In Vitro, in Silico, and in Vivo Assessments of Intestinal Precipitation and Its Impact on Bioavailability of a BCS Class 2 Basic Compound

Evaluation of the impact of mucin on supersaturation and permeation of BCS class 2 basic drugs

This study evaluated the impact of mucin on supersaturation and permeation of BCS Class 2 basic drugs in a pH-shift, 2-stage model using three model compounds, dipyridamole, ricobendazole, and Compound A. The three compounds showed various degrees of supersaturation (DoS) in Stage 2 and modest to no increases in flux with the presence of mucin in the dissolution media. Mucin's impact on DoS and flux, if any, appeared to be compound specific and possibly related to its pKa and ionization state. Overall, the increases in supersaturation and permeation due to mucin ranged from modest to minimal for the three model compounds under the conditions tested. The pH-shift model using MacroFLUX was able to monitor gastric and intestinal dissolution and simultaneously assess the effect of intestinal mucin on supersaturation and flux.

Comparative Evaluation of Particle Size Reduction, Salt Formation, and Amorphous Formulation on the Biopharmaceutical Performance of a Weak Base Drug Candidate

Various approaches have been developed to enhance the solubility or dissolution rate for the delivery of poorly water-soluble molecules. In this work, guided by an in silico solubility sensitivity analysis for oral absorption, a comparative assessment of the biopharmaceutical performance of a jet-milled free base, a tosylate salt, and a 50:50 (w/w) amorphous solid dispersion (ASD) with hydroxypropyl methylcellulose acetate succinate (HPMCAS) of a weak base drug candidate, GDC-3280, was conducted. Successful particle size reduction without amorphization or form change was confirmed for the jet-milled free base. The potential of solubility enhancement and desupersaturation risk were identified for tosylate salt and ASD formulation by measurements of tosylate salt solubility product constant (Ksp) and amorphous solubility of GDC-3280. In vitro dissolution testing demonstrated dissolution rate improvement for the jet-milled free base when compared with the unmilled free base and confirmed solubility enhancement followed by desupersaturation for GDC-3280 tosylate salt and ASD formulation. A crystallization inhibitor, hydroxypropyl methylcellulose (HPMC), was found to slow down the desupersaturation of tosylate salt solution, providing general insights for the development of pharmaceutical salts with disproportionation risks. Finally, a pharmacokinetic study in dogs showed that the in vivo exposure increased by 1.7- to 2-fold for the tosylate salt and ASD formulation compared with the jet-milled free base, consistent with the in silico solubility sensitivity analysis for the fraction of drug absorbed. Overall, this work provides insights into the evaluation of multiple formulation approaches for enhancing the biopharmaceutical performance of poorly water-soluble drugs.

Digitalizing the TIM-1 Model using Computational Approaches-Part One: TIM-1 Data Explorer

The TIM-1 gastrointestinal model is one of the most advanced in vitro systems currently available for biorelevant dissolution testing. This technology, the initial version of which was developed nearly 30 years ago and has been subject to a number of significant updates over this period, simulates the dynamic environment of the human gastrointestinal tract, including pH, transfer times, secretion of bile, enzymes, and electrolytes. In the pharmaceutical industry, the TIM-1 system is used to support drug product design and provide a biopredictive assessment of drug product performance. Typically, the bioaccessibility data sets generated by TIM-1 experiments are used to qualitatively compare formulation performance, and the use of bioaccessibility data as inputs for physiologically based pharmacokinetic (PBPK) modeling for quantitative predictions is limited. To expand the utility of the TIM-1 model beyond standard bioaccessibility measurements (which define the fraction available for absorption), we have developed a computational tool, TIM-1 Data Explorer, to describe the fluid and mass balance within the TIM-1 system. The use of this tool allows a detailed inspection and in-depth interpretation of the experimental data. In addition to mass balance calculation, this model also can be used to describe the critical processes a drug substance would undergo during a TIM-1 experiment, such as dissolution, precipitation on transfer from the stomach to duodenum, and redissolution. The TIM-1 Data Explorer was validated in two case studies. In the first case study with paracetamol, we have shown the ability of the simulator to adequately describe mass transfer events within the TIM-1 system, and in the second study with a weakly basic in-house compound, PF-07059013, the TIM-1 Data Explorer was successfully used to describe dissolution and precipitation processes.

Progressive tools and critical strategies for development of best fit PBPK model aiming better in vitro-in vivo correlation

Nowadays, conducting discriminative dissolution experiments employing physiologically based pharmacokinetic modeling (PBPK) or physiologically based biopharmaceutical modeling (PBBM) is gaining significant importance in quantitatively predicting oral absorption of drugs. Mechanistic understanding of each process involved in drug absorption and its impact on the performance greatly facilitates designing a formulation with high confidence. Unfortunately, the biggest challenge scientists are facing in current days is the lack of standardized protocol for integrating dissolution experiment data during PBPK modeling. However, in vitro-in vivo drug release interrelation can be improved with the consideration and development of appropriate biorelevant dissolution media that closely mimic physiological conditions. Multiple reported dissolution models have described nature and functionality of different regions of the gastrointestinal tract (GI) to more accurately design discriminative dissolution media. Dissolution experiment data can be integrated either mechanistically or without a mechanism depending primarily on the formulation type, biopharmaceutics classification system (BCS) class and particle size of the drug substance. All such parameters are required to be considered for selecting the appropriate functions during PBPK modeling to produce a best fit model. The primary focus of this review is to critically discuss various progressive dissolution models and tools, existing challenges and approaches for establishing best fit PBPK model aiming better in vitro-in vivo correlation (IVIVC). Strategies for proper selection of dissolution models as an input function in PBPK/PBBM modeling have also been critically discussed. Logical and scientific pathway for selection of different type of functions and integration events in the commercially available in silico software has been described through case studies.

Evaluating the bioequivalence of two pitavastatin calcium formulations based on IVIVC modeling and clinical study

In vitro-in vivo correlation (IVIVC) allows prediction of the in vivo performance of a pharmaceutical product based on its in vitro drug release profiles and can be used to reduce the number of bioequivalence (BE) studies during product development, and facilitate certain regulatory decisions. Here, we developed an IVIVC model for pitavastatin calcium, a basic Biopharmaceutics Classification System (BCS) II lipid-lowering drug, which was then used to predict the BE outcome of formulations manufactured at two manufacturers. In addition, virtual trials using the IVIVC model using pH 4.0 acetate buffer dissolution showed similarity in areas under the curves and maximum plasma concentration (Cmax ) for test and reference tablets under fasting condition. These predicted results were verified in definitive BE study. In conclusion, we demonstrated that for certain BCS II molecules, IVIVC modeling could be used as a priori to predict the BE outcome.

Integration of In Silico, In Vitro and In Situ Tools for the Preformulation and Characterization of a Novel Cardio-Neuroprotective Compound during the Early Stages of Drug Development

The main aim of this work is the biopharmaceutical characterization of a new hybrid benzodiazepine-dihydropyridine derivative, JM-20, derived with potent anti-ischemic and neuroprotective effects. In this study, the pKa and the pH-solubility profile were experimentally determined. Additionally, effective intestinal permeability was measured using three in vitro epithelial cell lines (MDCK, MDCK-MDR1 and Caco-2) and an in situ closed-loop intestinal perfusion technique. The results indicate that JM-20 is more soluble at acidic pH (9.18 ± 0.16); however, the Dose number (Do) was greater than 1, suggesting that it is a low-solubility compound. The permeability values obtained with in vitro cell lines as well as with the in situ perfusion method show that JM-20 is a highly permeable compound (Caco-2 value 3.8 × 10-5). The presence of an absorption carrier-mediated transport mechanism was also demonstrated, as well as the efflux effect of P-glycoprotein on the permeability values. Finally, JM-20 was provisionally classified as class 2 according to the biopharmaceutical classification system (BCS) due to its high intestinal permeability and low solubility. The potential good oral absorption of this compound could be limited by its solubility.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

Novel High-Drug-Loaded Amorphous Dispersion Tablets of Posaconazole; In Vivo and In Vitro Assessment

Amorphous solid dispersions (ASDs) can increase the bioavailability of drugs with poor aqueous solubility. However, concentration-sustaining dispersion polymers (CSPs) incorporated in ASDs can result in low drug loading and, therefore, a large dosage-form size or multiple units to meet dose requirements, potentially decreasing patient compliance. To address this challenge, a high-loaded dosage-form (HLDF) architecture for ASDs was developed, in which a drug is first spray-dried with a high glass-transition temperature (T_g) dispersion polymer to facilitate high drug loading while maintaining physical stability. The ASD is then granulated with a CSP designed to extend supersaturation in solution. The HLDF differs from traditional ASD architectures in which the dispersion polymer inside the ASD acts as the CSP. By strategically combining two different polymers, one "inside" and one "outside" the ASD, solubilization performance, physical stability, and overall drug loading are maximized. This study demonstrates in vivo performance of the HLDF architecture using posaconazole as a model drug. Two sizes of HLDF tablets were tested in beagle dogs, along with traditional ASD architecture (benchmark) tablets, ASD tablets without a CSP, and a commercial crystalline oral suspension (Noxafil OS). HLDF tablets performed equivalently to the benchmark tablets, the smaller HLDF tablet being 40% smaller (by mass) than the benchmark tablet. The HLDF tablets doubled the blood plasma AUC relative to Noxafil OS. In line with the in vivo outcome, in vitro results in a multicompartment dissolution apparatus demonstrated similar area under the curve (AUC) values in the intestinal compartment for ASD tablets. However, the in vitro data underpredicted the relative in vivo AUC of Noxafil OS compared to the ASD tablets. This study demonstrated that the HLDF approach can increase drug loadings while achieving good performance for ASD drug products.

Mechanistic Study of Belinostat Oral Absorption From Spray-Dried Dispersions

Spray-dried dispersions (SDDs) are an important technology for enhancing the oral bioavailability of poorly water-soluble drugs. To design an effective oral SDD formulation, the key rate-determining step(s) for oral drug absorption must be understood. This work combined in vivo and in vitro tests with in silico modeling to identify the rate-determining steps for oral absorption of belinostat SDDs made with 3 different polymers (PVP K30, PVP VA64, and HPMCAS-M). The goal was developing a belinostat SDD formulation that maximizes oral bioavailability (ideally matching the performance of a belinostat oral solution) and defining critical performance attributes for formulation optimization. The in vivo pharmacokinetic study with beagle dogs demonstrated that 1 of the 3 SDDs (PVP K30 SDD) matched the performance of the oral solution. In vitro data coupled with in silico modeling elucidated differences among the SDDs and supported the hypothesis that absorption of belinostat in the small intestine from the other 2 SDDs (PVP VA64 and HPMCAS-M) may be limited by dissolution rate or reduced drug activity (maximum concentration) in the presence of polymer. It was concluded that drug concentration in the stomach before emptying into the proximal intestine is a key factor for maximizing in vivo performance.