Dissolution Challenges Associated with the Surface pH of Drug Particles: Integration into Mechanistic Oral Absorption Modeling

Parameterization of Physiologically Based Biopharmaceutics Models: Workshop Summary Report

This Article shares the proceedings from the August 29th, 2023 (day 1) workshop "Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives". The focus of the day was on model parametrization; regulatory authorities from Canada, the USA, Sweden, Belgium, and Norway presented their views on PBBM case studies submitted by industry members of the IQ consortium. The presentations shared key questions raised by regulators during the mock exercise, regarding the PBBM input parameters and their justification. These presentations also shed light on the regulatory assessment processes, content, and format requirements for future PBBM regulatory submissions. In addition, the day 1 breakout presentations and discussions gave the opportunity to share best practices around key questions faced by scientists when parametrizing PBBMs. Key questions included measurement and integration of drug substance solubility for crystalline vs amorphous drugs; impact of excipients on apparent drug solubility/supersaturation; modeling of acid-base reactions at the surface of the dissolving drug; choice of dissolution methods according to the formulation and drug properties with a view to predict the in vivo performance; mechanistic modeling of in vitro product dissolution data to predict in vivo dissolution for various patient populations/species; best practices for characterization of drug precipitation from simple or complex formulations and integration of the data in PBBM; incorporation of drug permeability into PBBM for various routes of uptake and prediction of permeability along the GI tract.

Bioequivalence risk assessment of oral formulations containing racemic ibuprofen through a chiral physiologically based pharmacokinetic model of ibuprofen enantiomers

The characterization of the time course of ibuprofen enantiomers can be useful in the selection of the most sensitive analyte in bioequivalence studies. Physiologically based pharmacokinetic (PBPK) modelling and simulation represents the most efficient methodology to virtually assess bioequivalence outcomes. In this work, we aim to develop and verify a PBPK model for ibuprofen enantiomers administered as a racemic mixture with different immediate release dosage forms to anticipate bioequivalence outcomes based on different particle size distributions. A PBPK model incorporating stereoselectivity and non-linearity in plasma protein binding and metabolism as well as R-to-S unidirectional inversion has been developed in Simcyp®. A dataset composed of 11 Phase I clinical trials with 54 scenarios (27 per enantiomer) and 14,452 observations (7129 for R-ibuprofen and 7323 for S-ibuprofen) was used. Prediction errors for AUC0-t and Cmax for both enantiomers fell within the 0.8-1.25 range in 50/54 (93 %) and 42/54 (78 %) of scenarios, respectively. Outstanding model performance, with 10/10 (100 %) of Cmax and 9/10 (90 %) of AUC0-t within the 0.9-1.1 range, was demonstrated for oral suspensions, which strongly supported its use for bioequivalence risk assessment. The deterministic bioequivalence risk assessment has revealed R-ibuprofen as the most sensitive analyte to detect differences in particle size distribution for oral suspensions containing 400 mg of racemic ibuprofen, suggesting that achiral bioanalytical methods would increase type II error and declare non-bioequivalence for formulations that are bioequivalent for the eutomer.

Solubility vs Dissolution in Physiological Bicarbonate Buffer

BACKGROUND

Phosphate buffer is often used as a replacement for the physiological bicarbonate buffer in pharmaceutical dissolution testing, although there are some discrepancies in their properties making it complicated to extrapolate dissolution results in phosphate to the in vivo situation. This study aims to characterize these discrepancies regarding solubility and dissolution behavior of ionizable compounds.

METHODS

The dissolution of an ibuprofen powder with a known particle size distribution was simulated in silico and verified experimentally in vitro at two different doses and in two different buffers (5 mM pH 6.8 bicarbonate and phosphate).

RESULTS

The results showed that there is a solubility vs. dissolution mismatch in the two buffers. This was accurately predicted by the in-house simulations based on the reversible non-equilibrium (RNE) and the Mooney models.

CONCLUSIONS

The results can be explained by the existence of a relatively large gap between the initial surface pH of the drug and the bulk pH at saturation in bicarbonate but not in phosphate, which is caused by not all the interfacial reactions reaching equilibrium in bicarbonate prior to bulk saturation. This means that slurry pH measurements, while providing surface pH estimates for buffers like phosphate, are poor indicators of surface pH in the intestinal bicarbonate buffer. In addition, it showcases the importance of accounting for the H2CO3-CO2 interconversion kinetics to achieve good predictions of intestinal drug dissolution.

Does Media Choice Matter When Evaluating the Performance of Hydroxypropyl Methylcellulose Acetate Succinate-Based Amorphous Solid Dispersions?

Hydroxypropyl methylcellulose acetate succinate (HPMCAS) is a weakly acidic polymer that is widely used in the formulation of amorphous solid dispersions (ASDs). While the pH-dependent solubility of HPMCAS is widely recognized, the role of other solution properties, including buffer capacity, is less well understood in the context of ASD dissolution. The goal of this study was to elucidate the rate-limiting steps for drug and HPMCAS release from ASDs formulated with two poorly water soluble model drugs, indomethacin and indomethacin methyl ester. The surface area normalized release rate of the drug and/or polymer in a variety of media was determined. The HPMCAS gel layer apparent pH was determined by incorporating pH sensitive dyes into the polymer matrix. Water uptake extent and rate into the ASDs were measured gravimetrically. For neat HPMCAS, the rate-limiting step for polymer dissolution was observed to be the polymer solubility at the polymer-solution interface. This, in turn, was impacted by the gel layer pH which was found to be substantially lower than the bulk solution pH, varying with medium buffer capacity. For the ASDs, the HPMCAS release rate was found to control the drug release rate. However, both drugs reduced the polymer release rate with indomethacin methyl ester having a larger impact. In low buffer capacity media, the presence of the drug had less impact on release rates when compared to observations in higher strength buffers, suggesting changes in the rate-limiting steps for HPMCAS dissolution. The observations made in this study can contribute to the fundamental understanding of acidic polymer dissolution in the presence and absence of a molecularly dispersed lipophilic drug and will help aid in the design of more in vivo relevant release testing experiments.

Harmonizing Biopredictive Methodologies Through the Product Quality Research Institute (PQRI) Part I: Biopredictive Dissolution of Ibuprofen and Dipyridamole Tablets

Assessing in vivo performance to inform formulation selection and development decisions is an important aspect of drug development. Biopredictive dissolution methodologies for oral dosage forms have been developed to understand in vivo performance, assist in formulation development/optimization, and forecast the outcome of bioequivalence studies by combining them with simulation tools to predict plasma profiles in humans. However, unlike compendial dissolution methodologies, the various biopredictive methodologies have not yet been harmonized or standardized. This manuscript presents the initial phases of an effort to develop best practices and move toward standardization of the biopredictive methodologies through the Product Quality Research Institute (PQRI, https://pqri.org ) entitled "The standardization of in vitro predictive dissolution methodologies and in silico bioequivalence study Working Group." This Working Group (WG) is comprised of participants from 10 pharmaceutical companies and academic institutes. The project will be accomplished in a total of five phases including assessing the performance of dissolution protocols designed by the individual WG members, and then building "best practice" protocols based on the initial dissolution profiles. After refining the "best practice" protocols to produce equivalent dissolution profiles, those will be combined with physiologically based biopharmaceutics models (PBBM) to predict plasma profiles. In this manuscript, the first two of the five phases are reported, namely generating biopredictive dissolution profiles for ibuprofen and dipyridamole and using those dissolution profiles with PBBM to match the clinical plasma profiles. Key experimental parameters are identified, and this knowledge will be applied to build the "best practice" protocol in the next phase.

Acalabrutinib Maleate Tablets: The Physiologically Based Biopharmaceutics Model behind the Drug Product Dissolution Specification

Acalabrutinib maleate tablets correspond to an improved formulation compared to acalabrutinib capsules as they can be dosed with and without acid reducing agents and therefore benefit more cancer patients. The dissolution specification for the drug product was determined using all the information available on the drug safety, efficacy, and in vitro performance. In addition, a physiologically based biopharmaceutics model was developed for acalabrutinib maleate tablets on the back of a previously published model for acalabrutinib capsules to establish that the proposed drug product dissolution specification would ensure safe and effective products for all patients including those under acid reducing agent treatment. The model was built, validated, and used to predict the exposure of virtual batches where the dissolution was slower than that of the clinical target. A combination of exposure prediction and the use of a PK-PD model allowed it to be demonstrated that the proposed drug product dissolution specification was acceptable. This combination of models enabled a larger safe space than would have been granted by consideration of bioequivalence only.

Best Practices for Integration of Dissolution Data into Physiologically Based Biopharmaceutics Models (PBBM): A Biopharmaceutics Modeling Scientist Perspective

Dissolution is considered as a critical input into physiologically based biopharmaceutics models (PBBM) as it governs in vivo exposure. Despite many workshops, initiatives by academia, industry, and regulatory, wider practices are followed for dissolution data input into PBBM models. Due to variety of options available for dissolution data input into PBBM models, it is important to understand pros, cons, and best practices while using specific dissolution model. This present article attempts to summarize current understanding of various dissolution models and data inputs in PBBM software's and aims to discuss practical challenges and ways to overcome such scenarios. Different approaches to incorporate dissolution data for immediate, modified, and delayed release formulations are discussed in detail. Common challenges faced during fitting of z-factor are discussed along with novel approach of dissolution data incorporation using P-PSD model. Ways to incorporate dissolution data for MR formulations using Weibull and IVIVR approaches were portrayed with examples. Strategies to incorporate dissolution data for DR formulations was depicted along with practical aspects. Approaches to generate virtual dissolution profiles, using Weibull function, DDDPlus, and time scaling for defining dissolution safe space, and strategies to generate virtual dissolution profiles for justifying single and multiple dissolution specifications were discussed. Finally, novel ways to integrate dissolution data for complex products such as liposomes, data from complex dissolution systems, importance of precipitation, and bio-predictive ability of QC media for evaluation of CBA's impact were discussed. Overall, this article aims to provide an easy guide for biopharmaceutics modeling scientist to integrate dissolution data effectively into PBBM models.

Use of Gastrointestinal Simulator, Mass Transport Analysis, and Absorption Simulation to Investigate the Impact of pH Modifiers in Mitigating Weakly Basic Drugs' Performance Issues Related to Gastric pH: Palbociclib Case Study

It is well known that reduced gastric acidity, for example with concomitant administration of acid reducing agents, can result in variable pharmacokinetics and decreased absorption of weakly basic drugs. It is important to identify the risk of reduced and variable absorption early in development, so that product design options to address the risk can be considered. This article describes the utilization of in vitro and in silico tools to predict the effect of gastric pH, as well as the impact of adding pH modifiers, in mitigating the effect of acid reducing agents on weak base drugs' dissolution and absorption. Palbociclib, a weakly basic drug, was evaluated in low and high gastric pH conditions in a multicompartmental dissolution apparatus referred to as a gastrointestinal simulator (GIS). The GIS permits the testing of pharmaceutical products in a way that better assesses dissolution under physiologically relevant conditions of pH, buffer concentration, formulation additives, and physiological variations including GI pH, buffer concentrations, secretions, stomach emptying rate, residence time in the GI, and aqueous luminal volume. To predict drug dissolution in the GIS, a hierarchical mass transport model was used and validated using in vitro experimental data. Dissolution results were then compared to observed human clinical plasma data with and without proton pump inhibitors using a GastroPlus absorption model to predict palbociclib plasma profiles and pharmacokinetic parameters. The results showed that the in silico model successfully predicted palbociclib dissolution in the GIS under low and high gastric pH conditions with and without pH modifiers. Furthermore, the GIS data coupled with the in silico tools anticipated (1) the reduced palbociclib exposure due to proton pump inhibitor coadministration and (2) the mitigating effect of a pH-modifying agent. This study provides tools to help in the development of orally administered formulations to overcome the effect of elevated gastric pH, especially when formulating with pH modifiers.

A Simple One-Parameter Percent Dissolved Versus Time Dissolution Equation that Accommodates Sink and Non-sink Conditions via Drug Solubility and Dissolution Volume

In vitro dissolution generally involves sink conditions, so dissolution equations generally do not need to accommodate non-sink conditions. Greater use of biorelevant media, which are typically less able to provide sink conditions than pharmaceutical surfactants, necessitates equations that accommodate non-sink conditions. One objective was to derive an integrated, one-parameter dissolution equation for percent dissolved versus time that accommodates non-sink effects via drug solubility and dissolution volume parameters, including incomplete solubility. A second objective was to characterize the novel equation by fitting it to biorelevant dissolution profiles of tablets of two poorly water-soluble drugs, as well as by conducting simulations of the effect of dose on dissolution profile. The Polli dissolution equation was derived, [Formula: see text], where M₀ is the drug dose (mg), c_s is drug solubility (mg/ml), V is dissolution volume (ml), and k_d is dissolution rate coefficient (ml/mg per min). Maximum allowable percent dissolved was determined by drug solubility and not a fitted extent of dissolution parameter. The equation fit tablet profiles in the presence and absence of sink conditions, using a single fitted parameter, k_d, and where solubility ranged over a 1000-fold range. k_d was generally smaller when c_s was larger. FeSSGF provided relatively small k_d values, reflecting FeSSGF colloids are large and slowly diffusing. Simulations showed impact of non-sink conditions, as well as plausible k_d values for various c_s scenarios, in agreement with observed k_d values. The equation has advantages over first-order and z-factor dissolution rate equations. An Excel file for regression is provided.

Improved dissolution of an enteric polymer and its amorphous solid dispersions by polymer salt formation

Weakly acidic polymers, historically used as enteric coatings, are increasingly being employed in solubility-enhancing amorphous solid dispersion (ASD) formulations. However, there is a lack of fundamental understanding around how these carboxylic acid-containing polymers dissolve, in particular when molecularly mixed with a lipophilic drug, as in an ASD. Identification of critical factors dominating their dissolution is vital for rational design of new polymers with enhanced release properties to address contemporary ASD delivery challenges, notably achieving good release at higher drug loadings. Herein, after identification of polymer solubilization via ionization as the rate limiting step for dissolution, hydroxypropylmethyl cellulose phthalate (HP-50) was converted to a salt by neutralization of the phthalic acid groups with different bases. Surface normalized dissolution was performed to assess the dissolution rate improvement achieved by polymer pre-ionization via salt formation. Polymer salts showed ∼ 3-fold faster release than HP-50 at pH 6.8 (50 mM sodium phosphate buffer). Importantly, a polymer salt was able to maintain a rapid dissolution rate, irrespective of the buffer capacity of the medium, whereas the protonated polymer showed greatly diminished dissolution as medium buffer capacity decreased toward physiological gastrointestinal tract values. HP-50 and two polymer salts were formulated into ASDs with miconazole, a lipophilic and weakly basic antifungal drug, at a 20% drug loading. Rapid drug release rates were achieved with polymer salt ASDs, whereby drug release was 14 times faster than from the protonated HP-50 ASD. This study highlights the critical role of polymer ionization and buffer capacity in the dissolution of HP-50-based systems and how pre-ionization via polymer salt formation is a successful strategy for the design of new polymers for improved ASD performance.