Biopharmaceutical characterization of sotalol-containing oral immediate release drug products

Informing a Comprehensive Risk Assessment of Infant Drug Exposure From Human Milk: Application of a Physiologically Based Pharmacokinetic Lactation Model for Sotalol

Characterization of infant drug exposure through human milk is important and underexplored. Because infant plasma concentrations are not frequently collected in clinical lactation studies, modeling and simulation approaches can integrate physiology, available milk concentrations, and pediatric data to inform exposure in breastfeeding infants. A physiologically based pharmacokinetic model was built for sotalol, a renally eliminated drug, to simulate infant drug exposure from human milk. Intravenous and oral adult models were built, optimized, and scaled to an oral pediatric model for a breastfeeding-relevant age group (<2 years). Model simulations captured the data that were put aside for verification. The resulting pediatric model was applied to predict the impacts of sex, infant body size, breastfeeding frequency, age, and maternal dose (240 and 433 mg) on drug exposure during breastfeeding. Simulations suggest a minimal effect of sex or frequency on total sotalol exposure. Infants in the 90th percentile in height and weight have predicted exposures ≈20% higher than infants of the same age in the 10th percentile due to increased milk intake. The simulated infant exposures increase throughout the first 2 weeks of life and are maintained at the highest concentrations in weeks 2-4, with a consistent decrease observed as infants age. Simulations suggest that breastfeeding infants will have plasma concentrations in the lower range observed in infants administered sotalol. With further validation on additional drugs, physiologically based pharmacokinetic modeling approaches could use lactation data to a greater extent and provide comprehensive information to support decisions regarding medication use during breastfeeding.

Absorption sites of orally administered drugs in the small intestine

INTRODUCTION

In pharmacotherapy, drugs are mostly taken orally to be absorbed systemically from the small intestine, and some drugs are known to have preferential absorption sites in the small intestine. It would therefore be valuable to know the absorption sites of orally administered drugs and the influencing factors. Areas covered:In this review, the author summarizes the reported absorption sites of orally administered drugs, as well as, influencing factors and experimental techniques. Information on the main absorption sites and influencing factors can help to develop ideal drug delivery systems and more effective pharmacotherapies. Expert opinion: Various factors including: the solubility, lipophilicity, luminal concentration, pKa value, transporter substrate specificity, transporter expression, luminal fluid pH, gastrointestinal transit time, and intestinal metabolism determine the site-dependent intestinal absorption. However, most of the dissolved fraction of orally administered drugs including substrates for ABC and SLC transporters, except for some weakly basic drugs with higher pKa values, are considered to be absorbed sequentially from the proximal small intestine. Securing the solubility and stability of drugs prior to reaching to the main absorption sites and appropriate delivery rates of drugs at absorption sites are important goals for achieving effective pharmacotherapy.

Predictive Performance of Physiologically Based Pharmacokinetic and Population Pharmacokinetic Modeling of Renally Cleared Drugs in Children

Predictive performance of physiologically based pharmacokinetic (PBPK) and population pharmacokinetic (PopPK) models of drugs predominantly eliminated through kidney in the pediatric population was evaluated. After optimization using adult clinical data, the verified PBPK models can predict 33 of 34 drug clearance within twofold of the observed values in children 1 month and older. More specifically, 10 of 11 of predicted clearance values were within 1.5‐fold of those observed in children between 1 month and 2 years old. The PopPK approach also predicted 19 of 21 drug clearance within twofold of the observed values in children. In summary, our analysis demonstrated both PBPK and PopPK adult models, after verification with additional adult pharmacokinetic (PK) studies and incorporation of known ontogeny of renal filtration, could be applied for dosing regimen recommendation in children 1 month and older for renally eliminated drugs in a first‐in‐pediatric study.

Caco-2 Cells, Biopharmaceutics Classification System (BCS) and Biowaiter

Almost all orally administered drugs are absorbed across the intestinal mucosa. The Caco-2 monolayers are used as an in vitro model to predict drug absorption in humans and to explore mechanism of drug absorption. The Caco-2 cells are derived from a human colon adenocarcinoma and spontaneously differentiate to form confluent monolayer of polarized cells structurally and functionally resembling the small intestinal epithelium. For studying drug permeability, Caco-2 cells are seeded onto the Transwell inserts with semipermeable membrane and grown to late confluence (21 days). After determination of cell viability, the integrity of monolayer is checked by phenol red permeability and by 14C-mannitol permeability. The transport from apical to basolateral (AP-BL) and basolateral to apical (BL-AP) is studied by adding the diluted drug on the apical or basolateral side and withdrawing the samples from the opposite compartment, respectively, for HPLC analysis or liquid scintillation spectrometry. Ca2+- free transport medium is used to determine paracellular component of the drug transport. On the basis of permeability and solubility, drugs can be categorized into four classes of Biopharmaceutics Classification System (BCS). For certain drugs, the BCS-based biowaiver approach can be used which enables to reduce in vivo bioequivalence studies.

Biopharmaceutics classification system: importance and inclusion in biowaiver guidance

Pharmacological therapy is essential in many diseases treatment and it is important that the medicine policy is intended to offering safe and effective treatment with affordable price to the population. One way to achieve this is through biowaiver, defined as the replacement of in vivo bioequivalence studies by in vitro studies. For biowaiver of new immediate release solid oral dosage forms, data such as intestinal permeability and solubility of the drug are required, as well as the product dissolution. The Biopharmaceutics Classification System (BCS) is a scientific scheme that divides drugs according to their solubility and permeability and has been used by various guides as a criterion for biowaiver. This paper evaluates biowaiver application, addressing the general concepts and parameters used by BCS, making a historical account of its use, the requirements pertaining to the current legislation, the benefits and risks associated with this decision. The results revealed that the use of BCS as a biowaiver criterion greatly expands the therapeutics options, contributing to greater therapy access of the general population with drug efficacy and safety guaranteed associated to low cost.

Physiologically based pharmacokinetic models in the prediction of oral drug exposure over the entire pediatric age range-sotalol as a model drug

In recent years, the increased interest in pediatric research has enforced the role of physiologically based pharmacokinetic (PBPK) models in pediatric drug development. However, an existing lack of published examples contributes to some uncertainties about the reliability of their predictions of oral drug exposure. Developing and validating pediatric PBPK models for oral drug application shall enrich our knowledge about their limitations and lead to a better use of the generated data. This study was conducted to investigate how whole-body PBPK models describe the oral pharmacokinetics of sotalol over the entire pediatric age. Two leading software tools for whole-body PBPK modeling: Simcyp® (Simcyp Ltd, Sheffield, UK) and PK-SIM® (Bayer Technology Services GmbH, Leverkusen, Germany), were used. Each PBPK model was first validated in adults before scaling to children. Model input parameters were collected from the literature and clinical data for 80 children were used to compare predicted and observed values. The results obtained by both models were comparable and gave an adequate description of sotalol pharmacokinetics in adults and in almost all pediatric age groups. Only in neonates, the mean ratio_(Obs/Pred) for any PK parameter exceeded a twofold error range, 2.56 (95% confidence interval (CI), 2.10–3.49) and 2.15 (95% CI, 1.77–2.99) for area under the plasma concentration-time curve from the first to the last concentration point and maximal concentration (C_max) using SIMCYP® and 2.37 (95% CI, 1.76–3.25) for time to reach C_max using PK-SIM®. The two PBPK models evaluated in this study reflected properly the age-related pharmacokinetic changes and predicted adequately the oral sotalol exposure in children of different ages, except in neonates.

Drug discovery and regulatory considerations for improving in silico and in vitro predictions that use Caco-2 as a surrogate for human intestinal permeability measurements

There is a growing need for highly accurate in silico and in vitro predictive models to facilitate drug discovery and development. Results from in vitro permeation studies across the Caco-2 cell monolayer are commonly used for drug permeability screening in industry and are also accepted as a surrogate for human intestinal permeability measurements by the US FDA to support new drug applications. Countless studies carried out in this cell line with published permeability measurements have enabled the development of many in silico prediction models. We identify several common cases that illustrate how using Caco-2 permeability measurements in these in silico and in vitro predictive models will not correlate with human intestinal permeability and will further lead to inaccuracies in these models. We provide guidelines and recommendations for improving these models to more accurately predict clinically relevant information, thereby enhancing the drug discovery, development, and regulatory approval processes.

Sotalol permeability in cultured-cell, rat intestine, and PAMPA system

PURPOSE

To clarify sotalol's classification in the BCS versus BDDCS systems through cellular, rat everted sac and PAMPA permeability studies.

METHODS

Studies were carried out in Madin Darby canine kidney (MDCK) and MDR1-transfected MDCK (MDCK-MDR1) cell lines, rat everted gut sacs and the Parallel Artificial Membrane Permeability Assay (PAMPA) system. Three-hour transport studies were conducted in MDCK cell lines (with apical pH changes) and MDCK-MDR1 cells (with and without the P-glycoprotein inhibitor GG918); male Sprague-Dawley rats (300~350 g) were used to prepare everted sacs. In the PAMPA studies, drug solutions at different pH's were dosed in each well and incubated for 5 h. Samples were measured by LC-MS/MS, or liquid scintillation counting and apparent permeability (P(app)) was calculated.

RESULTS

Sotalol showed low permeability in all of the cultured-cell lines, everted sacs and PAMPA systems. It might be a border line P-glycoprotein substrate. The PAMPA study showed that sotalol's permeability increased with a higher apical pH, while much less change was found in MDCK cells.

CONCLUSION

The low permeability rate for sotalol correlates with its Class 3 BDDCS assignment and lack of in vivo metabolism.

Improving the prediction of the brain disposition for orally administered drugs using BDDCS

In modeling blood-brain barrier (BBB) passage, in silico models have yielded ~80% prediction accuracy, and are currently used in early drug discovery. Being derived from molecular structural information only, these models do not take into account the biological factors responsible for the in vivo outcome. Passive permeability and P-glycoprotein (Pgp, ABCB1) efflux have been successfully recognized to impact xenobiotic extrusion from the brain, as Pgp is known to play a role in limiting the BBB penetration of oral drugs in humans. However, these two properties alone fail to explain the BBB penetration for a significant number of marketed central nervous system (CNS) agents. The Biopharmaceutics Drug Disposition Classification System (BDDCS) has proved useful in predicting drug disposition in the human body, particularly in the liver and intestine. Here we discuss the value of using BDDCS to improve BBB predictions of oral drugs. BDDCS class membership was integrated with in vitro Pgp efflux and in silico permeability data to create a simple 3-step classification tree that accurately predicted CNS disposition for more than 90% of 153 drugs in our data set. About 98% of BDDCS class 1 drugs were found to markedly distribute throughout the brain; this includes a number of BDDCS class 1 drugs shown to be Pgp substrates. This new perspective provides a further interpretation of how Pgp influences the sedative effects of H1-histamine receptor antagonists.

High-permeability criterion for BCS classification: segmental/pH dependent permeability considerations

The FDA classifies a drug substance as high-permeability when the fraction of dose absorbed (F(abs)) in humans is 90% or higher. This direct correlation between human permeability and F(abs) has been recently controversial, since the β-blocker sotalol showed high F(abs) (90%) and low Caco-2 permeability. The purpose of this study was to investigate the scientific basis for this disparity between permeability and F(abs). The effective permeabilities (P(eff)) of sotalol and metoprolol, a FDA standard for the low/high P(eff) class boundary, were investigated in the rat perfusion model, in three different intestinal segments with pHs corresponding to the physiological pH in each region: (1) proximal jejunum, pH 6.5; (2) mid small intestine, pH 7.0; and (3) distal ileum, pH 7.5. Both metoprolol and sotalol showed pH-dependent permeability, with higher P(eff) at higher pH. At any given pH, sotalol showed lower permeability than metoprolol; however, the permeability of sotalol determined at pH 7.5 exceeded/matched metoprolol's at pH 6.5 and 7.0, respectively. Physicochemical analysis based on ionization, pK(a) and partitioning of these drugs predicted the same trend and clarified the mechanism behind these observed results. Experimental octanol-buffer partitioning experiments confirmed the theoretical curves. An oral dose of metoprolol has been reported to be completely absorbed in the upper small intestine; it follows, hence, that metoprolol's P(eff) value at pH 7.5 is not likely physiologically relevant for an immediate release dosage form, and the permeability at pH 6.5 represents the actual relevant value for the low/high permeability class boundary. Although sotalol's permeability is low at pH 6.5 and 7.0, at pH 7.5 it exceeds/matches the threshold of metoprolol at pH 6.5 and 7.0, most likely responsible for its high F(abs). In conclusion, we have shown that, in fact, there is no discrepancy between P(eff) and F(abs) in sotalol's absorption; the data emphasize that, if a compound has high fraction of dose absorbed, it will have high-permeability, not necessarily in the jejunum, but at some point along the relevant intestinal regions.

The use of drug metabolism for prediction of intestinal permeability (dagger)

The Biopharmaceutics Classification System (BCS), based on the aqueous solubility and intestinal permeability of a drug substance, has been widely used to predict the extent of drug absorption during the course of pharmaceutical development. Combined with product dissolution data, this system has gained a prominent role in regulatory process to determine if a drug formulated in an immediate release solid oral dosage form qualifies for waiver of in vivo bioequivalence studies. In parallel, the Biopharmaceutics Drug Disposition Classification System (BDDCS), using aqueous solubility and drug metabolism, takes on another venue to predict overall drug disposition. It has been suggested that the matrix of drug metabolism in BDDCS can be used to substantiate the classification of permeability by BCS. A total of 51 drugs were compiled in this study to examine the use of drug metabolism for predicting permeability. All compounds were classified as high permeability based on BCS, but only 73% of the compounds were found to exhibit extensive metabolism. Lipophilicity accounts for significant metabolism of many highly permeable drugs. Fourteen (14) out of 51 drugs have poor metabolism, suggesting that high permeability as defined by BCS does not necessarily dictate extensive metabolism. The drugs that have high permeability but poor metabolism are generally hydrophilic molecules with low molecular weight and are likely to be absorbed by active transport mechanisms. Based on the present data and literature information, it seems logical to predict that the extent of absorption is mostly complete (or > or =90%) if the drug is subject to a high degree of metabolism (e.g., > or =90%). The extent of drug metabolism may be useful in supporting permeability classification under certain circumstances.

Review of global regulations concerning biowaivers for immediate release solid oral dosage forms

The regulations with respect to biowaivers for immediate release (IR) solid oral dosage forms in the USA, the EU, Japan and from the World Health Organization (WHO) are summarized and compared. Two case studies are presented, one from our own files and one from the open literature, showing the similarities and the differences among the qualification requirements of the four systems. The regulatory experience gained up to now is reviewed and expected future trends are discussed.