Biowaiver Monographs for Immediate-Release Solid Oral Dosage Forms: Enalapril

Coupling Drug Dissolution with BCS

PURPOSE

The purpose of this study is to develop a Temporal Biopharmaceutic Classification System (T-BCS), linking Finite Dissolution Time (F.D.T.) and Mean Dissolution Time (M.D.T.) for Class I/III drugs and Mean Dissolution Time for saturation (M.D.T.s.) for Class II/IV drugs.

METHODS

These parameters are estimated graphically or by fitting dissolution models to experimental data and coupled with the dose-to-solubility ratio (q) for each drug normalized in terms of the actual volume of dissolution medium (900 mL).

RESULTS

Class I/III drugs consistently exhibited q values less than 1, aligning with expectations based on their solubility, while some Class II/IV drugs presented a deviation from anticipated q values, with observations of q < 1. This irregularity was rendered to the dissolution volume of 250 mL used for biopharmaceutical classification purposes instead of 900 mL applied as well as the dual classification of some sparingly soluble drugs. Biowaivers were also analyzed in terms of M.D.T., F.D.T. estimates and the regulatory dissolution time limits for rapidly and very-rapidly dissolved drugs.

CONCLUSIONS

The T-BCS is useful for establishing correlations and assessing the magnitude of M.D.T., F.D.T., or M.D.T.s. for inter- and intra-class comparisons of different drugs and provide relationships between these parameters across all the models that were utilized.

IVIVC Revised

PURPOSE

To revise the IVIVC considering the physiologically sound Finite Absorption Time (F.A.T.) and Finite Dissolution Time (F.D.T.) concepts.

METHODS

The estimates τ and τd for F.A.T. and F.D.T., respectively are constrained by the inequality τd ≤ τ; their relative magnitude is dependent on drug's BCS classification. A modified Levy plot, which includes the time estimates for τ and τd was developed. IVIVC were also considered in the light of τ and τd estimates. The modified Levy plot of theophylline, a class I drug, coupled with the rapid (30 min) and very rapid (15 min) dissolution time limits showed that drug dissolution/absorption of Class I drugs takes place in less than an hour. We reanalyzed a carbamazepine (Tegretol) bioequivalence study using PBFTPK models to reveal its complex absorption kinetics with two or three stages.

RESULTS

The modified Levy plot unveiled the short time span (~ 2 h) of the in vitro dissolution data in comparison with the duration of in vivo dissolution/absorption processes (~ 17 h). Similar results were observed with the modified IVIVC plots. Analysis of another set of carbamazepine data, using PBFTPK models, confirmed a three stages absorption process. Analysis of steady-state (Tegretol) data from a paediatric study using PBFTPK models, revealed a single input stage of duration 3.3 h. The corresponding modified Levy and IVIVC plots were found to be nonlinear.

CONCLUSIONS

The consideration of Levy plots and IVIVC in the light of the F.A.T. and F.D.T. concepts allows a better physiological insight of the in vitro and in vivo drug dissolution/absorption processes.

Adapting physiologically-based pharmacokinetic models for machine learning applications

Both machine learning and physiologically-based pharmacokinetic models are becoming essential components of the drug development process. Integrating the predictive capabilities of physiologically-based pharmacokinetic (PBPK) models within machine learning (ML) pipelines could offer significant benefits in improving the accuracy and scope of drug screening and evaluation procedures. Here, we describe the development and testing of a self-contained machine learning module capable of faithfully recapitulating summary pharmacokinetic (PK) parameters produced by a full PBPK model, given a set of input drug-specific and regimen-specific information. Because of its widespread use in characterizing the disposition of orally administered drugs, the PBPK model chosen to demonstrate the methodology was an open-source implementation of a state-of-the-art compartmental and transit model called OpenCAT. The model was tested for drug formulations spanning a large range of solubility and absorption characteristics, and was evaluated for concordance against predictions of OpenCAT and relevant experimental data. In general, the values predicted by the ML models were within 20% of those of the PBPK model across the range of drug and formulation properties. However, summary PK parameter predictions from both the ML model and full PBPK model were occasionally poor with respect to those derived from experiments, suggesting deficiencies in the underlying PBPK model.

Studies on charge transfer of enalapril maleate: from solid-state to molecular dynamics

INTRODUCTION

Enalapril maleate is an antihypertensive ethyl ester pro-drug with two crystalline forms. A network of hydrogen bonds in both polymorphs plays an important role on solid-state stability, charge transfer process and degradation reactions (when exposed to high humidity, temperature and/or pH changes).

COMPUTATIONAL PROCEDURES

Supramolecular arrangement was proposed by Hirshfeld surface using the CrystalExplorer17 software and quantum theory of atoms in molecules. The electronic structure properties were calculated using the functional hybrid M06-2X with 6-311++G** base function employing diffuse and polarization functions to improve the description of hydrogen atoms on intermolecular interactions. Also, the H+ charge transfer between enalapril and maleate molecules was performed using Car-Parrinello molecular dynamics with the Verlet algorithm. In both simulations, the temperature of the ionic system was maintained around 300 K using the Nosé-Hoover thermostat and the electronic system evolved without the use of the thermostat.

RESULTS

This work evaluates the effect of maleate on the structural stability of enalapril maleate solid state. The electronic structural analysis points out a partially covalent character for N1-H∙∙∙O7 interaction; and the molecular dynamic showed a decentralized hydrogen on maleate driving a decomposition by charge transfer process while a centered hydrogen driving the stabilization. The charge transfer process and the mobility of the proton (H+) between enalapril and maleate molecules was demonstrated using supramolecular modeling analyses and molecular dynamics calculations.

Hot-Melt Extrusion of the Thermo-Sensitive Peptidomimetic Drug Enalapril Maleate

The aim of this research was the production of extrudates for the treatment of hypertension and heart failure and the investigation of the degradation of the peptidomimetic drug enalapril maleate (EM) during hot-melt extrusion (HME). A fast HPLC method was developed to quantify enalapril maleate and possible degradation products. Screening experiments revealed that the diketopiperazine derivative (Impurity D) was the main degradation product. Hot-melt extrusion of enalapril maleate with the polymer Soluplus^® enabled extrusion at 100 °C, whereas a formulation with the polymer Eudragit^® E PO could be extruded at only 70 °C. Extrusion at 70 °C prevented thermal degradation. A stabilizing molecular interaction between enalapril maleate and Eudragit^® E PO was identified via FT-IR spectroscopy. Dissolution studies were carried out to study the influence of the formulation on the dissolution behavior of enalapril maleate. These promising results can be transferred to other thermo-sensitive and peptidomimetic drugs to produce extrudates which can be used, for instance, as feedstock material for the production of patient-specific dosage forms via Fused Deposition Modeling (FDM) 3D printing.

Lack of an Effect of Polysorbate 80 on Intestinal Drug Permeability in Humans

PURPOSE

Despite no broad, direct evidence in humans, there is a potential concern that surfactants alter active or passive drug intestinal permeation to modulate oral drug absorption. The purpose of this study was to investigate the impact of the surfactant polysorbate 80 on active and passive intestinal drug absorption in humans.

METHODS

The human (n = 12) pharmacokinetics (PK) of three probe substrates of intestinal absorption, valacyclovir, chenodeoxycholic acid (CDCA), and enalaprilat, were assessed. Endogenous bile acid levels were assessed as a secondary measure of transporter and microbiota impact.

RESULTS

Polysorbate 80 did not inhibit peptide transporter 1 (PepT1)- or apical sodium bile acid transporter (ASBT)-mediated PK of valacyclovir and CDCA, respectively. Polysorbate 80 did not increase enalaprilat absorption. Modest increases in unconjugated secondary bile acid C_max ratios suggest a potential alteration of the in vivo intestinal microbiota by polysorbate 80.

CONCLUSIONS

Polysorbate 80 did not alter intestinal membrane fluidity or cause intestinal membrane disruption. This finding supports regulatory relief of excipient restrictions for Biopharmaceutics Classification System-based biowaivers.

Synthesis, In Silico and In Vitro Evaluation of Antimicrobial and Toxicity Features of New 4-[(4-Chlorophenyl)sulfonyl]benzoic Acid Derivatives

The multi-step synthesis, physico-chemical characterization, and biological activity of novel valine-derived compounds, i.e., N-acyl-α-amino acids, 1,3-oxazol-5(4H)-ones, N-acyl-α-amino ketones, and 1,3-oxazoles derivatives, bearing a 4-[(4-chlorophenyl)sulfonyl]phenyl moiety are reported here. The structures of the newly synthesized compounds were confirmed by spectral (UV-Vis, FT-IR, MS, ¹H- and ¹³C-NMR) data and elemental analysis results, and their purity was determined by RP-HPLC. The new compounds were assessed for their antimicrobial activity and toxicity to aquatic crustacean Daphnia magna. Also, in silico studies regarding their potential mechanism of action and toxicity were performed. The antimicrobial evaluation revealed that the 2-{4-[(4-chlorophenyl)sulfonyl]benzamido}-3-methylbutanoic acid and the corresponding 1,3-oxazol-5(4H)-one exhibited antimicrobial activity against Gram-positive bacterial strains and the new 1,3-oxazole containing a phenyl group at 5-position against the C. albicans strain.

An Assessment of Occasional Bio-Inequivalence for BCS1 and BCS3 Drugs: What are the Underlying Reasons?

Despite having adequate solubility properties, bioequivalence (BE) studies performed on immediate release formulations containing BCS1/3 drugs occasionally fail. By systematically evaluating a set of 17 soluble drugs where unexpected BE failures have been reported and comparing to a set of 29 drugs where no such reports have been documented, a broad assessment of the risk factors leading to BE failure was performed. BE failures for BCS1/3 drugs were predominantly related to changes in C_max rather than AUC. C_max changes were typically modest, with minimal clinical significance for most drugs. Overall, drugs with a sharp plasma peak were identified as a key factor in BE failure risk. A new pharmacokinetic term (t½C_max) is proposed to identify drugs at higher risk due to their peak plasma profile shape. In addition, the analysis revealed that weak acids, and drugs with particularly high gastric solubility are potentially more vulnerable to BE failure, particularly when these features are combined with a sharp C_max peak. BCS3 drugs, which are often characterised as being more vulnerable to BE failure due to their potential for permeation and transit to be altered, particularly by excipient change, were not in general at greater risk of BE failures. These findings will help to inform how biowaivers may be optimally applied in the future.

Development and Validation of an HPLC Method Using an Experimental Design for Analysis of Amlodipine Besylate and Enalapril Maleate in a Fixed-dose Combination

Objectives

The aim of this study was to develop and optimize a simple, cost-effective, and robust high-performance liquid chromatography (HPLC) method by taking an experimental design approach to the assay and dissolution analysis of amlodipine besylate and enalapril maleate from a fixed-dose combination tablet.

Materials and Methods

The chromatographic analysis was performed on a C18 column (4.6x250 mm id., particle size of 5 μm). The injection volume was 5 μL, and the detection wavelength was 215 nm. A Box-Behnken design was used to test the robustness of the method. The flow rate (1, 1.2, and 1.4 mL/min), column temperature (25°C, 30°C, and 35°C), methanol ratio of the mobile phase (5, 10, and 15%), and pH of the mobile phase (2.8, 3, and 3.2) were selected as independent variables. The method was validated according to International Conference on Harmonization guidelines. Dissolution of the tablets was performed by using USP apparatus 2 and analyzed using the optimized HPLC method. Multivariate linear regression analysis and ANOVA were used in the statistical evaluation.

Results

Linear models were fitted for all variables. The flow rate was the most significant factor affecting the APIs' concentrations. The optimized method included the following parameters: Column temperature of 25°C, 10% methanol as the mobile phase, pH of 2.95, and flow rate of 1.205 mL/min. Retention times were 3.8 min and 7.9 min for enalapril and amlodipine, respectively. The method was found to be linear in the range of 0.8-24 μg/mL (R² >0.999) and 1.6-48 μg/mL (R² >0.999) for amlodipine and enalapril, respectively. Both APIs were dissolved more than 85% within 10 min.

Conclusion

The experimental design was proved as a useful tool for the determination and separation of enalapril maleate and amlodipine besylate in dosage forms. The optimized method can be used for in vitro performance and quality control tests of fixed-dose tablet combinations containing enalapril maleate and amlodipine besylate.

Antihypertensive effect of rapeseed peptides and their potential in improving the effectiveness of captopril

BACKGROUND

The main objective of this study was to evaluate the safety and antihypertensive activity of rapeseed peptides and to investigate their potential synergy with captopril.

RESULTS

The peptides were nontoxic with the maximum tolerated dose exceeding 25 g kg^-1 BW d^-1 for mice and they had angiotensin converting enzyme (ACE) inhibitory activity with IC₅₀ value of 1.27 mg mL^-1 . Rapeseed peptides did not have a synergistic effect with captopril on inhibiting ACE activity in simulated digestion tests in vitro. But in vivo they could synergistically augment the amplitude range of lowering blood pressure with captopril by approximately 9% and prolong the antihypertensive effect duration time by over 20% in antihypertension tests of spontaneously hypertensive rats. In addition, the inhibiting effect of rapeseed peptides on ACE activity was noticeable in some rat organs in vivo. Nevertheless, when compared to captopril group, the potential synergy of rapeseed peptides with captopril did not cause a further decrease in ACE activity in the organs but their synergy further improved levels of NO (12.7%) and endothelial nitric oxide synthase (74.1%) in rat serum. Further studies of some peptides identified from rapeseed peptides showed that some of the rapeseed peptides (Cys-Leu, Val-Ala-Pro) could markedly increase contents of NO and endothelial nitric oxide synthase.

CONCLUSIONS

Rapeseed peptides have antihypertensive activity and they showed potential synergy with captopril in antihypertensive performance in vivo. The synergy was not from ACE inhibition but from other pathways, like improvement in endogenous vasodilator contents. © 2020 Society of Chemical Industry.

Identification of the key target profiles underlying the drugs of narrow therapeutic index for treating cancer and cardiovascular disease

An appropriate therapeutic index is crucial for drug discovery and development since narrow therapeutic index (NTI) drugs with slight dosage variation may induce severe adverse drug reactions or potential treatment failure. To date, the shared characteristics underlying the targets of NTI drugs have been explored by several studies, which have been applied to identify potential drug targets. However, the association between the drug therapeutic index and the related disease has not been dissected, which is important for revealing the NTI drug mechanism and optimizing drug design. Therefore, in this study, two classes of disease (cancers and cardiovascular disorders) with the largest number of NTI drugs were selected, and the target property of the corresponding NTI drugs was analyzed. By calculating the biological system profiles and human protein–protein interaction (PPI) network properties of drug targets and adopting an AI-based algorithm, differentiated features between two diseases were discovered to reveal the distinct underlying mechanisms of NTI drugs in different diseases. Consequently, ten shared features and four unique features were identified for both diseases to distinguish NTI from NNTI drug targets. These computational discoveries, as well as the newly found features, suggest that in the clinical study of avoiding narrow therapeutic index in those diseases, the ability of target to be a hub and the efficiency of target signaling in the human PPI network should be considered, and it could thus provide novel guidance in the drug discovery and clinical research process and help to estimate the drug safety of cancer and cardiovascular disease.

Model-dependent pharmacokinetic analysis of enalapril administered to healthy adult volunteers using orodispersible minitablets for use in pediatrics

Introduction

Comparative pharmacokinetic (PK) data analysis of drugs administered using developed child-appropriate and market authorized dosage formulation is sparse and is important in pediatric drug development.

Objectives

To compare and evaluate any differences in PK of enalapril administered using two treatments of child-appropriate orodispersible minitablets (ODMTs) and market authorized reference tablet formulation (Renitec^®) using PK compartment model and validated least square minimization method (LSMM) of parameter estimation.

Methods

Full profile data sets were obtained from a phase I clinical trial, whereby three treatments of enalapril, ie, reference tablets with 240 mL water (treatment A), child-appropriate ODMTs with 240 mL (treatment B), and ODMTs dispersed in the mouth with 20 mL water (treatment C), were administered to 24 healthy adult volunteers. Virtual validation analysis was conducted using R program to select accurate and precise LSMM of parameter estimation. For the selection of PK model and estimation of parameters, enalapril data were fitted with one-and two-compartment models with first order of absorption and elimination, with and without incorporated lag time parameter (tlag). The log-transformed PK parameters were statistically compared by the two-sided paired t-test with the level of significance of P<0.05.

Results

One-compartment model with first-order absorption and elimination and incorporated lag time adequately predicted concentrations of enalapril. Reciprocal of predicted concentration using iteratively reweighted LSMM was selected as the most appropriate method of parameter estimation. Comparison of PK parameters including rate constant of absorption and elimination, volume of distribution, and tlag between the three treatments showed significant difference (P=0.018) in tlag between treatments B and A only.

Conclusion

Compared with reference formulation, enalapril administered from child-appropriate ODMTs administered with 240 mL water appeared 4 minutes earlier in serum. No other differences were observed in absorption, elimination, and relative bioavailability of drug between the three treatment arms.

Application of data mining approach to identify drug subclasses based on solubility and permeability

Solubility and permeability are recognized as key parameters governing drug intestinal absorption and represent the basis for biopharmaceutics drug classification. The Biopharmaceutics Classification System (BCS) is widely accepted and adopted by regulatory agencies. However, currently established low/high permeability and solubility boundaries are the subject of the ongoing scientific discussion. The aim of the present study was to apply data mining analysis on the selected drugs data set in order to develop a human permeability predictive model based on selected molecular descriptors, and to perform data clustering and classification to identify drug subclasses with respect to dose/solubility ratio (D/S) and effective permeability (P_eff ). The P_eff values predicted for 30 model drugs for which experimental human permeability data are not available were in good agreement with the reported fraction of drug absorbed. The results of clustering and classification analysis indicate the predominant influence of P_eff over D/S. Two P_eff cut-off values (1 × 10^-4 and 2.7 × 10^-4  cm/s) have been identified indicating the existence of an intermediate group of drugs with moderate permeability. Advanced computational analysis employed in the present study enabled the recognition of complex relationships and patterns within physicochemical and biopharmaceutical properties associated with drug bioperformance.

Integrating theoretical and experimental permeability estimations for provisional biopharmaceutical classification: Application to the WHO essential medicines

The accuracy of the provisional estimation of the Biopharmaceutics Classification System (BCS) is heavily influenced by the permeability measurement. In this study, several theoretical and experimental models currently employed for BCS permeability classification have been analysed. The experimental models included the in situ rat intestinal perfusion, the ex vivo rat intestinal tissue in an Ussing chamber, the MDCK and Caco-2 cell monolayers, and the parallel artificial membrane (PAMPA). The theoretical models included the octanol-water partition coefficient and the QSPeR (Quantitative Structure-Permeability Relationship) model recently developed. For model validation, a dataset of 43 compounds has been recompiled and analysed for the suitability for BCS permeability classification in comparison with the use of human intestinal absorption and oral bioavailability values. The application of the final model, based on a majority voting system showed a 95.3% accuracy for predicting human permeability. Finally, the present approach was applied to the 186 orally administered drugs in immediate-release dosage forms of the WHO Model List of Essential Medicines. The percentages of the drugs that were provisionally classified as BCS Class I and Class III was 62.4%, suggesting that in vivo bioequivalence (BE) may potentially be assured with a less expensive and more easily implemented in vitro dissolution test, ensuring the efficiency and quality of pharmaceutical products. The results of the current study improve the accuracy of provisional BCS classification by combining different permeability models.

Solubility Determination of Active Pharmaceutical Ingredients Which Have Been Recently Added to the List of Essential Medicines in the Context of the Biopharmaceutics Classification System-Biowaiver

Since the publication of Lindenberg et al., which classified orally administered active pharmaceutical ingredients (APIs) on the 2004 Essential Medicines List (EML) of the World Health Organization according to the Biopharmaceutics Classification System (BCS), various APIs have been added to the EML. In this work, BCS classifications for 16 of the orally administered APIs which were added to the EML after 2004 were determined. To establish a reliable solubility classification for all these compounds, a miniaturized shake-flask method was introduced. This method enables a fast, economical determination of the BCS solubility class while reliably discriminating between "highly soluble" and "not highly soluble" compounds. Nine of the 16 APIs investigated were classified as "highly soluble" compounds, making them potential candidates for an approval of multisource drug products via the BCS-based biowaiver procedure. The choice of dose definition (which currently varies among the guidances pertaining to BCS-based bioequivalence published by various regulatory authorities) had no effect on the solubility classification of any of the 16 substances evaluated. BCS classification of the compounds was then completed using permeability data obtained from the literature. As several APIs decomposed at one or more pH values, a decision tree for determining their solubility was established.