Development and application of a PBPK modeling strategy to support antimalarial drug development.

As part of a collaboration between Medicines for Malaria Venture (MMV), Certara UK and Monash University, physiologically-based pharmacokinetic (PBPK) models were developed for 20 antimalarials, using data obtained from standardized in vitro assays and clinical studies within the literature. The models have been applied within antimalarial drug development at MMV for more than 5 years. During this time, a strategy for their impactful use has evolved. All models are described in the supplementary material and are available to researchers. Case studies are also presented, demonstrating real-world development and clinical applications, including the assessment of the drug-drug interaction liability between combination partners or with co-administered drugs. This work emphasizes the benefit of PBPK modeling for antimalarial drug development and decision making, and presents a strategy to integrate it into the research and development process. It also provides a repository of shared information to benefit the global health research community.

An in vitro toolbox to accelerate anti-malarial drug discovery and development.

BACKGROUND: Modelling and simulation are being increasingly utilized to support the discovery and development of new anti-malarial drugs. These approaches require reliable in vitro data for physicochemical properties, permeability, binding, intrinsic clearance and cytochrome P450 inhibition. This work was conducted to generate an in vitro data toolbox using standardized methods for a set of 45 anti-malarial drugs and to assess changes in physicochemical properties in relation to changing target product and candidate profiles. METHODS: Ionization constants were determined by potentiometric titration and partition coefficients were measured using a shake-flask method. Solubility was assessed in biorelevant media and permeability coefficients and efflux ratios were determined using Caco-2 cell monolayers. Binding to plasma and media proteins was measured using either ultracentrifugation or rapid equilibrium dialysis. Metabolic stability and cytochrome P450 inhibition were assessed using human liver microsomes. Sample analysis was conducted by LC-MS/MS. RESULTS: Both solubility and fraction unbound decreased, and permeability and unbound intrinsic clearance increased, with increasing Log D7.4. In general, development compounds were somewhat more lipophilic than legacy drugs. For many compounds, permeability and protein binding were challenging to assess and both required the use of experimental conditions that minimized the impact of non-specific binding. Intrinsic clearance in human liver microsomes was varied across the data set and several compounds exhibited no measurable substrate loss under the conditions used. Inhibition of cytochrome P450 enzymes was minimal for most compounds. CONCLUSIONS: This is the first data set to describe in vitro properties for 45 legacy and development anti-malarial drugs. The studies identified several practical methodological issues common to many of the more lipophilic compounds and highlighted areas which require more work to customize experimental conditions for compounds being designed to meet the new target product profiles. The dataset will be a valuable tool for malaria researchers aiming to develop PBPK models for the prediction of human PK properties and/or drug-drug interactions. Furthermore, generation of this comprehensive data set within a single laboratory allows direct comparison of properties across a large dataset and evaluation of changing property trends that have occurred over time with changing target product and candidate profiles.

Risk-Benefit Assessment of Ethinylestradiol Using a Physiologically Based Pharmacokinetic Modeling Approach.

Current formulations of combined oral contraceptives (COC) containing ethinylestradiol (EE) have ≤35 µg due to increased risks of cardiovascular diseases (CVD) with higher doses of EE. Low-dose formulations however, have resulted in increased incidences of breakthrough bleeding and contraceptive failure, particularly when coadministered with inducers of cytochrome P450 enzymes (CYP). The developed physiologically based pharmacokinetic model quantitatively predicted the effect of CYP3A4 inhibition and induction on the pharmacokinetics of EE. The predicted Cmax and AUC ratios when coadministered with voriconazole, fluconazole, rifampicin, and carbamazepine were within 1.25 of the observed data. Based on published clinical data, an AUCss value of 1,000 pg/ml.h was selected as the threshold for breakthrough bleeding. Prospective application of the model in simulations of different doses of EE (20 µg, 35 µg, and 50 µg) identified percentages of the population at risk of breakthrough bleeding alone and with varying degrees of CYP modulation.

Case studies addressing human pharmacokinetic uncertainty using a combination of pharmacokinetic simulation and alternative first in human paradigms.

PF-184298 ((S)-2,3-dichloro-N-isobutyl-N-pyrrolidin-3-ylbenzamide) and PF-4776548 ((3-(4-fluoro-2-methoxy-benzyl)-7-hydroxy-8,9-dihydro-3H,7H-pyrrolo[2,3-c][1,7]naphthyridin-6-one)) are novel compounds which were selected to progress to human studies. Discordant human pharmacokinetic predictions arose from pre-clinical in vivo studies in rat and dog, and from human in vitro studies, resulting in a clearance prediction range of 3 to >20 mL min⁻¹ kg⁻¹ for PF-184298, and 5 to >20 mL min⁻¹ kg⁻¹ for PF-4776548. A package of work to investigate the discordance for PF-184298 is described. Although ultimately complementary to the human pharmacokinetic data in characterising the disposition of PF-184298 in humans, these data did not provide any further confidence in pharmacokinetic prediction. A fit for purpose human pharmacokinetic study was conducted for each compound, with an oral pharmacologically active dose for PF-184298, and an intravenous and oral microdose for PF-4776548. This provided a relatively low cost, clear decision making approach, resulting in the termination of PF-4776548 and further progression of PF-184298. A retrospective analysis of the data showed that, if the tools had been available at the time, the pharmacokinetics of PF-184298 in human could have been predicted from a population based simulation tool in combination with physicochemical properties and in vitro human intrinsic clearance.

The evolution of the OATP hepatic uptake transport protein family in DMPK sciences: from obscure liver transporters to key determinants of hepatobiliary clearance.

Over the last two decades the impact on drug pharmacokinetics of the organic anion transporting polypeptides (OATPs: OATP-1B1, 1B3 and 2B1), expressed on the sinusoidal membrane of the hepatocyte, has been increasingly recognized. OATP-mediated uptake into the hepatocyte coupled with subsequent excretion into bile via efflux proteins, such as MRP2, is often referred to as hepatobiliary excretion. OATP transporter proteins can impact some drugs in several ways including pharmacokinetic variability, pharmacodynamic response and drug-drug interactions (DDIs). The impact of transporter mediated hepatic clearance is illustrated with case examples, from the literature and also from the Pfizer portfolio. The currently available in vitro techniques to study the hepatic transporter proteins involved in the hepatobiliary clearance of drugs are reviewed herein along with recent advances in using these in vitro data to predict the human clearance of compounds recognized by hepatic uptake transporters.

Application of PBPK modelling in drug discovery and development at Pfizer.

Early prediction of human pharmacokinetics (PK) and drug-drug interactions (DDI) in drug discovery and development allows for more informed decision making. Physiologically based pharmacokinetic (PBPK) modelling can be used to answer a number of questions throughout the process of drug discovery and development and is thus becoming a very popular tool. PBPK models provide the opportunity to integrate key input parameters from different sources to not only estimate PK parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. Using examples from the literature and our own company, we have shown how PBPK techniques can be utilized through the stages of drug discovery and development to increase efficiency, reduce the need for animal studies, replace clinical trials and to increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however, some limitations need to be addressed to realize its application and utility more broadly.

Effects of the moderate CYP3A4 inhibitor, fluconazole, on the pharmacokinetics of fesoterodine in healthy subjects.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Available data suggest that fesoterodine dosage should not exceed 4 mg once daily when taken concomitantly with potent CYP3A4 inhibitors, such as ketoconazole. Currently, no information is available on whether dose adjustment is necessary when fesoterodine is administered with a moderate CYP3A4 inhibitor. WHAT THIS STUDY ADDS: This study shows that adjustment of fesoterodine dose is not warranted when co-administered with a moderate CYP3A4 inhibitor. AIMS: To assess the effects of fluconazole, a moderate CYP3A4 inhibitor, on the pharmacokinetics (PK) and safety/tolerability of fesoterodine. METHODS: In this open-label, randomized, two-way crossover study, 28 healthy subjects (18-55 years) received single doses of fesoterodine 8 mg alone or with fluconazole 200 mg. PK endpoints, including the area under the plasma concentration-time curve from 0 to infinity (AUC(0,∞)), maximum plasma concentration (C(max) ), time to C(max) (t(max) ), and half-life (t(1/2) ), were assessed for 5-hydroxymethyl tolterodine (5-HMT), the active moiety of fesoterodine. RESULTS: Concomitant administration of fesoterodine with fluconazole increased AUC(0,∞) and C(max) of 5-HMT by approximately 27% and 19%, respectively, with corresponding 90% confidence intervals of (18%, 36%) and (11%, 28%). There was no apparent effect of fluconazole on 5-HMT t(max) or t(½) . Fesoterodine was generally well tolerated regardless of fluconazole co-administration, with no reports of death, serious adverse events (AEs) or severe AEs. Following co-administration of fesoterodine with fluconazole, 13 subjects (48%) experienced a total of 40 AEs; following administration of fesoterodine alone, six subjects (22%) experienced a total of 19 AEs. The majority of AEs were of mild intensity. There were no clinically significant changes in laboratory or physical examination parameters. CONCLUSION: Fesoterodine 8 mg single dose was well tolerated when administered alone or with fluconazole. Based on the observed increase in 5-HMT exposures being within the inherent variability of 5-HMT pharmacokinetics, adjustment of fesoterodine dose is not warranted when co-administered with a moderate CYP3A4 inhibitor provided they are not also inhibitors of transporters.

Simulation of human intravenous and oral pharmacokinetics of 21 diverse compounds using physiologically based pharmacokinetic modelling.

BACKGROUND: The importance of predicting human pharmacokinetics during compound selection has been recognized in the pharmaceutical industry. To this end there are many different approaches that are applied. METHODS: In this study we compared the accuracy of physiologically based pharmacokinetic (PBPK) methodologies implemented in GastroPlus™ with the one-compartment approach routinely used at Pfizer for human pharmacokinetic plasma concentration-time profile prediction. Twenty-one Pfizer compounds were selected based on the availability of relevant preclinical and clinical data. Intravenous and oral human simulations were performed for each compound. To understand any mispredictions, simulations were also performed using the observed clearance (CL) value as input into the model. RESULTS: The simulation results using PBPK were shown to be superior to those obtained via traditional one-compartment analyses. In many cases, this difference was statistically significant. Specifically, the results showed that the PBPK approach was able to accurately predict passive distribution and absorption processes. Some issues and limitations remain with respect to the prediction of CL and active transport processes and these need to be improved to further increase the utility of PBPK modelling. A particular advantage of the PBPK approach is its ability to accurately predict the multiphasic shape of the pharmacokinetic profiles for many of the compounds tested. CONCLUSION: The results from this evaluation demonstrate the utility of PBPK methodology for the prediction of human pharmacokinetics. This methodology can be applied at different stages to enhance the understanding of the compounds in a particular chemical series, guide experiments, aid candidate selection and inform clinical trial design.

An evaluation of ondansetron binding interactions with human cytochrome P450 enzymes CYP3A4 and CYP2D6.

The results of an evaluation study of ondansetron binding to human cytochromes P450 CYP3A4 and CYP2D6 is reported. The methodology includes NMR spectroscopic measurements of substrate to heme iron distances together with molecular modelling of the enzyme-substrate interactions. It is shown that there is a generally good agreement between the experimental and calculated binding affinities for ondansetron towards CYP2D6 and CYP3A4 enzymes, based on interactive docking studies. Moreover, the modelled binding orientations for ondansetron in CYP2D6 and CYP3A4 are largely consistent with the NMR data and with the known routes for P450-mediated metabolism of this compound.

Comparison of different algorithms for predicting clinical drug-drug interactions, based on the use of CYP3A4 in vitro data: predictions of compounds as precipitants of interaction.

Cytochrome P450 3A4 (CYP3A4) is the most important enzyme in drug metabolism and because it is the most frequent target for pharmacokinetic drug-drug interactions (DDIs) it is highly desirable to be able to predict CYP3A4-based DDIs from in vitro data. In this study, the prediction of clinical DDIs for 30 drugs on the pharmacokinetics of midazolam, a probe substrate for CYP3A4, was done using in vitro inhibition, inactivation, and induction data. Two DDI prediction approaches were used, which account for effects at both the liver and intestine. The first was a model that simultaneously combines reversible inhibition, time-dependent inactivation, and induction data with static estimates of relevant in vivo concentrations of the precipitant drug to provide point estimates of the average magnitude of change in midazolam exposure. This model yielded a success rate of 88% in discerning DDIs with a mean -fold error of 1.74. The second model was a computational physiologically based pharmacokinetic model that uses dynamic estimates of in vivo concentrations of the precipitant drug and accounts for interindividual variability among the population (Simcyp). This model yielded success rates of 88 and 90% (for "steady-state" and "time-based" approaches, respectively) and mean -fold errors of 1.59 and 1.47. From these findings it can be concluded that in vivo DDIs for CYP3A4 can be predicted from in vitro data, even when more than one biochemical phenomenon occurs simultaneously.

Maraviroc: in vitro assessment of drug-drug interaction potential.

AIMS: To characterize the cytochrome P450 enzyme(s) responsible for the N-dealkylation of maraviroc in vitro, and predict the extent of clinical drug-drug interactions (DDIs). METHODS: Human liver and recombinant CYP microsomes were used to identify the CYP enzyme responsible for maraviroc N-dealkylation. Studies comprised enzyme kinetics and evaluation of the effects of specific CYP inhibitors. In vitro data were then used as inputs for simulation of DDIs with ketoconazole, ritonavir, saquinavir and atazanvir, using the Simcyptrade mark population-based absorption, distribution, metabolism and elimination (ADME) simulator. Study designs for simulations mirrored those actually used in the clinic. RESULTS: Maraviroc was metabolized to its N-dealkylated product via a single CYP enzyme characterized by a K(m) of 21 microM and V(max) of 0.45 pmol pmol(-1) min(-1) in human liver microsomes and was inhibited by ketoconazole (CYP3A4 inhibitor). In a panel of recombinant CYP enzymes, CYP3A4 was identified as the major CYP responsible for maraviroc metabolism. Using recombinant CYP3A4, N-dealkylation was characterized by a K(m) of 13 microM and a V(max) of 3 pmol pmol(-1) CYP min(-1). Simulations therefore focused on the effect of CYP3A4 inhibitors on maraviroc pharmacokinetics. The simulated median AUC ratios were in good agreement with observed clinical changes (within twofold in all cases), although, in general, there was a trend for overprediction in the magnitude of the DDI. CONCLUSION: Maraviroc is a substrate for CYP3A4, and exposure will therefore be modulated by CYP3A4 inhibitors. Simcyptrade mark has successfully simulated the extent of clinical interactions with CYP3A4 inhibitors, further validating this software as a good predictor of CYP-based DDIs.

Application of CYP3A4 in vitro data to predict clinical drug-drug interactions; predictions of compounds as objects of interaction.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Numerous retrospective analyses have shown the utility of in vitro systems for predicting potential drug-drug interactions (DDIs). Prediction of DDIs from in vitro data is commonly obtained using estimates of enzyme K(i), inhibitor and substrate concentrations and absorption rate for substrate and inhibitor. WHAT THIS STUDY ADDS: Using a generic approach for all test compounds, the findings from the current study showed the use of recombinant P450s provide a more robust in vitro measure of P450 contribution (fraction metabolized, f(m)) than that achieved when using chemical inhibitors in combination with human liver microsomes, for the prediction of potential CYP3A4 drug-drug interactions prior to clinical investigation. The current study supported the use of SIMCYP(R), a modelling and simulation software in utilizing the in vitro measures in the prediction of potential drug-drug interactions. AIMS: The aim of this study was to explore and optimize the in vitro and in silico approaches used for predicting clinical DDIs. A data set containing clinical information on the interaction of 20 Pfizer compounds with ketoconazole was used to assess the success of the techniques. METHODS: The study calculated the fraction and the rate of metabolism of 20 Pfizer compounds via each cytochrome P450. Two approaches were used to determine fraction metabolized (f(m)); 1) by measuring substrate loss in human liver microsomes (HLM) in the presence and absence of specific chemical inhibitors and 2) by measuring substrate loss in individual cDNA expressed P450s (also referred to as recombinant P450s (rhCYP)) The fractions metabolized via each CYP were used to predict the drug-drug interaction due to CYP3A4 inhibition by ketoconazole using the modelling and simulation software SIMCYP. RESULTS: When in vitro data were generated using Gentest supersomes, 85% of predictions were within two-fold of the observed clinical interaction. Using PanVera baculosomes, 70% of predictions were predicted within two-fold. In contrast using chemical inhibitors the accuracy was lower, predicting only 37% of compounds within two-fold of the clinical value. Poorly predicted compounds were found to either be metabolically stable and/or have high microsomal protein binding. The use of equilibrium dialysis to generate accurate protein binding measurements was especially important for highly bound drugs. CONCLUSIONS: The current study demonstrated that the use of rhCYPs with SIMCYP provides a robust in vitro system for predicting the likelihood and magnitude of changes in clinical exposure of compounds as a consequence of CYP3A4 inhibition by a concomitantly administered drug.

Quantitative structure-activity relationships (QSARs) in inhibitors of various cytochromes P450: the importance of compound lipophilicity.

The results of extensive quantitative structure-activity relationship (QSAR) analyses on 15 series of cytochrome P450 inhibitors, covering a total of 7 enzymes and 199 compounds, are reported. In general, it is found that lipophilicity represents the most important single factor in describing differences in inhibitory potency towards P450 enzymes. In two instances, this relationship is parabolic in nature but, by and large, the logarithm of inhibitory activity relates linearly with log P, where P is the octanol-water partition coefficient. On occasions, other parameters are involved in the QSAR expressions but there are many examples where either log P or its ionization-corrected equivalent, log D7.4, are the sole structural descriptors of inhibition. The correlations presented exhibit a range in R value from 0.85 to 0.99, where R is the correlation coefficient, and it is found that R is greater than 0.9 in 80% of the QSARs presented. It is apparent from these findings, therefore, that compound lipophilicity plays a major role in the ability of xenobiotics to inhibit enzymes of the cytochrome P450 superfamily, presumably due to the essentially hydrophobic nature of the active site region.

Lipophilicity relationships in inhibitors of CYP2C9 and CYP2C19 enzymes.

Quantitative structure-activity relationships (QSARs) within a series of cytochrome P450 2C9 (CYP2C9) and cytochrome P450 2C19 (CYP2C19) inhibitors are reported. In particular, it is noted that compound lipophilicity, in the form of log P values (where P is the octanol/water partition coefficient), is an important factor in explaining the variation in inhibitory potency within these series of compounds, many of which also act as substrates for the respective enzymes. In addition, there is a role for hydrogen bonding and pi-pi stacking interactions within the P450 active site which represent secondary factors in the binding processes of these compounds.

Quantitative structure-activity relationships (QSars) in CYP3A4 inhibitors: the importance of lipophilic character and hydrogen bonding.

The results of Quantitative Structure-Activity Relationship (QSAR) analyses on three series of CYP3A4 inhibitors are reported for enzyme inhibition expressed as Ki values. These include a small series of structurally related statins and two larger groupings of structurally diverse compounds, some of which display competitive inhibition of CYP3A4 whereas others act via heme iron ligation. In all cases, however, it is apparent that there are lipophilicity relationships associated with CYP3A4 inhibitory activity in the total of 46 compounds investigated. This is evidenced by linear correlations between inhibition of CYP3A4 and the octanol-water partition coefficient (P value) when expressed logarithmically (ie., log P). In the case of the statins, however, the distribution coefficient (D) at pH 7 is used due to the effect of compound ionization. Conversion of equilibrium constants (ie. Ki and P) to the corresponding free energy changes (deltaG values) facilitates exploration of the likely intermolecular forces of interaction between the inhibitors and the active site region of CYP3A4. In this respect, there appears to be good agreement between QSAR analyses and molecular modelling of the CYP3A4 enzyme itself, and both are consistent with the known mechanisms of inhibition displayed.

Induction of cytochromes P450.

The induction of cytochromes P450 (CYPs) has been appreciated for some time but an understanding of the mechanisms involved has been poorly understood until recently. The discovery of the role of nuclear receptors such as the pregnane X receptor (PXR) and the constitutive androstane receptor (CAR) has provided a major trigger for research in this area. This work has provided an explanation for species differences in hepatic induction. The production of a PXR crystal structure in the presence and absence of known high affinity ligands has offered the possibility of predicting structures which may bind to the receptor and hence act as inducing agents in man. An improvement in the technology of hepatocyte culture, access to good quality human hepatocytes and the miniaturisation of cultured preparations has meant that the potential of this technique to predict induction in man has been realised. Molecular biological techniques have also proved essential in both the science and the quantitation of CYP induction. The use of transient transfection cell based systems coupled with reporter gene assays have meant that dose response curves can be generated for many chemicals. Assays have been developed to measure the increase of the corresponding CYP mRNAs in primary hepatocytes and some cell lines with a high degree of sensitivity and specificity (allowing the quantitation of closely related CYPs). Although CYP induction is not usually considered as a major drawback in drug development, the aim should be to eliminate or reduce the inducing effects of a new drug to a minimum. Thus, it is essential to increase our understanding of the complex mechanisms that regulate induction and to pay attention to both the dose and the physicochemical and structural properties of CYP inducing agents.

Substrates of human cytochromes P450 from families CYP1 and CYP2: analysis of enzyme selectivity and metabolism.

A compilation of information relating to substrate metabolism via human cytochromes P450 (CYP) from the CYP1 and CYP2 families is reported. The data presented include details of preferred sites of metabolism and Km values (usually for the expressed enzymes) for each reaction for selected substrates of CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6 and CYP2E1. Although other P450 databases are available, they do not provide such information as is collated here, and which can prove useful for comparing P450 substrate characteristics. This information can be employed in analysing the structural requirements for human P450 enzyme selectivity and for establishing various rules regarding preferred site of metabolism for selective P450 substrates. For example, in most cases it would appear that there is a set number of intervening 'heavy' atoms (atoms other than hydrogen) between sites of metabolism and key hydrogen bond acceptors (or donors) for human P450 substrates, with the number of intervening atoms being dependent upon the type of P450 involved.

Compound lipophilicity for substrate binding to human P450s in drug metabolism.

Compound lipophilicity is of key importance to P450 binding affinity and enzyme selectivity. Here, lipophilicity is discussed with reference to the human drug-metabolizing P450 enzymes of families CYP1, CYP2 and CYP3. From an extensive compilation of log P values for P450 substrates, and by analysis of relationships between partitioning energy and substrate-binding free energy, the relevance of lipophilicity and other factors pertaining to P450 binding affinity is explained, leading to the formulation of lipophilicity relationships within substrates of each human P450 enzyme involved in drug metabolism. Furthermore, log P values for P450 substrates appear to represent markers for enzyme selectivity. Together with the important roles of hydrogen bonding and pi-pi stacking interaction energies, the desolvation of the P450 active site makes a major contribution to the overall substrate-binding energy and, consequently, a good agreement with experimental information is reported based on this analysis.

A molecular model of CYP2D6 constructed by homology with the CYP2C5 crystallographic template: investigation of enzyme-substrate interactions.

The results of homology modelling of CYP2D6 based on the mammalian P450 crystal structure of rabbit CYP2C5 are reported. It is found that many CYP2D6-selective substrates are able to fit closely within the putative active site of the enzyme where there are favourable contacts with complementary amino acid residues, including aspartate-301 which has been probed via site-directed mutagenesis. The homology model of CYP2D6 is consistent with available experimental evidence from selective substrate metabolism and site-specific mutation data. Quantitative structure-activity relationships (QSARs) with substrate binding affinity based on KD values and inhibition data (Ki values) demonstrate the importance of hydrogen bonding, pi-pi stacking and relative molecular mass in describing variations in avidity towards the CYP2D6 enzyme, although the compound lipophilicity (log D(7.4)) appears to be the most important single descriptor for CYP2D6 inhibition. Calculation of substrate binding affinity based on contributions from active site interactions and lipophilic character gives satisfactory agreement with experimentally determined KD values.