pH-Dependent Solubility and Permeability Criteria for

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pH-Dependent Solubility and Permeability Criteria for Provisional Biopharmaceutics Classification (BCS and BDDCS) in Early Drug Discovery Manthena V. Varma,† Iain Gardner,‡ Stefanus J. Steyn,† Paul Nkansah,† Charles J. Rotter,† Carrie Whitney-Pickett,† Hui Zhang,† Li Di,† Michael Cram,‡ Katherine S. Fenner,‡ and Ayman F. El-Kattan*,† †

Pfizer Global Research and Development, Pfizer Inc., Groton, Connecticut 06340, United States Pfizer Global Research and Development, Pfizer Inc., Sandwich, Kent, CT13 9NJ, U.K.



ABSTRACT: The Biopharmaceutics Classification System (BCS) is a scientific framework that provides a basis for predicting the oral absorption of drugs. These concepts have been extended in the Biopharmaceutics Drug Disposition Classification System (BDDCS) to explain the potential mechanism of drug clearance and understand the effects of uptake and efflux transporters on absorption, distribution, metabolism, and elimination. The objective of present work is to establish criteria for provisional biopharmaceutics classification using pH-dependent passive permeability and aqueous solubility data generated from high throughput screening methodologies in drug discovery settings. The apparent permeability across monolayers of clonal cell line of Madin−Darby canine kidney cells, selected for low endogenous efflux transporter expression, was measured for a set of 105 drugs, with known BCS and BDDCS class. The permeability at apical pH 6.5 for acidic drugs and at pH 7.4 for nonacidic drugs showed a good correlation with the fraction absorbed in human (Fa). Receiver operating characteristic (ROC) curve analysis was utilized to define the permeability class boundary. At permeability ≥5 × 10−6 cm/s, the accuracy of predicting Fa of ≥0.90 was 87%. Also, this cutoff showed more than 80% sensitivity and specificity in predicting the literature permeability classes (BCS), and the metabolism classes (BDDCS). The equilibrium solubility of a subset of 49 drugs was measured in pH 1.2 medium, pH 6.5 phosphate buffer, and in FaSSIF medium (pH 6.5). Although dose was not considered, good concordance of the measured solubility with BCS and BDDCS solubility class was achieved, when solubility at pH 1.2 was used for acidic compounds and FaSSIF solubility was used for basic, neutral, and zwitterionic compounds. Using a cutoff of 200 μg/mL, the data set suggested a 93% sensitivity and 86% specificity in predicting both the BCS and BDDCS solubility classes. In conclusion, this study identified pH-dependent permeability and solubility criteria that can be used to assign provisional biopharmaceutics class at early stage of the drug discovery process. Additionally, such a classification system will enable discovery scientists to assess the potential limiting factors to oral absorption, as well as help predict the drug disposition mechanisms and potential drug−drug interactions. KEYWORDS: Biopharmaceutics Classification System (BCS), Biopharmaceutics Drug Disposition Classification System (BDDCS), solubility, intestinal permeability, high throughput screening



INTRODUCTION Solubility and permeability are considered to be pivotal properties that determine drug absorption following oral administration. Based on these fundamental properties, Amidon et al. proposed a biopharmaceutics classification system (BCS), which serves as a guide for regulatory and industrial purposes to waive conducting expensive bioequivalence clinical studies (BE) for high solubility-high permeability (class I) drugs.1−3 According to the US Food and Drug Administration (FDA) guidance, 2 a drug substance is considered highly soluble when the highest dose strength is soluble in 250 mL or less of aqueous medium over the pH range of 1−7.5. The volume estimate of 250 mL is derived from typical BE study protocols that prescribe administration of a drug product to fasting human volunteers with 250 mL of © 2012 American Chemical Society

water. A drug substance is considered highly permeable when the extent of absorption (Fa) is ≥90% of oral dose. Permeability class can be determined by estimating the extent of drug absorption in human oral pharmacokinetic studies in comparison to intravenous reference dose or mass-balance studies or by measuring the human effective permeability (Peff) across the jejunum membrane.4,5 Alternatively, tools like in situ rat intestinal perfusion and in vitro epithelial cell culture models, that are appropriately validated to predict the extent of Received: Revised: Accepted: Published: 1199

September 29, 2011 March 23, 2012 April 10, 2012 April 10, 2012 dx.doi.org/10.1021/mp2004912 | Mol. Pharmaceutics 2012, 9, 1199−1212

Molecular Pharmaceutics

Article

appropriate chemistry strategies during lead optimization and candidate selection. We determined pH-dependent solubility and permeability in a high throughput setting for a set of over 100 drugs with known BCS and BDDCS class. Apparent permeability determined across monolayers of low-efflux Madin−Darby canine kidney (MDCK-LE) cells was validated against human jejunum effective permeability (human Peff); and a pH-dependent permeability criterion was defined for provisional biopharmaceutics classification, based on the relationship between permeability and human intestinal absorption (human Fa). Equilibrium solubility in pH 1.2 for acids and in fasted-state simulated intestinal fluid (FaSSIF) medium for nonacids (bases, neutrals, and zwitterions) was used to define solubility boundary. The provisional biopharmaceutics classification based on the current pH-dependent permeability and solubility criteria showed good agreement with both BCS and BDDCS.

drug absorption in humans, can be used for permeability classification.6 Several high throughput (HT) screening methods for measuring permeability and solubility have been previously reported for BCS classification and estimating the oral absorption of druglike molecules.7 Cell-based permeability assays utilizing Caco-2, Madin−Darby canine kidney (MDCK), and recently the low efflux-MDCK cell lines have been employed in discovery settings.8−11 Similarly, the parallel artificial membrane permeation assay (PAMPA) has been established as an alternative to cell-based assays for predicting oral absorption.12,13 Also, several HT solubility assays are used to screen large numbers of druglike molecules in early drug discovery stage.14−17 In most cases, compounds are introduced as the dimethyl sulfoxide (DMSO) stock solution and the nonthermodynamic solubility is estimated typically in pH buffer at 7.4.7 However, the solubility data generated under thermodynamic equilibrium conditions represents the best case scenario.14 The solubility is quantified utilizing a UV plate reader and liquid chromatography with UV or mass spectrometry, after equilibration and filtration, or determined in situ by turbidimetric or nephelometric methods.16−18 Although solubility and permeability data are often generated in HT format, a clear strategy of how to use the data to assign compounds into biopharmaceutics classes has not been presented in discovery settings. While the pharmaceutical industry has taken advantage of BCS-based biowaivers, its principles are used throughout drug discovery and development to drive oral active programs.6 On the basis of the apparent correlation between intestinal permeability and extent of drug metabolism, Benet and coworkers proposed the Biopharmaceutics Drug Disposition Classification System (BDDCS), where drugs are categorized in terms of the extent of metabolism and solubility.19−21 The group noted that the major route of elimination in humans for a majority of high-permeability class I and class II drugs was metabolism, predominantly cytochrome P450-mediated, with an extent of metabolism ≥70%; while the major route of elimination for the poorly permeable (classes III and IV) drugs was renal and/or biliary excretion of unchanged drug with an overall extent of metabolism ≤30%. Interestingly, most drugs are either very highly metabolized or very poorly metabolized, and a relatively few drugs showed the extent of metabolism between 30% and 70%. Based on the established concordance between the intestinal permeability and the extent of drug metabolism, if an efficient measure of intestinal permeability rate is identified and the relationship established, it would be possible to use these permeability values to predict the major route of elimination for new molecular entities (NME) in humans in early discovery. The objective of the present study was to determine if the data generated using HT permeability and solubility assays could be used early in the drug discovery process to provide provisional biopharmaceutics classification for new molecular entities (NMEs). This will be pivotal in enabling discovery teams to flag potential liabilities for oral absorption and predict the clearance mechanism and the potential for drug−drug interaction. Even though there are many of unknowns at the early stage of drug discovery, such as dose, dissolution rate, final solid form, clearance, route of elimination, etc., the provisional biopharmaceutics classification may help project teams calibrate NME against BCS and BDDCS. Additionally, such a classification scheme can be used to guide teams to develop



MATERIALS AND METHODS Materials. All drugs or test compounds were obtained from Pfizer Global Material Management (Groton, CT) or purchased from Sigma-Aldrich (St. Louis, MO). Minimum essential medium (MEM) with L-glutamine, ribo/deoxyribo nucleosides, heat inactivated fetal bovine serum (FBS), nonessential amino acids (NEAA), penicillin−streptomycin (Pen/Strep), L-glutamine and 0.25% trypsin−EDTA, Hanks balanced salt solution with CaCl2, D-glucose, HEPES, and MgCl2 were purchased from Gibco Laboratories (Grand Island, NY). The 96-Transwell insert plates with polyethylene terephthalate membrane (1 μm pore size, including 96-well membrane inserts and feeder tray), 96-well angled bottom collection plates, and velocity V11 peelable seals were purchased from BD Falcon (Bedford, MA). All other reagents were of analytical grade. Cell Culture and High Throughput Permeability Assay. The cell culturing conditions for in-house low efflux transporter MDCK (MDCK-LE) cell line (clonal cells isolated from Madin−Darby canine kidney cells, selected for low endogenous efflux transporter expression) were discussed elsewhere.10 Briefly, MDCK-LE cells were cultured at 37 °C, 5% CO2, 95% relative humidity in minimum essential medium that contained 10% FBS, 1% NEAA, 100 U/mL penicillin, 100 μg/mL streptomycin, and 1% L-glutamine. Cells were passaged each week at about 90%, confluency. Cells were trypsinized and resuspended in complete media to obtain a cell suspension of 2.5 × 105 cells/mL, and then plated onto 96-well membrane inserts, with each insert receiving a volume of 75 μL. The inserts were placed into a feeder tray containing complete growth medium. Plates were used on day 4 for transport studies. Cell inserts were washed with prewarmed transport buffer before the experiment. Monodirectional transport studies were performed with 2 μM drug solution in transport buffer with 0.1% DMSO. Drug solution was added to the donor wells and buffer was added the receiver wells to initiate the transport assay (in-house screening code: RRCKG_01). The plates were incubated at 37 °C, and samples from both the donor and receiver were taken at time 0 min and 90 min for analysis. Permeability was determined at donor pH 6.5 and 7.4, with receiver medium pH always 7.4. Drugs were quantified in the samples using LC−MS/MS methodology. Pfizer research compound (CP-628374) was used as an internal standard for LC−MS in both positive and 1200

dx.doi.org/10.1021/mp2004912 | Mol. Pharmaceutics 2012, 9, 1199−1212

Molecular Pharmaceutics

Article

negative ionization modes. LC−MS/MS analysis was conducted on a Sciex Triple Quad 4000 mass spectrometer (turbospray ionization source) with a Shimadzu LC-10 HPLC system and Gilson 215 autosampler. The mass spectrometer was controlled by Analyst 1.4.2 software. The Gilson autosampler was independently controlled by Gilson 735 software and synchronized to Analyst via contact closure. The LC method consisted of a step gradient with 25 μL samples loaded onto a 1.5 × 5 mm Showadenko ODP 13 μm particle size column using 95% ammonium acetate buffer (2 mM), 2.5% methanol and 2.5% acetonitrile. Samples were eluted with 10% ammonium acetate buffer (2 mM), 45% methanol, and 45% acetonitrile. MS/MS parameters utilized either negative or positive ionization mode depending on the compound. Peak area counts of analyte compound and internal standard were integrated using DiscoveryQuant Analyze as an add-on to Analyst 1.4.2. High Throughput Equilibrium Solubility Assay. Equilibrium solubility of 49 drugs was measured in simulated gastric fluid without pepsin (SGF) at pH 1.2, in 50 mM phosphate buffer (PBS) at pH 6.5, and in fasted-state simulated intestinal fluid (FaSSIF) at pH 6.5. An in-house fully automated HT method (screen code: SW_BIORE_SOL) was used to perform all solubility and pH measurements. The HT platform consisted of an integrated robotic system with a powder dispensing and liquid handling of compounds, a robotic arm for plate transfer between robots and peripherals such as heater/ cooler shakers, vacuum filtration unit, plate sealer, GR4 centrifuge, and a customized Microlab probe for pH measurement. The protocol used for the solubility studies involved weighing out each solid compound in triplicate onto sample plates using the powder dispenser. To each sample one of three media (SGF pH 1.2, PBS pH 6.5 and FeSSIF pH 6.5) was added. Sample plates were then sealed and shaken for 18 h at room temperature. After incubation, the insoluble portion was removed through 0.5 μm filtration plates. The sample plates are unsealed, and the final pH of samples was measured. The filtrates were diluted, and an autosampler delivered samples to a LC−MS single-quadrupole (SQ) mass detector to determine the concentrations of dissolved drug. The equilibrium solubility of the test compound was determined against a calibration curve. For versatility and to increase the throughput the LC was in-turned coupled with multiwavelength UV (λ = 210−400 nm) plate reader for recording the full UV absorption spectra of samples passing through the LC detector. Crystallinity of the undissolved drug after incubation was determined using polarized light microscopy (PLM). In order to balance sample consumption, throughput, analytical detection, and data quality, the current HT equilibrium solubility screen was developed and validated with a focus on low soluble compounds typically encountered in early drug discovery space. Consequently the screen was designed for a dynamic range of 0.3−300 μg/mL in all media. Therefore, in cases where the measured solubility exceeded the limits of the assay, they were reported with the qualifier, “≤0.3 μg/mL” or “≥300 μg/mL”. Data Analysis. The absorptive (AP-to-BL) transepithelial transport was represented as permeability value (Papp, cm/s) calculated using the following equation:10 Papp =

dM r 1 × area × C D(0) dt

where area is the surface area of the cell monolayer (0.0625 cm2), CD(0) the initial concentration of compound applied to the donor chamber, and Mr the mass of drug in the receiver compartment, at time t. The complete radial mixing (parallel tube) model, as suggested by Fagerholm et al., was used to predict the human Fa from human effective permeability (Peff) and apparent MDCK-LE permeability (Papp).22,23 Fa = 1 − e−(2APapp

Tres r ·2.8)

(2)

where Tres and r are the average human small intestinal transit time and radius, and are assumed to be 3 h and 1.75 cm, respectively. A is a constant, defining the relationship between human effective permeability and the measured apparent permeability, obtained by fitting the data. Correction factor, fvalue was set at 2.8.22 Binary Classification and Receiver Operating Characteristic (ROC) Analysis. Sensitivity, specificity, and accuracy are statistical measures of the performance of a binary classification test and are measured as shown in eqs 3 and 4. Sensitivity measures the ratio of actual positives that are correctly identified, whereas specificity is defined as the ratio of negatives selected by the test to the true negatives. sensitivity =

true positives true positives + false negatives

(3)

specificity =

true negatives true negatives + false positives

(4)

ROC curve analysis was used to determine a permeability cutoff for high human Fa and test the predictability of the obtained cutoff value. The ROC curve depends on the calculation of sensitivity and specificity.24 The area under the curve (AUC) of a ROC curve can be used as a diagnostic of the performance of the test, where an AUC of 1 would mean that the test is 100% specific and sensitive, while an AUC of 0.5 or below indicates random prediction. In general, an AUC value equal to or larger than 0.8 is usually regarded as acceptable.24,25 For obtaining permeability boundary, we defined human Fa greater than or equal to 80% or 90% as true positives and human Fa less than 80% or 90% as true negatives. The point that has the shortest distance to zero on x-axis and one on y-axis (i.e., the point having both sensitivity and specificity of 1) represented the cutoff value.



RESULTS Data Set. A list of 130 drugs and compounds, for which BCS class was assessed and listed by Custodio et al.,26 was the initial source for the current work. When a drug was listed in more than one class, the most appropriate class was assigned based on further literature assessment. Except for compounds like glucose and phenylalanine, the majority of the drugs were evaluated for permeability using the in-house MDCK-LE model.10 Permeability data for 105 drugs was available after considering the assay recovery (70−120%) and reproducibility (coefficient of variance