulatory agencies will increase their confidence in our ability to accurately measure PPB of highly bound compounds, and experimental fu values below 0.01 will more likely be used for DDI predictions in the future.

Case Study 5: Predicting the Drug Interaction Potential for Inhibition of CYP2C8 by Montelukast.

Predicting drug-drug interactions (DDIs) from in vitro data is made difficult by not knowing concentrations of substrate and inhibitor at the target site. For in vivo targets, this is understandable, since intracellular concentrations can differ from extracellular concentrations. More vexing is that the concentration of the drug at the target for some in vitro assays can also be unknown. This uncertainty has resulted in standard in vitro practices that cannot accurately predict human pharmacokinetics. This case study highlights the impact of drug distribution, both in vitro and in vivo, with the example of the drug interaction potential of montelukast.

Evolving approaches on measurements and applications of intracellular free drug concentration and Kpuu in drug discovery.

Introduction: Intracellular-free drug concentration (Cu,cell) and unbound partition coefficient (Kpuu) are two important parameters to develop pharmacokinetic and pharmacodynamic relationships, predict drug-drug interaction potentials and estimate therapeutic indices.Area covered: Methods on measurements of Cu,cell, Kpuu, partition coefficient (Kp) and fraction unbound of cells (fuc) are discussed. Advantages and limitations of several fuc methods are reviewed. Applications highlighted here are bridging the potency gaps between biochemical and cell-based assays, in vitro hepatocyte assay to predict in vivo liver-to-plasma Kpuu, the role of Kpuu in prediction of hepatic clearance for enzyme- and transporter-mediated mechanisms using extended clearance equation, and structural attributes governing tissue Kpuu.Expert opinion: Cu,cell and Kpuu are of growing applications in drug discovery. Methods for measurements of these properties continue to evolve in order to achieve higher precision/accuracy and obtain more detailed information at the subcellular levels. Future directions of the field include the development of in vitro and in silico models to predict tissue Kpuu, direct measurement of free drug concentration in subcellular organelles, and further investigations into the critical elements governing cell and tissue Kpuu. Significant innovation is needed to advance this complex, but highly impactful and exciting area of science.