An Investigation into the Influence of Process Parameters and Formulation Variables on Compaction Properties of Liquisolid Systems.

Liquisolid technology, as a promising approach for bioavailability enhancement, has received increasing attention in recent years. However, literature reports addressing the challenges for its industrial application, particularly those related to compaction behavior of liquisolid systems, are scarce. The aim of this study was to investigate the influence of process parameters and formulation variables on the flowability, wetting, and compaction properties of the liquisolid systems prepared in a fluid bed processor. The experiments with microcrystalline cellulose, as a carrier, were performed according to 23 full factorial design. The effects of liquid content, spray air pressure, and liquid feed rate on the properties of liquisolid systems were investigated. Liquisolid admixtures with microcrystalline cellulose were compared with those prepared with novel carriers, Fujicalin® and Neusilin® US2. "Out-die" Heckel, modified Walker, and Kuentz-Leuenberger models were used to analyze the compressibility of liquisolid admixtures. The results obtained showed that an increase in liquid content (in the range of 10 to 15%) led to a decrease in flowability of liquisolid admixtures with microcrystalline cellulose, as well as more pronounced influence of spraying conditions. On the other hand, higher liquid content led to higher compressibility. Fujicalin® and Neusilin® US2 liquisolid admixtures were found to have superior flowability and compressibility in comparison with those with microcrystalline cellulose, despite the considerably higher liquid load (50-55% liquid content in Neusilin® US2 compacts). Acceptable compactibility of the investigated liquisolid systems was observed. The fluid bed processor was shown to be suitable equipment for production of liquisolid systems, but with careful adjustment of process parameters.

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 (Peff ). The Peff 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 Peff over D/S. Two Peff 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.

Assessing the risk of alcohol-induced dose dumping from sustained-release oral dosage forms: in vitro-in silico approach.

Consumption of alcoholic beverages with sustained-release oral dosage forms may pose a risk to patients due to potential alcohol-induced dose dumping (ADD). Regulatory guidances recommend in vitro dissolution testing to identify the risk of ADD, but the question remains whether currently proposed test conditions can be considered biopredictive. The purpose of this study was to evaluate different dissolution setups to assess ADD, and the potential of combined in vitro-in silico approach to predict drug absorption after concomitant alcohol intake for hydrophilic and lipophilic sustained-release tablets containing ibuprofen or diclofenac sodium. According to the obtained results, the impact of ethanol was predominantly governed by the influence on matrix integrity, with the increase in drug solubility being less significant. Hydrophilic matrix tablets were less susceptible to ADD than lipophilic matrices, although the conclusion on formulation ethanol-vulnerability depended on the employed experimental conditions. In silico predictions indicated that the observed changes in drug dissolution would not result in plasma concentrations beyond therapeutic window, but sustained-release characteristics of the formulations might be lost. Overall, the study demonstrated that in vitro-in silico approach may provide insight into the effect of ADD on drug clinical performance, and serve as a tool for ADD risk assessment.

In vitro and in vivo investigation of taste-masking effectiveness of Eudragit E PO as drug particle coating agent in orally disintegrating tablets.

CONTEXT: Considering that bitter taste of drugs incorporated in orally disintegrating tablets (ODTs) can be the main reason for avoiding drug therapy, it is of the utmost importance to achieve successful taste-masking. The evaluation of taste-masking effectiveness is still a major challenge. OBJECTIVE: The objective of this study was to mask bitter taste of the selected model drugs by drug particle coating with Eudragit® E PO, as well as to evaluate taste-masking effectiveness of prepared ODTs using compendial dissolution testing, dissolution in the small-volume shake-flask assembly and trained human taste panel. MATERIALS AND METHODS: Model drugs were coated in fluidized bed. Disintequik™ ODT was used as a novel co-processed excipient for ODT preparation. Selected formulations were investigated in vitro and in vivo using techniques for taste-masking assessment. RESULTS AND DISCUSSION: Significantly slower drug dissolution was observed from tablets with coated drug particles during the first 3 min of investigation. Results of in vivo taste-masking assessment demonstrated significant improvement in drug bitterness suppression in formulations with coated drug. Strong correlation between the results of drug dissolution in the small-volume shake-flask assembly and in vivo evaluation data was established (R ≥ 0.970). CONCLUSION: Drug particle coating with Eudragit® E PO can be a suitable approach for bitter taste-masking. Strong correlation between in vivo and in vitro results implicate that small-volume dissolution method may be used as surrogate for human panel taste-masking assessment, in the case of physical taste-masking approach application.

Melt granulation in fluidized bed: a comparative study of spray-on versus in situ procedure.

OBJECTIVE: The aim of this study was to investigate the influence of process parameters, binder content and binder addition method on characteristics of the granules obtained by melt granulation (MG) in fluidized bed. METHODS: Spray-on experiments were performed according to 2(3) full factorial design. The effect of binder content, molten binder feed rate, and spray air pressure on granule size and size distribution, granule shape, flowability and drug release rate was investigated. In the in situ experiments, the influence of binder particle size and binder content was evaluated. Solid-state characterization was performed by means of differential scanning calorimetry, X-ray powder diffraction and Fourier transform infrared spectroscopy. RESULTS: Size of the granules obtained by spray-on procedure was significantly influenced by binder content and spray air pressure, while the width of particle size distribution was mainly affected by binder feed rate. Spray air pressure showed the most significant influence on granule shape. It was shown that smooth and spherical particles with good flow properties may be obtained by both procedures, spray-on and in situ MG. The results obtained indicated the influence of agglomeration mechanism on granule sphericity, with higher degree of granule sphericity observed when immersion and layering was the dominant mechanism. Paracetamol release from granulates was very rapid, but after compression of the granules into tablets, drug release was considerably slower. Solid-state analysis confirmed that the physical form of the granulate components remained unaffected after the MG process. CONCLUSION: The results presented indicate that MG in fluidized bed could be a good alternative to conventional granulation techniques.

A case study of in silico modelling of ciprofloxacin hydrochloride/metallic compound interactions.

With the development of physiologically based absorption models, there is an increased scientific and regulatory interest in in silico modelling and simulation of drug-drug and drug-food interactions. Clinically significant interactions between ciprofloxacin and metallic compounds are widely documented. In the current study, a previously developed ciprofloxacin-specific in silico absorption model was employed in order to simulate ciprofloxacin/metallic compound interaction observed in vivo. Commercially available software GastroPlus™ (Simulations Plus Inc., USA) based on the ACAT model was used for gastrointestinal (GI) simulations. The required input parameters, relating to ciprofloxacin hydrochloride physicochemical and pharmacokinetic characteristics, were experimentally determined, taken from the literature or estimated by GastroPlus™. Parameter sensitivity analysis (PSA) was used to assess the importance of selected input parameters (solubility, permeability, stomach and small intestine transit time) in predicting percent drug absorbed. PSA identified solubility and permeability as critical parameters affecting the rate and extent of ciprofloxacin absorption. Using the selected input parameters, it was possible to generate a ciprofloxacin absorption model, without/with metal cation containing preparations co-administration, which matched well the in vivo data available. It was found that reduced ciprofloxacin absorption in the presence of aluminium hydroxide, calcium carbonate or multivitamins/zinc was accounted for by reduced drug solubility. The impact of solubility-permeability interplay on ciprofloxacin absorption can be observed in the ciprofloxacin-aluminium interaction, while in ciprofloxacin-calcium and ciprofloxacin-zinc interactions, effect of solubility was more pronounced. The results obtained indicate that in silico model developed can be successfully used to complement relevant in vitro studies in the simulation of physicochemical ciprofloxacin/metallic compound interactions.

A comprehensive assessment of machine learning algorithms for enhanced characterization and prediction in orodispersible film development.

Orodispersible films (ODFs) have emerged as innovative pharmaceutical dosage forms, offering patient-specific treatment through adjustable dosing and the combination of diverse active ingredients. This expanding field generates vast datasets, requiring advanced analytical techniques for deeper understanding of data itself. Machine learning is becoming an important tool in the rapidly changing field of pharmaceutical research, particularly in drug preformulation studies. This work aims to explore into the application of machine learning methods for the analysis of experimental data obtained by ODF characterization in order to obtain an insight into the factors governing ODF performance and use it as guidance in pharmaceutical development. Using a dataset derived from extensive experimental studies, various machine learning algorithms were employed to cluster and predict critical properties of ODFs. Our results demonstrate that machine learning models, including Support vector machine, Random forest and Deep learning, exhibit high accuracy in predicting the mechanical properties of ODFs, such as flexibility and rigidity. The predictive models offered insights into the complex interaction of formulation variables. This research is a pilot study that highlights the potential of machine learning as a transformative approach in the pharmaceutical field, paving the way for more efficient and informed drug development processes.

Application of Machine-Learning Algorithms for Better Understanding the Properties of Liquisolid Systems Prepared with Three Mesoporous Silica Based Carriers.

The processing of liquisolid systems (LSS), which are considered a promising approach to improving the oral bioavailability of poorly soluble drugs, has proven challenging due to the relatively high amount of liquid phase incorporated within them. The objective of this study was to apply machine-learning tools to better understand the effects of formulation factors and/or tableting process parameters on the flowability and compaction properties of LSS with silica-based mesoporous excipients as carriers. In addition, the results of the flowability testing and dynamic compaction analysis of liquisolid admixtures were used to build data sets and develop predictive multivariate models. In the regression analysis, six different algorithms were used to model the relationship between tensile strength (TS), the target variable, and eight other input variables. The AdaBoost algorithm provided the best-fit model for predicting TS (coefficient of determination = 0.94), with ejection stress (ES), compaction pressure, and carrier type being the parameters that influenced its performance the most. The same algorithm was best for classification (precision = 0.90), depending on the type of carrier used, with detachment stress, ES, and TS as variables affecting the performance of the model. Furthermore, the formulations with Neusilin® US2 were able to maintain good flowability and satisfactory values of TS despite having a higher liquid load compared to the other two carriers.

A case study on the in silico absorption simulations of levothyroxine sodium immediate-release tablets.

The aim of this case study was to develop a drug-specific absorption model for levothyroxine (LT4) using mechanistic gastrointestinal simulation technology (GIST) implemented in the GastroPlus™ software package. The required input parameters were determined experimentally, in silico predicted and/or taken from the literature. The simulated plasma profile was similar and in a good agreement with the data observed in the in vivo bioequivalence study, indicating that the GIST model gave an accurate prediction of LT4 oral absorption. Additionally, plasma concentration-time profiles were simulated based on a set of experimental and virtual in vitro dissolution data in order to estimate the influence of different in vitro drug dissolution kinetics on the simulated plasma profiles and to identify biorelevant dissolution specification for LT4 immediate-release (IR) tablets. A set of experimental and virtual in vitro data was also used for correlation purposes. In vitro-in vivo correlation model based on the convolution approach was applied in order to assess the relationship between the in vitro and in vivo data. The obtained results suggest that dissolution specification of more than 85% LT4 dissolved in 60 min might be considered as biorelevant dissolution specification criteria for LT4 IR tablets.

Processability evaluation of multiparticulate units prepared by selective laser sintering using the SeDeM Expert System approach.

3D printing in dosage forms fabrication is in the focus of researchers, however, the attempts in multiparticulate units (MPUs) preparation are scarce. The aim of this study was to fabricate different size MPUs by selective laser sintering (SLS), using different polymers, and investigate their processability based on the SeDeM Expert System approach. MPUs (1- or 2-mm size) were prepared with model drug (ibuprofen or caffeine), polymer (poly(ethylene)oxide (PEO), ethyl cellulose (EC) or methacrylic acid-ethyl acrylate copolymer (MA-EA)) and printing aid. Comprehensive sample characterization was performed and experimentally obtained parameters were mathematically transformed and evaluated using the SeDeM Expert System framework. The obtained samples exhibited irregular shape, despite the spherical printing object design. Polymer incorporated notably affected MPUs properties. The obtained samples exhibited low bulk density, good flowability-, as well as stability-related parameters, which indicated their suitability for filling into capsules or sachets. Low density values implied that compressibility enhancing excipients may be required for MPUs incorporation in tablets. Samples containing EC and MA-EA were found suitable for compression, due to high compacts tensile strength. The obtained results indicate that SeDeM Expert System may extended from powder compressibility evaluation tool to framework facilitating powders/multiparticulate units processing.

In vitro-in vivo correlation for gliclazide immediate-release tablets based on mechanistic absorption simulation.

The aim of this study was to develop a drug-specific absorption model for gliclazide (GLK) using mechanistic gastrointestinal simulation technology (GIST) implemented in GastroPlus(TM) software package. A range of experimentally determined, in silico predicted or literature data were used as input parameters. Experimentally determined pH-solubility profile was used for all simulations. The human jejunum effective permeability (P (eff)) value was estimated on the basis of in vitro measured Caco-2 permeability (literature data). The required PK inputs were taken from the literature. The results of the simulations were compared with actual clinical data and revealed that the GIST-model gave accurate prediction of gliclazide oral absorption. The generated absorption model provided the target in vivo dissolution profile for in vitro-in vivo correlation and identification of biorelevant dissolution specification for GLK immediate-release (IR) tablets. A set of virtual in vitro data was used for correlation purposes. The obtained results suggest that dissolution specification of more than 85% GLK dissolved in 60 min may be considered as "biorelevant" dissolution acceptance criteria for GLK IR tablets.

An investigation into the influence of experimental conditions on in vitro drug release from immediate-release tablets of levothyroxine sodium and its relation to oral bioavailability.

The aim of this study was to investigate the influence of experimental conditions on levothyroxine sodium release from two immediate-release tablet formulations which narrowly passed the standard requirements for bioequivalence studies. The in vivo study was conducted as randomised, single-dose, two-way cross-over pharmacokinetic study in 24 healthy subjects. The in vitro study was performed using various dissolution media, and obtained dissolution profiles were compared using the similarity factor value. Drug solubility in different media was also determined. The in vivo results showed narrowly passing bioequivalence. Considering that levothyroxine sodium is classified as Class III drug according to the Biopharmaceutics Classification System, drug bioavailability will be less sensitive to the variation in its dissolution characteristics and it can be assumed that the differences observed in vitro in some of investigated media probably do not have significant influence on the absorption process, as long as rapid and complete dissolution exists. The study results indicate that the current regulatory criteria for the value of similarity factor in comparative dissolution testing, as well as request for very rapid dissolution (more than 85% of drug dissolved in 15 min), are very restricted for immediate-release dosage forms containing highly soluble drug substance and need further investigation. The obtained results also add to the existing debate on the appropriateness of the current bioequivalence standards for levothyroxine sodium products.

Investigation into liquisolid system processability based on the SeDeM Expert System approach.

Liquisolid systems are emerging formulation approach for poorly soluble drugs, based on adsorption/absorption of drug dispersion and obtaining free-flowing powder with good compressibility. SeDeM Expert System represents a powder processability evaluation method. It may provide additional insight into liquisolid systems critical quality attributes, but the contribution of this approach remains to be explored. The aims of this study were: pellet preparation by combination of liquisolid technology and water granulation/extrusion, evaluation of liquisolid based systems (pellets/admixtures) and investigation into the applicability of SeDeM Expert System in liquisolid systems characterization. Pellets/admixtures were prepared with microcrystalline cellulose as carrier and crospovidone/silicon dioxide as coating agent. Ibuprofen solution in polyethylene glycol 400 was used as liquid phase. After comprehensive sample characterization, experimentally obtained parameters were mathematically transformed and evaluated in the SeDeM Expert System framework. Pellets exhibited low aspect ratio and excellent flowability, despite liquid load up to 52.2%. The investigated liquisolid admixtures exhibited good flowability and faster drug dissolution than pellets. Single pellet crushing test results exhibited strong correlation with compact indentation hardness and may be used as indentation hardness predictor. SeDeM Expert System provides useful insight into liquisolid system processability and comparative evaluation and it may facilitate final solid dosage form development.

An Investigation into Mechanical Properties and Printability of Potential Substrates for Inkjet Printing of Orodispersible Films.

Inkjet printing is novel approach in drug manufacturing that enables dispensing precise volumes of ink onto substrates. Optimal substrate properties including suitable mechanical characteristic are recognized as crucial to achieve desired dosage form performance upon administration. Identification of relevant quality attributes and their quantification is subject of intensive scientific research. The aim of this work was to explore applicability of different materials as printing substrates and explore contribution of the investigated substrate properties to its printability. Substrates were characterized with regards to uniformity, porosity, disintegration time, mechanical properties and drug dissolution. Experimentally obtained values were mathematically transformed and the obtained results were presented as relevant radar charts. It was shown that structurally different substrates may be employed for orodispersible films inkjet printing. Main disadvantage of single-polymer films was low drug load, and their printability was dependent on film flexibility and mechanical strength. Structured orodispersible film templates exhibited favorable mechanical properties and drug load capacity. Wafer edible sheets were characterized with high mechanical resistance and brittleness which somewhat diminished printability, but did not hinder high drug load. Obtained results provide insight into application of different materials as printing substrates and contribute to understanding of substrate properties which can affect printability.

Tableting of hot-melt coated paracetamol granules: Material tableting properties and quality characteristics of the obtained tablets.

Hot-melt coating (HMC) has been recognized as a promising technique in the production of solid dosage forms e.g., HMC of granules can be applied prior to compression in order to obtain modified drug release or taste masking. However, tableting properties of HMC granules have not been studied yet. In this work, we explored the influence of the lipid coating on granules tableting properties, and assessed quality attributes of the obtained tablets. Paracetamol granules, previously coated with the lipid excipient Precirol® ATO 5 using a hot-melt coating technique in modified fluidized-bed system, were evaluated in terms of work of compression, elastic recovery, tablets tensile strength, detachment stress and ejection stress. Regarding the product quality, tablets content uniformity, friability, disintegration time and drug release properties were tested. Our results demonstrated that tablets made of coated granules exhibited more pronounced elastic behaviour, and increased tensile strength in comparison to tablets made of uncoated granules, suggesting that lipid coating promotes elastic deformation and forms lipid matrix within the tablets. Additionally, low detachment and ejection stresses for tablets made of HMC granules indicated no need to add lubricant prior to tableting process. Evaluation of tablets properties revealed that tablets friability was not influenced by the presence of lipid coating on the compressed granules. However, formation of lipid matrix within the tablets made of HMC granules resulted in prolonged tablet disintegration time, and sustained drug release. Moreover, the performance of lipid matrix tablets, in terms of drug dissolution rate, was relatively insensitive to compression pressure variations in 104-173 MPa range. The obtained results indicate that tableting of HMC granules is a promising technique to obtain sustained release lipid matrix tablets of suitable pharmaceutical-technical properties.

Mathematical modeling of pH-surfactant-mediated solubilization of nimesulide.

AIM: The equilibrium-based mathematical model was used to describe the pH-surfactant-mediated solubilization of weakly acidic electrolyte, nimesulide, in buffer solutions. This model assumed that the total drug solubility could be expressed as a sum of the solubilities of four different species: unionized and ionized form in solution and their corresponding micellar forms. Sucrose-laurate, new synthetic surfactant, and polysorbate 80 were investigated for their benefits in the testing of poorly soluble acidic model drug. METHOD: Two sets of solubility data, determined at pH values 4.5 and 9.0 in media containing different surfactant concentrations, were used to calculate solubilization slopes and corresponding micellar equilibrium constants for the unionized (Kn) and ionized (K(i)) drug. These values were used to estimate drug solubilization in media considered to represent physiologically relevant conditions. RESULTS: Predicted solubility values were in good agreement with the experimental data, suggesting that the impact of pH and surfactant on nimesulide solubility could be well characterized by the equilibrium model described in this article. CONCLUSIONS: Obtained results indicated that the extent of solubilization was significantly dependent on the surfactant used.

An Investigation into the Factors Governing Drug Absorption and Food Effect Prediction Based on Data Mining Methodology.

Drug absorption is a complex process governed by a number of interrelated physicochemical, biopharmaceutical, and pharmacokinetic factors. In order to explore complex relationships among these factors, multivariate exploratory analysis was performed on the dataset of drugs with diverse bioperformance. The investigated dataset included subset of drugs for which bioequivalence between solid dosage form and oral solution has been reported, and subset of drugs described in the literature as low solubility/low permeability compounds. Discriminatory power of hierarchical clustering on principal components was somewhat higher when applied on the data subsets of drugs with similar bioperformance, while analysis of the integrated dataset indicated existence of two groups of drugs with the boundaries reflected in Peff value of approximately 2 × 10-4 cm/s and Fa and Fm values higher than 85% and 50%, respectively. Majority of the investigated drugs within the integrated dataset were grouped within their initial subset indicating that overall drug bioperformance is closely related to its physicochemical, biopharmaceutical and pharmacokinetic properties. Classification models constructed using the random forest (RF) and support vector machine with polynomial kernel function were able to predict food effect based on drug dose/solubility ratio (D/S), effective permeability (Peff), percent of dose metabolized (Fm), and elimination half-life (τ1/2). Although both models performed well during training and testing, only RF kept satisfying performance when applied on the external dataset (kappa value > 0.4). The results obtained indicate that data mining can be employed as useful tool in biopharmaceutical drug characterization which merits further investigation.

Reinforcement of the Framework for Experiential Education in Healthcare in Serbia: Post-Implementation Project Review within Pharmacy Education.

Background: The Erasmus+ project "Reinforcement of the Framework for Experiential Education in Healthcare in Serbia" (ReFEEHS) has been undertaken with the aim to: (i) reinforce and modernize experiential education (ExEd) in the health sciences curricula, (ii) introduce interprofessional education (IPE), and (iii) promote teaching competency development of academic staff and teacher practitioners/clinician educators. The aim of this paper is a post-implementation review of the project activities and outcomes with the emphasis on the impact and sustainability in pharmacy education. Methods: Project Logical framework matrix has been employed as planning, monitoring and evaluation tool which summarizes the main project objectives, project outcomes, relevant activities, indicators of progress, sources of verification, assumptions and risks. Results: The key project outcomes are: (i) update of competency-based curricula and development of quality assurance framework for students professional practice placements; (ii) development and introduction of interprofessional teaching and learning activities through joint curriculum delivery; and (iii) development and implementation of Teaching Certificate in Health Professions Education (TCinHPE) study program. The short-term impact of project activities and outcomes has been assessed based on the feedback received from relevant stakeholders, as well as self-evaluation of participants enrolled in new/updated curricula. Sustainability of project results is necessary in order to achieve long-term impact envisioned as increased level of professional competency of health science students; increased level of teaching competency of academic staff and teacher practitioners; improved patient healthcare and harmonisation with the EU practice and policies. Conclusions: The project outcomes contributed to building capacity at the Serbian universities involved in terms of collaboration between the healthcare professions and, in curriculum and academic staff development. It is expected that improved curricula will positively impact professional competency development of pharmacy students, graduates employability and increased workforce mobility. Meeting the quality standards of the European Higher Education Area will contribute to visibility of Serbian universities and their internationalisation, which is one of the strategic aims of improvement.

Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach.

Multivariate data analysis (MVDA) and artificial neural networks (ANN) are supporting statistical methodologies required for successful development and manufacturing of drug products. To address this purpose, a complex dataset from 49 industrially produced capsules filled with pellets was first analyzed through the development of a multiple linear regression model focused on determining raw material attributes or process parameters with a significant impact on drug dissolution. Based on the model, the following molecular and micrometrics properties of κ-carrageenan have been identified as critical material attributes with the highest contribution to drug dissolution: molecular weight and polydispersity index, viscosity, content of potassium ions, wettability, particle size, and density. The process parameters identified to control the drug dissolution behavior of pellets were amount of granulation liquid, torque of dry blend, spheronization parameters, and yields after screening. To further scrutinize the dataset, an ANN model was subsequently built, incorporating 29 batches addressing drug particle size and process parameters such as torque during granulation and spheronization time as critical factors. Finally, this study demonstrates the ability of MVDA and ANN to allow prediction of the key performance drivers influencing the drug dissolution of industrially developed capsules filled with pellets and it highlights their complementary relationship.

Rationale for ibuprofen co-administration with antacids: potential interaction mechanisms affecting drug absorption.

Ibuprofen is a widely used NSAID which is often co-administered with antacids because of its gastro-irritant effects. Literature data suggest that antacid interactions may increase or decrease the drug's absorption rate and onset of action and that the interaction may be formulation specific. In the present study, literature data on ibuprofen absorption were evaluated in order to gain insight into the nature of the in vivo effect. Solubility determinations in reactive media containing magnesium or aluminium and dissolution studies in the presence of antacid suspension were performed in an attempt to simulate in vitro the effects observed in vivo. The results obtained indicate that magnesium hydroxide enhances ibuprofen solubility, dissolution and bioavailability, while aluminium hydroxide has a retarding effect. Solubility studies indicated formation of a soluble solid ibuprofen phase in the presence of Mg2+, in contrast, an insoluble ibuprofen salt was formed with Al3+. The introduction of magnesium based antacid suspension into the dissolution media resulted in a formulation specific increase in drug dissolution rate with the most pronounced effect observed for the slowest release tablet formulation. The results obtained indicate the potential for in vitro studies to predict physicochemical interactions that are likely to influence drug absorption rate in vivo.