In silico prediction of the solubility advantage for amorphous drugs – Are there property-based rules for drug discovery and early pharmaceutical development?

Does Media Choice Matter When Evaluating the Performance of Hydroxypropyl Methylcellulose Acetate Succinate-Based Amorphous Solid Dispersions?

Hydroxypropyl methylcellulose acetate succinate (HPMCAS) is a weakly acidic polymer that is widely used in the formulation of amorphous solid dispersions (ASDs). While the pH-dependent solubility of HPMCAS is widely recognized, the role of other solution properties, including buffer capacity, is less well understood in the context of ASD dissolution. The goal of this study was to elucidate the rate-limiting steps for drug and HPMCAS release from ASDs formulated with two poorly water soluble model drugs, indomethacin and indomethacin methyl ester. The surface area normalized release rate of the drug and/or polymer in a variety of media was determined. The HPMCAS gel layer apparent pH was determined by incorporating pH sensitive dyes into the polymer matrix. Water uptake extent and rate into the ASDs were measured gravimetrically. For neat HPMCAS, the rate-limiting step for polymer dissolution was observed to be the polymer solubility at the polymer-solution interface. This, in turn, was impacted by the gel layer pH which was found to be substantially lower than the bulk solution pH, varying with medium buffer capacity. For the ASDs, the HPMCAS release rate was found to control the drug release rate. However, both drugs reduced the polymer release rate with indomethacin methyl ester having a larger impact. In low buffer capacity media, the presence of the drug had less impact on release rates when compared to observations in higher strength buffers, suggesting changes in the rate-limiting steps for HPMCAS dissolution. The observations made in this study can contribute to the fundamental understanding of acidic polymer dissolution in the presence and absence of a molecularly dispersed lipophilic drug and will help aid in the design of more in vivo relevant release testing experiments.

Trends in small molecule drug properties: A developability molecule assessment perspective

Developability molecule assessment is a key interfacial capability across the biopharmaceutical industry, screening and staging molecules discovered by medicinal chemists for successful chemistry manufacturing controls (CMC) development and launch. The breadth of responsibility and expertise such teams possess puts them in a unique position to understand the impact of the physicochemical properties of a drug during its initial discovery and subsequent development. However, most of the publications describing trends in physicochemical properties are written from a medicinal chemistry perspective with the aim to identify molecules with better ADMET profiles that are either lead-like or drug-like, failing to describe the impact these properties have on CMC development. To systematically uncover knowledge obtained from recent trends in physicochemical properties and the corresponding impact on CMC development, a comprehensive analysis was conducted on molecules in the drug repurposing hub dataset. The only physicochemical property that seems to have been preserved in FDA-approved oral molecules over the decades (1900-2020) is a constant H-bond donor count, highlighting the importance this property has on cell permeability and lattice energy. Pharmaceutical attrition analysis suggests that partition-distribution coefficient, H-bond acceptors, polar surface area and the fraction of sp³ carbons are properties that are associated with compound attrition. Looking at pharmaceutical attrition asynchronously with the temporal analysis of FDA-approved oral molecules highlights the opposing trends, risks and diminishing effects some of these physiochemical properties (cLogP, cLogD and Fsp3) have on describing compound attrition during the past decade. Trellising the dataset by target class suggests that certain formulation and drug delivery strategies can be anticipated or put into place based on target class of a molecule. For example, molecules binding to nuclear hormone receptors are amenable to lipid-based drug delivery systems with proven commercial success. Although the poor solubility of kinase inhibitors is a combination of hydrophobicity (due to aromaticity) required to bind to its target and high lattice energy (melting point), they are a challenging target class to formulate. The influence of drug targets on physicochemical properties and the temporal nature of these properties is highlighted when comparing molecules in the drug repurposing dataset to those developed at Amgen. An improved understanding of the impact of molecular properties on performance attributes can accelerate decisions and facilitate risk assessments during candidate selection and development.

Discovery solubility measurement and assessment of small molecules with drug development in mind

Solubility is a key physicochemical property for the success of any drug candidate. Although the methods used and their rationales for determining solubility are subject to project needs and stages along the drug discovery-drug development pipeline, an artificial boundary can exist at the discovery-development interface. This boundary results in less effective solubility knowledge sharing and data integration among scientists in both drug discovery and drug development. Herein, we present a refreshed perspective on solubility. Solubility experimentation is not a one-size-fits-all measurement; instead, we stress the importance of constructing a seamless solubility understanding of a molecule as it progresses from a new chemical entity into a drug product.

Interpreting the Physicochemical Meaning of a Molecular Descriptor Which Is Predictive of Amorphous Solid Dispersion Formation in Polyvinylpyrrolidone Vinyl Acetate

A molecular descriptor known as R3m (the R-GETAWAY third-order autocorrelation index weighted by the atomic mass) was previously identified as capable of grouping members of an 18-compound library of organic molecules that successfully formed amorphous solid dispersions (ASDs) when co-solidified with the co-polymer polyvinylpyrrolidone vinyl acetate (PVPva) at two concentrations using two preparation methods. To clarify the physical meaning of this descriptor, the R3m calculation is examined in the context of the physicochemical mechanisms of dispersion formation. The R3m equation explicitly captures information about molecular topology, atomic leverage, and molecular geometry, features which might be expected to affect the formation of stabilizing non-covalent interactions with a carrier polymer, as well as the molecular mobility of the active pharmaceutical ingredient (API) molecule. Molecules with larger R3m values tend to have more atoms, especially the heavier ones that form stronger non-covalent interactions, generally, more irregular shapes, and more complicated topology. Accordingly, these molecules are more likely to remain dispersed within PVPva. Furthermore, multiple linear regression modeling of R3m and more interpretable descriptors supported these conclusions. Finally, the utility of the R3m descriptor for predicting the formation of ASDs in PVPva was tested by analyzing the commercially available products that contain amorphous APIs dispersed in the same polymer. All of these analyses support the conclusion that the information about the API geometry, size, shape, and topological connectivity captured by R3m relates to the ability of a molecule to interact with and remain dispersed within an amorphous PVPva matrix.

Machine learning methods for prediction of food effects on bioavailability: A comparison of support vector machines and artificial neural networks

Despite countless advances in recent decades across various in vitro, in vivo and in silico tools, anticipation of whether a drug will show a human food effect (FE) remains challenging. One means to predict potential FE involves probing any dependence between FE and drug properties. Accordingly, this study explored the potential for two machine learning (ML) algorithms to predict likely FE. Using a collated database of drugs licensed from 2016-2020, drugs were classified into three groups; positive, negative or no FE. Greater than 250 drug properties were predicted for each drug which were used to train predictive models using Support Vector Machine (SVM) and Artificial Neural Network (ANN) algorithms. When compared, ANN outperformed SVM for FE classification upon training (82%, 72%) and testing (72%, 69%). Both models demonstrated higher FE prediction accuracy than the Biopharmaceutics Classification System (BCS) (46%). This exploratory work provided new insights into the connection between FE and drug properties as the Octanol Water Partition Coefficient (S+logP), Number of Hydrogen Bond Donors (HBD), Topological Polar Surface Area (T_PSA) and Dose (mg) were all significant for prediction. Overall, this study demonstrated the utility of ML to facilitate early anticipation of likely FE in pre-clinical development using four well-known drug properties.

Fast-Dissolving Solid Dispersions for the Controlled Release of Poorly Watersoluble Drugs

Solid dispersions offer many advantages for oral drug delivery of poorly water-soluble drugs over other systems, including an increase in drug solubility and drug dissolution. An improvement in drug absorption and the higher bioavailability of active pharmaceutical ingredients in the gastrointestinal tract have been reported in various studies. In certain circumstances, a rapid pharmacological effect is required for patients. Fastdissolving solid dispersions provide an ideal formulation in such cases. This report will provide an overview of current studies on fast-dissolving solid dispersions, including not only solid dispersion powders with fast dissolution rates but also specific dose form for the controlled release of poorly water-soluble drugs. Specifically, the applications of fast-dissolving solid dispersions will be described in every specific case. Moreover, pharmaceutical approaches and the utilization of polymers will be summarized. The classification and analysis of fastdissolving solid dispersions could provide insight into strategies and potential applications in future drug delivery developments.

Synergistic Computational Modeling Approaches as Team Players in the Game of Solubility Predictions

Several approaches to predict and model drug solubility have been used in the drug discovery and development processes during the last decades. Each of these approaches have their own benefits and place, and are typically used as standalone approaches rather than in concert. The synergistic effects of these are often overlooked, partly due to the need of computational experts to perform the modeling and simulations as well as analyzing the data obtained. Here we provide our views on how these different approaches can be used to retrieve more information on drug solubility, ranging from multivariate data analysis over thermodynamic cycle modeling to molecular dynamics simulations. We are discussing aqueous solubility as well as solubility in more complex mixed solvents and media with colloidal structures present. We conclude that the field of computational pharmaceutics is in its early days but with a bright future ahead. However, education of computational formulators with broad knowledge of modeling and simulation approaches is imperative if computational pharmaceutics is to reach its full potential.

Study on the stabilization mechanisms of wet-milled cepharanthine nanosuspensions using systematical characterization

Objectives: Stability issues are inevitable problems that are encountered in nanosuspension (NS) technology developments and in the industrial application of pharmaceuticals. This study aims to assess the stability of wet-milled cepharanthine NSs and elucidate the stabilization mechanisms of different stabilizers.Methods: The aggregation state was examined via scanning electron microscopy, laser diffraction, and rheometry. The zeta potential, stabilizer adsorption, surface tension, and drug-stabilizer interactions were employed to elucidate the stabilization mechanisms.Results: The results suggest that croscarmellose sodium (CCS), D-α-tocopherol polyethylene glycol 1000 succinate (TPGS), or polyvinyl pyrrolidone VA64 (PVP VA64) alone was able to prevent nanoparticle aggregation for at least 30 days. Attempts to evaluate the stability mechanisms of different stabilization systems revealed that CCS improved the steric-kinetic stabilization of the NSs, attributed to its high viscosity, swelling capacity, and physical barrier effects. In contrast, the excellent physical stability of TPGS systems was mainly due to the reduced surface tension and higher crystallinity. PVP VA64 can adsorb onto the surfaces of nanoparticles and stabilize the NS via steric forces.Conclusion: This study demonstrated the complex effects of CCS, TPGS, and PVP VA64 on cepharanthine NS stability and presented an approach for the rational design of stable NSs.

A Novel Rheological Method to Assess Drug-Polymer Interactions Regarding Miscibility and Crystallization of Drug in Amorphous Solid Dispersions for Oral Drug Delivery

Solid dispersions provide a key technology to formulate poorly water-soluble drugs, and a main task of early development is appropriate selection of polymer. This study investigates the use of a novel rheology-based approach to evaluate miscibility and interactions of drugs with polymers regarding amorphous solid drug dispersions for oral administration. Tacrolimus was used as model drug and hydroxypropyl cellulose, ethylcellulose, Soluplus^®, polyethyleneglycol 6000, Poloxamer-188 (Koliphor-188), and Eudragit^® S100 were used as excipients. Solvent-based evaporation methods were used to prepare binary solid dispersions of drug and polymer. Data of the dilute solution viscosimetry were compared with in silico calculations of the Hansen solubility parameter (HSP), as well as phase separation/crystallization data obtained from X-ray diffraction and differential scanning calorimetry. HSP calculations in some cases led to false positive predictions of tacrolimus miscibility with the tested polymers. The novel rheology-based method provided valuable insights into drug-polymer interactions and likely miscibility with polymer. It is a rather fast, inexpensive, and robust analytical approach, which could be used complementary to in silico-based evaluation of polymers in early formulation development, especially in cases of rather large active pharmaceutical ingredients.

Lipophilicity and hydrophobicity considerations in bio-enabling oral formulations approaches – a PEARRL review

Objectives

This review highlights aspects of drug hydrophobicity and lipophilicity as determinants of different oral formulation approaches with specific focus on enabling formulation technologies. An overview is provided on appropriate formulation selection by focussing on the physicochemical properties of the drug.

Key findings

Crystal lattice energy and the octanol–water partitioning behaviour of a poorly soluble drug are conventionally viewed as characteristics of hydrophobicity and lipophilicity, which matter particularly for any dissolution process during manufacturing and regarding drug release in the gastrointestinal tract. Different oral formulation strategies are discussed in the present review, including lipid-based delivery, amorphous solid dispersions, mesoporous silica, nanosuspensions and cyclodextrin formulations.

Summary

Current literature suggests that selection of formulation approaches in pharmaceutics is still highly dependent on the availability of technological expertise in a company or research group. Encouraging is that, recent advancements point to more structured and scientifically based development approaches. More research is still needed to better link physicochemical drug properties to pharmaceutical formulation design.

The Application of Modeling and Prediction to the Formation and Stability of Amorphous Solid Dispersions

Amorphous solid dispersion (ASD) formulation development is frequently difficult owing to the inherent physical instability of the amorphous form, and limited understanding of the physical and chemical interactions that translate to initial dispersion formation and long-term physical stability. Formulation development for ASDs has been historically accomplished through trial and error or experience with extant systems; however, rational selection of appropriate excipients is preferred to reduce time to market and decrease costs associated with development. Current efforts to develop thermodynamic and computational models attempt to rationally direct formulation and show promise. This review compiles and evaluates important methods used to predict ASD formation and physical stability. Recent literature in which these methods are applied is also reviewed, and limitations of each method are discussed.

Toward an improved understanding of the precipitation behavior of weakly basic drugs from oral lipid-based formulations

The aim of the present study was to analyze the impact of lipid-based formulation (LBF) dispersion and digestion on the precipitation behavior of weakly basic drugs. Loratadine and carvedilol were formulated in a range of LBFs and drug solubilization was analyzed under simulated dispersive and digestive conditions (fasted state). The extent of supersaturation and drug precipitation as well as the solid-state properties and redissolution behavior of precipitated drugs were assessed. X-ray powder diffraction indicated that carvedilol precipitated in a crystalline form upon dispersion, but interestingly, this drug gave an amorphous precipitate during lipolysis. In contrast, loratadine precipitated as crystalline material during both formulation dispersion and digestion. No influence of the formulation composition on the type of precipitation was observed. These results suggested that in vitro conditions (dispersive versus digestive) largely influenced the solid-state properties of precipitating weak bases. Solid-state characterization of precipitated drugs under different experimental conditions should be routinely performed in formulation screening to better understand the biopharmaceutical behavior of LBFs. Hence, these findings are of high practical importance for the pharmaceutical development and in vitro assessment of LBFs using weakly basic drugs.