Preclinical Bioavailability Strategy for Decisions on Clinical Drug Formulation Development: An In Depth Analysis

Lipid based formulations as supersaturating oral delivery systems: From current to future industrial applications

Lipid-based formulations, in particular supersaturated lipid-based formulations, are important delivery approaches when formulating challenging compounds, as especially low water-soluble compounds profit from delivery in a pre-dissolved state. In this article, the classification of lipid-based formulation is described, followed by a detailed discussion of different supersaturated lipid-based formulations and the recent advances reported in the literature. The supersaturated lipid-based formulations discussed include both the in situ forming supersaturated systems as well as the thermally induced supersaturated lipid-based formulations. The in situ forming drug supersaturation by lipid-based formulations has been widely employed and numerous clinically available products are on the market. There are some scientific gaps in the field, but in general there is a good understanding of the mechanisms driving the success of these systems. For thermally induced supersaturation, the technology is not yet fully understood and developed, hence more research is required in this field to explore the formulations beyond preclinical studies and initial clinical trials.

Usefulness of the Beagle Model in the Evaluation of Paracetamol and Ibuprofen Exposure after Oral Administration to Pediatric Populations: An Exploratory Study

The present study aimed to explore the usefulness of beagle dogs in combination with physiologically based pharmacokinetic (PBPK) modeling in the evaluation of drug exposure after oral administration to pediatric populations at an early stage of pharmaceutical product development. An exploratory, single-dose, crossover bioavailability study in six beagles was performed. A paracetamol suspension and an ibuprofen suspension were coadministered in the fasted-state conditions, under reference-meal fed-state conditions, and under infant-formula fed-state conditions. PBPK models developed with GastroPlus v9.7 were used to inform the extrapolation of beagle data to human infants and children. Beagle-based simulation outcomes were compared with published human-adult-based simulations. For paracetamol, fasted-state conditions and reference-meal fed-state conditions in beagles appeared to provide adequate information for the applied scaling approach. Fasted-state and/or reference-meal fed-state conditions in beagles appeared suitable to simulate the performance of ibuprofen suspension in pediatric populations. Contrary to human-adult-based translations, extrapolations based on beagle data collected under infant-formula fed-state conditions appeared less useful for informing simulations of plasma levels in pediatric populations. Beagle data collected under fasted and/or reference-meal fed-state conditions appeared to be useful in the investigation of pediatric product performance of the two investigated highly permeable and highly soluble drugs in the upper small intestine. The suitability of the beagle as a preclinical model to understand pediatric drug product performance under different dosing conditions deserves further evaluation with a broader spectrum of drugs and drug products and comparisons with pediatric in vivo data.

Meningeal B Cell Clusters Correlate with Submeningeal Pathology in a Natural Model of Multiple Sclerosis

Multiple sclerosis (MS) is an idiopathic demyelinating disease in which meningeal inflammation correlates with accelerated disease progression. The study of meningeal inflammation in MS has been limited because of constrained access to MS brain/spinal cord specimens and the lack of experimental models recapitulating progressive MS. Unlike induced models, a spontaneously occurring model would offer a unique opportunity to understand MS immunopathogenesis and provide a compelling framework for translational research. We propose granulomatous meningoencephalomyelitis (GME) as a natural model to study neuropathological aspects of MS. GME is an idiopathic, progressive neuroinflammatory disease of young dogs with a female bias. In the GME cases examined in this study, the meninges displayed focal and disseminated leptomeningeal enhancement on magnetic resonance imaging, which correlated with heavy leptomeningeal lymphocytic infiltration. These leptomeningeal infiltrates resembled tertiary lymphoid organs containing large B cell clusters that included few proliferating Ki67+ cells, plasma cells, follicular dendritic/reticular cells, and germinal center B cell-like cells. These B cell collections were confined in a specialized network of collagen fibers associated with the expression of the lympho-organogenic chemokines CXCL13 and CCL21. Although neuroparenchymal perivascular infiltrates contained B cells, they lacked the immune signature of aggregates in the meningeal compartment. Finally, meningeal B cell accumulation correlated significantly with cortical demyelination reflecting neuropathological similarities to MS. Hence, during chronic neuroinflammation, the meningeal microenvironment sustains B cell accumulation that is accompanied by underlying neuroparenchymal injury, indicating GME as a novel, naturally occurring model to study compartmentalized neuroinflammation and the associated pathology thought to contribute to progressive MS.

Orally Administered Drug Solubility-Enhancing Formulations: Lesson Learnt from Optimum Solubility-Permeability Balance

Although oral drug delivery is considered as most acceptable route for administering the active pharmaceutical ingredients to patients of all age-groups with the exceptions of bed-ridden patients and infants, the extent and rate of drug reaching the systemic circulation (in other word, drug bioavailability) always depends on many factors such as drug solubility in gastrointestinal fluids and drug permeation into intraluminal epithelial membrane structure, absence (fasting state) and presence (fed state) of food materials in the gastrointestinal tract, and individual variations in gastric emptying time. Taking the most influential factors like drug solubility and its permeability into consideration, these two factors play a pivotal role and even act as the litmus test for the formulation scientists who involve in oral dosage form development. It is very clear that there should be an optimum solubility and permeability balance to be reachable for getting the desired drug bioavailability to exert the intended therapeutic activity. The objectives of current review are (1) to provide an overview of two-different categories of poorly water soluble API molecules, (2) to describe briefly three-different case studies taken from drug solubility-enhancing formulations dealing with interplay between solubility and permeability, and (3) to showcase selected examples of solubility-permeability interplay phenomena arising out from the various orally administrable dosage forms. The lessons learnt from the past and current literatures are certainly encouraging to go ahead for oral dosage form development but with the prior knowledge about the possible existence of solubility-permeability interplay/tradeoff phenomenon.

Applying Computational Predictions of Biorelevant Solubility Ratio Upon Self-Emulsifying Lipid-Based Formulations Dispersion to Predict Dose Number

Computational approaches are increasingly utilised in development of bio-enabling formulations, including self-emulsifying drug delivery systems (SEDDS), facilitating early indicators of success. This study investigated if in silico predictions of drug solubility gain i.e. solubility ratios (SR), after dispersion of a SEDDS in biorelevant media could be predicted from drug properties. Apparent solubility upon dispersion of two SEDDS in FaSSIF was measured for 30 structurally diverse poorly water soluble drugs. Increased drug solubility upon SEDDS dispersion was observed in all cases, with higher SRs observed for cationic and neutral versus anionic drugs at pH 6.5. Molecular descriptors and solid-state properties were used as inputs during partial least squares (PLS) modelling resulting in predictive models for SR_MC (r² = 0.81) and SR_LC (r² = 0.77). Multiple linear regression (MLR) facilitated generation of simplified SR equations with high predictivity (SR_MC r² = 0.74; SR_LC r² = 0.69), requiring only three drug properties; partition coefficient at pH 6.5 (logD_6.5), melting point (Tm) and aromatic bonds as fraction of total bonds (F-AromB). Through using the equations to inform developability classification system (DCS) classes for drugs that have already been licensed as lipid-based formulations, merits for development with SEDDS was predicted for 2/3 drugs.

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.