Characterising Drug Release from Immediate-Release Formulations of a Poorly Soluble Compound, Basmisanil, Through Absorption Modelling and Dissolution Testing

Discriminative Dissolution Method Development Through an aQbD Approach

Using a one-factor-at-a-time approach for dissolution method and discrimination analysis can be time-consuming and may not yield the optimal and discriminative method. To address this, we have developed a two-stage workflow for the dissolution method development followed by demonstration of discrimination power through an analytical Quality by Design (aQbD) approach. In the first stage, an optimal dissolution method was achieved by determining the method operable design region (MODR) through a design of experiment study of the high-risk method-related parameters. In the second stage, we established a Formulation-Discrimination Correlation Diagram strategy to examine the method discrimination capability, through which one can determine the method discriminative design region (MDDR) and visualize the impact of each formulation parameter and their interactions on dissolution. The application of aQbD principles into a workflow provides a scientific-driven guidance for robust method development and demonstrating discrimination power for dissolution methods.

Streamlining Food Effect Assessment - Are Repeated Food Effect Studies Needed? An IQ Analysis

Current regulatory guidelines on drug-food interactions recommend an early assessment of food effect to inform clinical dosing instructions, as well as a pivotal food effect study on the to-be-marketed formulation if different from that used in earlier trials. Study waivers are currently only granted for BCS class 1 drugs. Thus, repeated food effect studies are prevalent in clinical development, with the initial evaluation conducted as early as the first-in-human studies. Information on repeated food effect studies is not common in the public domain. The goal of the work presented in this manuscript from the Food Effect PBPK IQ Working Group was to compile a dataset on these studies across pharmaceutical companies and provide recommendations on their conduct. Based on 54 studies collected, we report that most of the repeat food effect studies do not result in meaningful differences in the assessment of the food effect. Seldom changes observed were more than twofold. There was no clear relationship between the change in food effect and the formulation change, indicating that in most cases, once a compound is formulated appropriately within a specific formulation technology, the food effect is primarily driven by inherent compound properties. Representative examples of PBPK models demonstrate that following appropriate validation of the model with the initial food effect study, the models can be applied to future formulations. We recommend that repeat food effect studies should be approached on a case-by-case basis taking into account the totality of the evidence including the use of PBPK modeling.

Developing a Formulation Strategy Coupled with PBPK Modeling and Simulation for the Weakly Basic Drug Albendazole

Albendazole (ABZ) is a weakly basic drug that undergoes extensive presystemic metabolism after oral administration and converts to its active form albendazole sulfoxide (ABZ_SO). The absorption of albendazole is limited by poor aqueous solubility, and dissolution is the rate-limiting step in the overall exposure of ABZ_SO. In this study, PBPK modeling was used to identify formulation-specific parameters that impact the oral bioavailability of ABZ_SO. In vitro experiments were carried out to determine pH solubility, precipitation kinetics, particle size distribution, and biorelevant solubility. A transfer experiment was conducted to determine the precipitation kinetics. A PBPK model for ABZ and ABZ_SO was developed using the Simcyp™ Simulator based on parameter estimates from in vitro experiments. Sensitivity analyses were performed to assess the impact of physiological parameters and formulation-related parameters on the systemic exposure of ABZ_SO. Model simulations predicted that increased gastric pH significantly reduced ABZ absorption and, subsequently, ABZ_SO systemic exposure. Reducing the particle size below 50 µm did not improve the bioavailability of ABZ. Modeling results illustrated that systemic exposure of ABZ_SO was enhanced by increasing solubility or supersaturation and decreasing the drug precipitation of ABZ at the intestinal pH level. These results were used to identify potential formulation strategies to enhance the oral bioavailability of ABZ_SO.

Pediatric Mini-Tablets: Predicting the Hidden Risk of Fill Errors

Compressed mini-tablets in sachets or capsules are an increasingly prevalent oral solid dosage form for pediatric products. While resembling adult tablets, additional care is required to control weight and potency (blend uniformity) variation due to their small size (≤2.5 mm average diameter). Additionally, sachet fill count errors complicate dose accuracy as they are difficult to resolve with weight-checking equipment. This study quantified the probability of failing content uniformity (CU) specifications (which results in the inability to release a batch) defined in USP <905> using a Monte Carlo computational model. Failure risk was modeled as a function of sachet fill count, mini-tablet weight, potency distribution, and fill error frequency. The model allows product developers to (1) determine appropriate fill counts based on anticipated product weight and potency relative standard deviation (RSD), (2) set fill error probability tolerances for sachet filling processes, (3) identify CU improvement opportunities, and (4) quantify the probability of CU failure informing risk management activities and risk disclosure for regulatory agencies. A representative product with weight and potency RSD no greater than 5%, fill count of 1-4 mini-tablets per sachet, and fill error probability per mini-tablet filled of 0.1% may experience CU batch failure probabilities as high as 8.23%, but only 0.283% if the fill count is increased to 5-10 mini-tablets per sachet. Generally, fill counts of less than five mini-tablets per sachet should be avoided where possible.

Physiologically Based Biopharmaceutics Modeling of Food Effect for Basmisanil: A Retrospective Case Study of the Utility for Formulation Bridging

Basmisanil, is a lipophilic drug substance, exhibiting poor solubility and good permeability (BCS class 2). A validated physiologically based biopharmaceutics model (PBBM) has been previously described for tablets dosed in the fed state. The PBBM captured the less than proportional increases in exposure at higher doses well and indicated that absorption was dissolution rate-limited below 200 mg while solubility was limiting for higher doses. In this study, a model for dosing in the fasted state is described and is verified for simulation of the food effect where exposures were ~1.5 fold higher when a 660 mg tablet was given with food. The model is then applied to simulate the food effect for a granules formulation given at a lower dose (120 mg). The food effect at the lower dose was reasonably simulated with a ratio of simulated/observed food effect of 1.35 for Cmax and 0.83 for AUC. Sensitivity analysis was carried out for uncertain model parameters to confirm that the model could predict the magnitude of the positive food effect with moderate to high confidence. This study suggests that a verified PBBM can provide a useful alternative to a repeat food effect study when formulation changes are minor. However, there is need for further evaluation of the approach and a definition of what formulation changes are minor in this context. In addition, this work highlights some uncertainties in the handling of solubility in PBBM, in particular around temperature dependency of solubility and the parameterization of bile salt solubilization using measurements in biorelevant media.

The Use of Physiologically Based Pharmacokinetic Analyses-in Biopharmaceutics Applications -Regulatory and Industry Perspectives

The use of physiologically based pharmacokinetic (PBPK) modeling to support the drug product quality attributes, also known as physiologically based biopharmaceutics modeling (PBBM) is an evolving field and the interest in using PBBM is increasing. The US-FDA has emphasized on the use of patient centric quality standards and clinically relevant drug product specifications over the years. Establishing an in vitro in vivo link is an important step towards achieving the goal of patient centric quality standard. Such a link can aid in constructing a bioequivalence safe space and establishing clinically relevant drug product specifications. PBBM is an important tool to construct a safe space which can be used during the drug product development and lifecycle management. There are several advantages of using the PBBM approach, though there are also a few challenges, both with in vitro methods and in vivo understanding of drug absorption and disposition, that preclude using this approach and therefore further improvements are needed. In this review we have provided an overview of experience gained so far and the current perspective from regulatory and industry point of view. Collaboration between scientists from regulatory, industry and academic fields can further help to advance this field and deliver on promises that PBBM can offer towards establishing patient centric quality standards.

Development and Validation of a Discriminatory Dissolution Model for an Immediately Release Dosage Form by DOE and Statistical Approaches

A discriminatory dissolution model was built through DOE with multivariate analysis of variance (MANOVA) and multiple linear regression (MLR) modeling to assess dissolution operational space for a highly water soluble immediate-release solid dosage drug product. The dissolution was utilized in the following five aspects: (1) understand the impact of individual variables and their interactions on dissolution performance through effect analysis; (2) explain the lack of discriminatory power of the initial dissolution condition used in early phase development by prediction profiler; (3) predict discriminatory dissolution operational space to differentiate photo degraded drug products from control with contour profiler analysis; (4) validate by the external experimental data acquired with the initial nondiscriminatory dissolution condition and the predicted discriminatory dissolution condition, followed by model independent statistical analysis (e.g., f2); and (5) establish correlation of the discriminatory dissolution with disintegration. The selected discriminatory dissolution method was validated by demonstrating accuracy, precision and linearity, specificity, repeatability, intermediate precision, stability, filter verification, and robustness.

Basmisanil, a highly selective GABAA-α5 negative allosteric modulator: preclinical pharmacology and demonstration of functional target engagement in man

GABA_A-α5 subunit-containing receptors have been shown to play a key modulatory role in cognition and represent a promising drug target for cognitive dysfunction, as well as other disorders. Here we report on the preclinical and early clinical profile of a novel GABA_A-α5 selective negative allosteric modulator (NAM), basmisanil, which progressed into Phase II trials for intellectual disability in Down syndrome and cognitive impairment associated with schizophrenia. Preclinical pharmacology studies showed that basmisanil is the most selective GABA_A-α5 receptor NAM described so far. Basmisanil bound to recombinant human GABA_A-α5 receptors with 5 nM affinity and more than 90-fold selectivity versus α1, α2, and α3 subunit-containing receptors. Moreover, basmisanil inhibited GABA-induced currents at GABA_A-α5 yet had little or no effect at the other receptor subtypes. An in vivo occupancy study in rats showed dose-dependent target engagement and was utilized to establish the plasma exposure to receptor occupancy relationship. At estimated receptor occupancies between 30 and 65% basmisanil attenuated diazepam-induced spatial learning impairment in rats (Morris water maze), improved executive function in non-human primates (object retrieval), without showing anxiogenic or proconvulsant effects in rats. During the Phase I open-label studies, basmisanil showed good safety and tolerability in healthy volunteers at maximum GABA_A-α5 receptor occupancy as confirmed by PET analysis with the tracer [¹¹C]-Ro 15-4513. An exploratory EEG study provided evidence for functional activity of basmisanil in human brain. Therefore, these preclinical and early clinical studies show that basmisanil has an ideal profile to investigate potential clinical benefits of GABA_A-α5 receptor negative modulation.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been extensively applied to quantitatively translate in vitro data, predict the in vivo performance, and ultimately support waivers of in vivo clinical studies. In the area of biopharmaceutics and within the context of model-informed drug discovery and development (MID3), there is a rapidly growing interest in applying verified and validated mechanistic PBPK models to waive in vivo clinical studies. However, the regulatory acceptance of PBPK analyses for biopharmaceutics and oral drug absorption applications, which is also referred to variously as "PBPK absorption modeling" [Zhang et al. CPT: Pharmacometrics Syst. Pharmacol. 2017, 6, 492], "physiologically based absorption modeling", or "physiologically based biopharmaceutics modeling" (PBBM), remains rather low [Kesisoglou et al. J. Pharm. Sci. 2016, 105, 2723] [Heimbach et al. AAPS J. 2019, 21, 29]. Despite considerable progress in the understanding of gastrointestinal (GI) physiology, in vitro biopharmaceutic and in silico tools, PBPK models for oral absorption often suffer from an incomplete understanding of the physiology, overparameterization, and insufficient model validation and/or platform verification, all of which can represent limitations to their translatability and predictive performance. The complex interactions of drug substances and (bioenabling) formulations with the highly dynamic and heterogeneous environment of the GI tract in different age, ethnic, and genetic groups as well as disease states have not been yet fully elucidated, and they deserve further research. Along with advancements in the understanding of GI physiology and refinement of current or development of fully mechanistic in silico tools, we strongly believe that harmonization, interdisciplinary interaction, and enhancement of the translational link between in vitro, in silico, and in vivo will determine the future of PBBM. This Perspective provides an overview of the current status of PBBM, reflects on challenges and knowledge gaps, and discusses future opportunities around PBPK/PD models for oral absorption of small and large molecules to waive in vivo clinical studies.

Investigating a Modified Apparatus to Discriminate the Dissolution Capacity In Vitro and Establish an IVIVC of Mycophenolate Mofetil Tablets in the Fed State

In this study, a modified dissolution apparatus was developed by equipping a USP apparatus Ⅰ with an open-loop system to discriminate the dissolution capacity in vitro and establish an in vitro and in vivo correlation (IVIVC) for mycophenolate mofetil (MMF) tablets. MMF had strong pH-dependent solubility that could influence the dissolution rate in vivo after the meal. Dissolution tests involving reference (Cellcept®) and test formulations (F1 and F2) were conducted using pH 4.5 acetate buffer to simulate gastric fluids in the fed state. The dissolution profiles of the reference and test formulations were distinguished by using the modified dissolution apparatus and compared with those determined using the USP apparatuses Ⅱ and Ⅳ, and the dissolution capacities of the formulations were discriminated at different sampling time-points. The results of human bioequivalence (BE) studies in the fed state were consistent with in vitro evaluations that the maximum concentrations (C_max,in vivo) of both F1 and F2 fell below the acceptable range (80.00%). A level A IVIVC between the absorption fraction in vivo and dissolution in vitro, and a level C correlation between C_max,in vivo and C_{max,in vitro}, were established to guide the optimization of the tablet formulation containing MMF.

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.

Application of percolation threshold to disintegration and dissolution of ibuprofen tablets with different microcrystalline cellulose grades

The study presented was conducted to determine whether a percolation threshold value, previously determined for ibuprofen/microcrystalline cellulose (MCC) blends using percolation theory and compression data (Queiroz et al., 2019), could translate to tablet disintegration and dissolution data. The influence of MCC grade (air stream dried versus spray dried) on tablet disintegration and dissolution was also investigated. Complementary to conventional disintegration and dissolution testing, Raman imaging determined drug distribution within tablets, and in-line particle video microscopy (PVM) and focused-beam reflectance measurement (FBRM) monitored tablet disintegration. Tablets were prepared containing 0-30% w/w ibuprofen. Raman imaging confirmed the percolation threshold by quantifying the number and equivalent circular diameters of ibuprofen domains on tablet surfaces. Across the percolation threshold, a step change in dissolution behaviour occurred, and tablets containing air stream dried MCC showed slower disintegration rates compared to tablets containing spray dried MCC. Dissolution measurements confirmed experimentally a percolation threshold in agreement with that determined using percolation theory and compression data. An increase in drug domains, due to cluster formation, and less efficient tablet disintegration contributed to slower ibuprofen dissolution above the percolation threshold. Slower dissolution was measured for tablets containing air stream dried compared to spray dried MCC.

Integrating Drug- and Formulation-Related Properties With Gastrointestinal Tract Variability Using a Product-Specific Particle Size Approach: Case Example Ibuprofen

In the present study, an in vitro-in vivo extrapolation of dissolution integrated to a physiologically based pharmacokinetics modeling approach, considering a product-specific particle size distribution and a self-buffering effect of the drug, is introduced and appears to be a promising translational modeling strategy to support drug product development, manufacturing changes and setting clinically relevant specifications for immediate release formulations containing ibuprofen and other weak acids with similar properties.

In vivo models and decision trees for formulation development in early drug development: A review of current practices and recommendations for biopharmaceutical development

The ability to predict new chemical entity performance using in vivo animal models has been under investigation for more than two decades. Pharmaceutical companies use their own strategies to make decisions on the most appropriate formulation starting early in development. In this paper the biopharmaceutical decision trees available in four EFPIA partners (Bayer, Boehringer Ingelheim, Bristol Meyers Squibb and Janssen) were discussed by 7 companies of which 4 had no decision tree currently defined. The strengths, weaknesses and opportunities for improvement are discussed for each decision tree. Both pharmacokineticists and preformulation scientists at the drug discovery & development interface responsible for lead optimization and candidate selection contributed to an overall picture of how formulation decisions are progressed. A small data set containing compound information from the database designed for the IMI funded OrBiTo project is examined for interrelationships between measured physicochemical, dissolution and relative bioavailability parameters. In vivo behavior of the drug substance and its formulation in First in human (FIH) studies cannot always be well predicted from in vitro and/or in silico tools alone at the time of selection of a new chemical entity (NCE). Early identification of the risks, challenges and strategies to prepare for formulations that provide sufficient preclinical exposure in animal toxicology studies and in FIH clinical trials is needed and represents an essential part of the IMI funded OrBiTo project. This article offers a perspective on the use of in vivo models and biopharmaceutical decision trees in the development of new oral drug products.

Stability and compatibility of Basmisanil granules co-administered with soft food

Co-administration of solid oral dosage forms with soft food or beverages is commonly used to facilitate administration and to improve compliance in the paediatric and geriatric population and in patient groups with swallowing difficulties. The present case study was conducted to investigate the compatibility, stability and dissolution of Basmisanil administered as granules mixed with different soft food matrices. The data were generated to justify dosing instructions, according which Basmisanil should be sprinkled on or mixed with one tablespoon of soft food to aid swallowing. Different soft food types were selected to cover a broad range of various food components (e.g. fat, protein, carbohydrates, fiber and water) and pH. Active content and degradation products of the active substance were determined after mixing the granules with the semisolid food matrix and after two hours of storage under ambient conditions, respectively. In-vitro dissolution tests of granule/food mixtures were also conducted. Furthermore, the stability of the API polymorph was evaluated. Basmisanil shows good chemical stability when the granules are mixed with soft food and consumed within two hours. No polymorphic conversion (anhydrate to monohydrate) could be detected in the granule/food mixtures after preparation and after storage up to 24 h. The in-vitro dissolution of the API from the granules was not adversely affected by the presence of the food matrix. All results were comparable regardless of the tested food matrix. The results do not prohibit the administration of the granules with soft food to the patient.