Carbamazepine level-A in vivo-in vitro correlation (IVIVC): a scaled convolution based predictive approach

Quantitative Assessment of the in vivo Dissolution Rate to Establish a Modified IVIVC for Isosorbide Mononitrate Tablets

A modified in vitro-in vivo correlation (IVIVC) of the oral solid dosage forms has been proposed as a linear correlation between in vitro and in vivo dissolution. Nevertheless, the analysis of in vivo dissolution is limited by the lack of available methods. In this proof-of-concept study, a novel pharmacokinetic (PK) model containing the in vivo dissolution process and its quantification was presented to directly estimate the in vivo dissolution rate constant (k_d). The new model was validated with a hypothetical oral solution (k_d → +∞). The accuracy of the new method was clarified by comparing with the relatively true value of k_d from the literature. Isosorbide mononitrate (ISMN) was used as a model drug to explore the practicability of the novel method. The dissolution capacities of ISMN reference and test tablets were discriminated by an improved in vitro dissolution method. Following the human PK studies, the k_d values and corresponding in vivo dissolution profiles of two formulations were obtained using the novel method. Finally, a modified level A IVIVC between in vitro and in vivo dissolution of ISMN tablets was established, which is expected to guide the optimization of the tablet formulation containing ISMN.

Biowaiver Monograph for Immediate-Release Solid Oral Dosage Forms: Carbamazepine

Literature relevant to assessing whether BCS-based biowaivers can be applied to immediate release (IR) solid oral dosage forms containing carbamazepine as the single active pharmaceutical ingredient are reviewed. Carbamazepine, which is used for the prophylactic therapy of epilepsy, is a non-ionizable drug that cannot be considered "highly soluble" across the range of pH values usually encountered in the upper gastrointestinal tract. Furthermore, evidence in the open literature suggests that carbamazepine is a BCS Class 2 drug. Nevertheless, the oral absolute bioavailability of carbamazepine lies between 70 and 78% and both in vivo and in vitro data support the classification of carbamazepine as a highly permeable drug. Since the therapeutic and toxic plasma level ranges overlap, carbamazepine is considered to have a narrow therapeutic index. For these reasons, a BCS based biowaiver for IR tablets of carbamazepine cannot be recommended. Interestingly, in nine out of ten studies, USP dissolution conditions (900 mL water with 1% SLS, paddle, 75 rpm) appropriately discriminated among bioinequivalent products and this may be a way forward to predicting whether a given formulation will be bioequivalent to the comparator product.

Two-step in vitro-in vivo correlations: Deconvolution and convolution methods, which one gives the best predictability? Comparison with one-step approach

Finding predictive dissolution tests and valid IVIVCs are essential activities in generic industry, as they can be used as substitutes of human bioequivalence studies. IVIVCs can be developed by two different strategies: a one-step approach or a two-step approach. The objectives of this work were to compare different deconvolution and convolution methods used in the development of two-step level A IVIVCs and to study if the relationship between the in vitro dissolution rate and the in vivo dissolution rate should guide the decision between using a two-step approach or a one-step approach during the development of a new IVIVC. When the in vitro and the in vivo dissolution rates had a linear relationship, valid and biopredictive two-step IVIVCs were obtained, although there was not a combination of deconvolution and convolution methods that could be named as the best one, as long as all the prediction errors for any combination were within the limits. It was not possible to obtain a valid two-step IVIVC when the relationship between dissolution rates was non-linear, but the one-step approach was able to overcome this fact and it gave valid IVIVCs regardless of whether the relationship between dissolution rates was linear or non-linear.

In Vivo Predictive Dissolution (IPD) for Carbamazepine Formulations: Additional Evidence Regarding a Biopredictive Dissolution Medium

The aim of the present study was to bring additional evidence regarding a biopredictive dissolution medium containing 1% sodium lauryl sulphate (SLS) to predict the in vivo behavior of carbamazepine (CBZ) products. Twelve healthy volunteers took one immediate release (IR) dose of either test and reference formulations in a bioequivalence study (BE). Dissolution profiles were carried-out using the medium. Level A in vitro–in vivo correlations (IVIVC) were established using both one-step and two-step approaches as well as exploring the time-scaling approach to account for the differences in dissolution rate in vitro versus in vivo. A detailed step by step calculation was provided to clearly illustrate all the procedures. The results show additional evidence that the medium containing 1% SLS can be classified as a universal biopredictive dissolution tool, and that both of the approaches used to develop the IVIVC (one and two-steps) provide good in vivo predictability. Therefore, this biopredictive medium could be a highly relevant tool in Latin-American countries to ensure and check the quality of their CBZ marketed products for which BE studies were not requested by their regulatory health authorities.

Evaluation and optimized selection of supersaturating drug delivery systems of posaconazole (BCS class 2b) in the gastrointestinal simulator (GIS): An in vitro-in silico-in vivo approach

Supersaturating drug delivery systems (SDDS) have been put forward in the recent decades in order to circumvent the issue of low aqueous solubility. Prior to the start of clinical trials, these enabling formulations should be adequately explored in in vitro/in silico studies in order to understand their in vivo performance and to select the most appropriate and effective formulation in terms of oral bioavailability and therapeutic outcome. The purpose of this work was to evaluate the in vivo performance of four different oral formulations of posaconazole (categorized as a biopharmaceutics classification system (BCS) class 2b compound) based on the in vitro concentrations in the gastrointestinal simulator (GIS), coupled with an in silico pharmacokinetic model to predict their systemic profiles. Recently published intraluminal and systemic concentrations of posaconazole for these formulations served as a reference to validate the in vitro and in silico results. Additionally, the morphology of the formed precipitate of posaconazole was visualized and characterized by optical microscopy studies and thermal analysis. This multidisciplinary work demonstrates an in vitro-in silico-in vivo approach that provides a scientific basis for screening SDDS by a user-friendly formulation predictive dissolution (fPD) device in order to rank these formulations towards their in vivo performance.

Defining level A IVIVC dissolution specifications based on individual in vitro dissolution profiles of a controlled release formulation

Regulatory guidelines recommend that, when a level A IVIVC is established, dissolution specification should be established using averaged data and the maximum difference between AUC and C_max between the reference and test formulations cannot be greater than 20%. However, averaging data assumes a loss of information and may reflect a bias in the results. The objective of the current work is to present a new approach to establish dissolution specifications using a new methodology (individual approach) instead of average data (classical approach). Different scenarios were established based on the relationship between in vitro-in vivo dissolution rate coefficient using a level A IVIVC of a controlled release formulation. Then, in order to compare this new approach with the classical one, six additional batches were simulated. For each batch, 1000 simulations of a dissolution assay were run. C_max ratios between the reference formulation and each batch were calculated showing that the individual approach was more sensitive and able to detect differences between the reference and the batch formulation compared to the classical approach. Additionally, the new methodology displays wider dissolution specification limits than the classical approach, ensuring that any tablet from the new batch would generate in vivo profiles which its AUC or C_max ratio will be out of the 0.8-1.25 range, taking into account the in vitro and in vivo variability of the new batches developed.

An updated overview with simple and practical approach for developing in vitro-in vivo correlation

Preclinical Research & Development An in vitro-in vivo correlation (IVIVC) is as a predictive mathematical model that demonstrates a key role in the development, advancement, evaluation and optimization of extended release, modified release and immediate release pharmaceutical formulations. A validated IVIVC model can serve as a surrogate for bioequivalence studies and subsequently save time, effort and expenditure during pharmaceutical product development. This review discusses about different levels of correlations, general approaches to develop an IVIVC by mathematical modelling, validation, data analysis and various applications. In the current setting, the dearth of success associated with IVIVC is due to complexity of underlying scientific principles as well as the practice of fitting/matching in vivo plasma level-time data with in vitro dissolution profile. Hence, a simple, straightforward practical means to predict plasma drug levels by convolution technique and percentage drug absorbed computed from in vitro dissolution profile based on deconvolution method are illustrated. The bioavailability/bioequivalence assessment and evaluation are frequently validated by the pharmacokinetic parameters such as maximum concentration, time to reach maximum concentration, and area under the curve. The implementation of a quality by design manufacturing based on in vivo bioavailability and clinically relevant dissolution specification are recommended because corresponding design safe space will guarantee that all batches from relevant products are met with sufficient quality and bioperformance. Recently, United States Food and Drug Administration and European Medicines Agency have proposed that in silico/physiologically based pharmacokinetic modelling can be used in decision making during preclinical experiments as well as to recognize the dissolution profiles that can forecast and ensure the desired clinical performance.

A novel beads-based dissolution method for the in vitro evaluation of extended release HPMC matrix tablets and the correlation with the in vivo data

The aim of this work was to establish alternative in vitro dissolution method with good discrimination and in vivo predictability for the evaluation of HPMC extended release matrix tablets. For this purpose, two different HPMC matrix tablet formulations were first evaluated by a range of conventional dissolution testing methods using apparatus 1, apparatus 2, and apparatus 3 according to US Pharmacopoeia. Obtained results showed low discrimination between the tested samples. Afterward, a novel dissolution testing method which combines plastic beads and apparatus 3 was developed with the aim to better mimic the mechanical forces that occur in vivo. Results showed that sufficiently large mechanical stress with high dips per minute program setting (apparatus 3) was needed to obtain in vitro discriminative results, which are in accordance with the in vivo data. The in vivo relevance of the method was confirmed with the establishment of the level A in vitro-in vivo correlation.

Discriminatory dissolution method for quality control measurements of carbamazepine immediate release tablets based on in vitro--in vivo investigations

The purpose of this study was to identify a discriminatory dissolution method able to predict the in vivo performance of tablet formulations designed for carbamazepine (CBZ). After evaluation of dissolution medium and rotation speed using a 2⁵ central composite design and investigation of the in vivo release behaviors in beagle dogs, the dissolution method of CBZ 100 mg tablets was validated using a USP apparatus II, at a rotation speed of 75 rpm, and 900 ml deaerated water with 0.5% sodium lauryl sulfate (w/v) as the dissolution medium. Dissolution profiles were evaluated by the Weibull parameters and the modified fit factor, ƒ^(1,area). The in vitro-in vivo relationship of CBZ tablets was examined. Compared with the results from the USP and Chinese Pharmacopoeia monograph, the proposed system provides a superior discriminatory method. Since the dissolution method in pharmacopoeia for CBZ tablets is unable to distinguish between a good and a bad product, the method presented here can be used for the quality control testing of CBZ tablets.

Predicting the in vivo release from a liposomal formulation by IVIVC and non-invasive positron emission tomography imaging

This study aimed to predict the in vivo performance from the in vitro release of a low-molecular weight model compound, [(18)F]-2-fluoro-2-deoxy-d-glucose ([(18)F]FDG), from liposomes and by means of positron emission tomography (PET). Liposomes composed of hydrogenated phosphatidylcholine (HPC) were prepared by a freeze-thaw method. Particle size distribution was measured by dynamic light scattering (DLS). In vitro release was examined with a dispersion method detecting the radioactivity of [(18)F]FDG. In vivo release of [(18)F]FDG, following i.p. injection of the liposomes in rats, was determined by using a Micro-PET scanner. Convolution was performed to predict the in vivo profiles from the in vitro data and to establish an in vitro-in vivo correlation (IVIVC). The in vivo predictions slightly underestimated the experimentally determined values. The magnitude of the prediction errors (13% and 19%) displayed a satisfactory IVIV relationship leaving yet room for further improvement. This study demonstrated for the first time the use of PET in attaining an IVIVC for a parenterally administered modified release dosage form. It is therefore possible to predict target tissue concentrations, e.g., in the brain, from in vitro release experiments. IVIVC using non-invasive PET imaging could thus be a valuable tool in drug formulation development, resulting in reduced animal testing.

In-vitro and in-vivo correlation for two gliclazide extended-release tablets

The aim of this study was to perform an in-vitro-in-vivo correlation (IVIVC) for two 60-mg gliclazide extended-release formulations (Fast and Slow release) given once a day and to compare their plasma concentrations over time. In-vitro release rate data were obtained for each formulation using the USP apparatus II, paddle stirrer at 50 and 100 rev min−1 in 0.1 M HCl and pH 7.4 phosphate buffer. The similarity factor (f2) was used to analyse the dissolution data. Eighteen healthy subjects participated in the study, conducted according to a completely randomized, two-way crossover design. The formulations were compared using area under the plasma concentration-time curve, AUC0-∞′, time to reach peak plasma concentration, Tmax', and peak plasma concentration Cmax', while correlation was determined between in-vitro release and in-vivo absorption. A linear correlation model was developed using percent absorbed data versus percent dissolved data from the two formulations. Predicted gliclazide concentrations were obtained by use of a curve fitting equation. Prediction errors were estimated for Cmax and area under the curve AUC0-∞ to determine the validity of the correlation. 0.1 M HCl at 50 rev min−1 was found to be the most discriminating dissolution method. Linear regression analysis of the mean percentage of dose absorbed versus the mean percentage of in-vitro release resulted in a significant correlation (r2 > 0.98) for the two formulations. An average percent prediction error for Cmax was 4.15% for Fast release and 3.99% for Slow release formulation whereas for AUC0-∞ it was 6.36% and 4.66% for Fast release and Slow release formulation, respectively.

The science of USP 1 and 2 dissolution: present challenges and future relevance

Since its inception, the dissolution test has come under increasing levels of scrutiny regarding its relevance, especially to the correlation of results to levels of drug in blood. The technique is discussed, limited to solid oral dosage forms, beginning with the scientific origins of the dissolution test, followed by a discussion of the roles of dissolution in product development, consistent batch manufacture (QC release), and stability testing. The ultimate role of dissolution testing, "to have the results correlated to in vivo results or in vivo in vitro correlation," is reviewed. The recent debate on mechanical calibration versus performance testing using USP calibrator tablets is presented, followed by a discussion of variability and hydrodynamics of USP Apparatus 1 and Apparatus 2. Finally, the future of dissolution testing is discussed in terms of new initiatives in the industry such as quality by design (QbD), process analytical technology (PAT), and design of experiments (DOE).

Extended release dosage form of glipizide: development and validation of a level A in vitro-in vivo correlation

Defining a quantitative and reliable relationship between in vitro drug release and in vivo absorption is highly desired for rational development, optimization, and evaluation of controlled-release dosage forms and manufacturing process. During the development of once daily extended-release (ER) tablet of glipizide, a predictive in vitro drug release method was designed and statistically evaluated using three formulations with varying release rates. In order to establish internally and externally validated level A in vitro-in vivo correlation (IVIVC), a total of three different ER formulations of glipizide were used to evaluate a linear IVIVC model based on the in vitro test method. For internal validation, a single-dose four-way cross over study (n=6) was performed using fast-, moderate-, and slow-releasing ER formulations and an immediate-release (IR) of glipizide as reference. In vitro release rate data were obtained for each formulation using the United States Pharmacopeia (USP) apparatus II, paddle stirrer at 50 and 100 rev. min(-1) in 0.1 M hydrochloric acid (HCl) and pH 6.8 phosphate buffer. The f(2) metric (similarity factor) was used to analyze the dissolution data. The formulations were compared using area under the plasma concentration-time curve, AUC(0-infinity), time to reach peak plasma concentration, T(max), and peak plasma concentration, C(max), while correlation was determined between in vitro release and in vivo absorption. A linear correlation model was developed using percent absorbed data versus percent dissolved from the three formulations. Predicted glipizide concentrations were obtained by convolution of the in vivo absorption rates. Prediction errors were estimated for C(max) and AUC(0-infinity) to determine the validity of the correlation. Apparatus II, pH 6.8 at 100 rev. min(-1) was found to be the most discriminating dissolution method. Linear regression analysis of the mean percentage of dose absorbed versus the mean percentage of in vitro release resulted in a significant correlation (r(2)>or=0.9) for the three formulations.

Predicting Human Drug Pharmacokinetics from In Vitro Permeability Using an Absorption–Disposition Model

The purpose of this research is to simulate the in vivo performance of drugs with a wide range of solubility and permeability characteristics formulated as oral dosage forms. The absorption-disposition model was developed using a number of physiological parameters as well as in vitro permeability data generated with Caco-2 cells, 2/4/A1 cells, and hexadecane membranes. A total of 13 drugs with varying solubility and permeability properties were examined using the absorption-disposition model to predict their pharmacokinetic profile. The correlation of predicted and experimentally determined AUC and Cmax, as measures of the pharmacokinetic profile, were >0.96 for all permeation techniques examined. The predictive ability of the model is influenced by the type of permeation method employed; 2/4/A1 cell data yielded the highest degree of accuracy in predicting Cmax and AUC values. The absorption-disposition model developed in this work accurately predicts the in vivo performance of a wide range of orally administered drugs with 8 of 9 drugs examined falling within 80-125% of the experimental value of AUC when using 2/4/A1 cells.

Level A in vitro-in vivo Correlation (IVIVC) Model with Bayesian Approach to Formulation Series

In vitro-in vivo correlation (IVIVC) models for formulation series are useful in drug development, but the current models are limited by their inability to include data variability in the predictions. Our goal was to develop a level A IVIVC model that provides predictions with probabilities. The Bayesian approach was used to describe uncertainty related to the model and the data. Three bioavailability studies of levosimendan were used to develop IVIVC model. Dissolution was tested at pH 5.8 with basket. The IVIVC model with Bayesian approach consisted of prior and observed data. All observed data were fitted to the one-compartment model together with prior data. Probability distributions of pharmacokinetic parameters and concentration time profiles were obtained. To test the external predictability of IVIVC model, only dissolution data of formulations E and F were used. The external predictability was good. The possibility to utilize all observed data when constructing IVIVC model, can be considered as a major strength of Bayesian approach. For levosimendan capsule data traditional IVIVC model was not predictable. The usefulness of IVIVC model with Bayesian approach was shown with our data, but the same approach can be used more widely for formulation optimization and for dissolution based biowaivers.

An automated process for building reliable and optimal in vitro/in vivo correlation models based on Monte Carlo simulations

Many mathematical models have been proposed for establishing an in vitro/in vivo correlation (IVIVC). The traditional IVIVC model building process consists of 5 steps: deconvolution, model fitting, convolution, prediction error evaluation, and cross-validation. This is a time-consuming process and typically a few models at most are tested for any given data set. The objectives of this work were to (1) propose a statistical tool to screen models for further development of an IVIVC, (2) evaluate the performance of each model under different circumstances, and (3) investigate the effectiveness of common statistical model selection criteria for choosing IVIVC models. A computer program was developed to explore which model(s) would be most likely to work well with a random variation from the original formulation. The process used Monte Carlo simulation techniques to build IVIVC models. Data-based model selection criteria (Akaike Information Criteria [AIC], R2) and the probability of passing the Food and Drug Administration "prediction error" requirement was calculated. To illustrate this approach, several real data sets representing a broad range of release profiles are used to illustrate the process and to demonstrate the advantages of this automated process over the traditional approach. The Hixson-Crowell and Weibull models were often preferred over the linear. When evaluating whether a Level A IVIVC model was possible, the model selection criteria AIC generally selected the best model. We believe that the approach we proposed may be a rapid tool to determine which IVIVC model (if any) is the most applicable.

A multi-mechanistic drug release approach in a bead dosage form and in vitro/in vivo correlations

An in vitro/in vivo relationship of a combined multi-mechanistic dosage form has now been established in the literature. In our previous study, we successfully prepared a combination of immediate release, enteric coated, and controlled-release (CR) beads and mathematically modeled in vitro and in vivo drug release characteristics of the combination based on the release profiles of individual beads. The objective of the present study is to develop in vitro/in vivo correlations (IVIVC) for three individual beads and the combination using theophylline as a model drug and the beagle dog as an animal model. In the study, an IVIVC correlation is estimated by two-stage procedures: deconvolution followed by comparison of the fraction of drug absorbed to the fraction of drug dissolved. The Wagner-Nelson mass balance method was used to deconvolute plasma drug concentration-time curves. In vitro, a two-stage medium (0.1 N HCl and pH 6.5 phosphate buffer) was used for the dissolution test; a 2h first stage (acidic) was selected based on the average gastric emptying time in a fasted dog. In vivo, t(lag) was used for the gastric emptying process for enteric coated beads and the combination, which contains enteric coated beads. A time-scaling technique was used to consider the rate difference between in vitro dissolution and in vivo absorption in the process of IVIVC. As shown in the results, a point-to-point correlation was established for each formulation. The linear regression analysis of the correlation was r2>0.99 for all three individual beads and 0.97 for the combined bead dosage form. The results suggest level A IVIVCs indicating an appropriateness for the in vitro and in vivo models used in this study.

Direct, differential-equation-based in-vitro-in-vivo correlation (IVIVC) method

A new, differential equation-based in-vitro-in-vivo correlation (IVIVC) method is proposed that directly relates the time-profiles of in-vitro dissolution rates and in-vivo plasma concentrations by using one- or multi-compartment pharmacokinetic models and a corresponding system of differential equations. The rate of in-vivo input is connected to the rate of in-vitro dissolution through a general functional dependency that allows for time scaling and time shifting. A multiplying factor that accounts for the variability of absorption conditions as the drug moves along is also incorporated. Two data sets incorporating slow-, medium-, and fast-release formulations were used to test the applicability of the method, and predictive powers were assessed with a leave-one-formulation-out approach. All fitted parameters had realistic values, and good or acceptable fits and predictions were obtained as measured by plasma concentration mean squared errors and percent AUC errors. Introduction of step-down functions that account for the transit of the dosage form past the intestinal sites of absorption proved useful. By avoiding the integral transforms used in the existing deconvolution- or convolution-based IVIVC models, the present method can provide increased transparency, improved performance, and greater modelling flexibility.

Utilisation of pharmacokinetic-pharmacodynamic modelling and simulation in regulatory decision-making

Modelling and simulation (M&S) play an important role in regulatory decision-making that affects both the public and industry. Technological advances in various fields related to drug development call for more focus on ways to optimise current drug development practices. Recognition of the potential of M&S by regulatory agencies inevitably has a substantial impact on drug development. The objective of the current review is to present the various regulatory initiatives for application of M&S to clinical drug development. The relevant parts of the various recommendations issued by the US Food and Drug Administration (FDA), via guidance documents and advisory committee meeting proceedings, are highlighted. Application of M&S to a variety of activities, such as integrating pharmacokinetic-pharmacodynamic knowledge across a new drug application and designing efficient trials, is discussed. Some of the challenges that pharmaceutical institutions currently face when implementing M&S projects, such as team structure, communication with regulators, training and time constraints, are also presented, and solutions are proposed.

In silico prediction of optimal in vivo delivery properties using convolution-based model and clinical trial simulation

PURPOSE

To develop a new strategy for the in silico evaluation of the optimal in vivo delivery properties of a drug, minimizing a cost function defined by the brain receptor occupancy obtained in positron-emission tomography experiments.

METHODS

A convolution-based model was formulated to link in vivo delivery rate to plasma concentrations whereas a second-stage model was used to link plasma concentrations to the pharmacodynamic effect. A feedback control approach was applied to identify the optimal in vivo delivery rate given an appropriate optimality criterion. Finally, clinical trial simulation was used as a supportive tool for decision-making by evaluating different scenarios accounting for pharmacokinetic/pharmacodynamic parameter uncertainty, inter-subject variability. and drug potency.

RESULTS

The results revealed that the mean in vivo delivery time significantly affects brain receptor occupancy whereas the fraction of the dose available for the systemic circulation shows the highest influence on brain receptor occupancy for a given in vivo delivery rate. Finally, variability on receptor occupancy seems to be more affected by the inter-individual variability on the disposition PK parameters.

CONCLUSION

The integration of convolution-based model. feedback control approach, and clinical trial simulation offers a unique tool for in ilico improvement of the drug development process by identifying critical issues on drug properties, optimal in vivo delivery rate, and potential problems related to the inter-individual variability.