Molecular dynamics simulation of amorphous hydroxypropyl-methylcellulose acetate succinate (HPMCAS): polymer model development, water distribution, and plasticization

Niosomes: a novel targeted drug delivery system for cancer

Recently, nanotechnology is involved in various fields of science, of which medicine is one of the most obvious. The use of nanoparticles in the process of treating and diagnosing diseases has created a novel way of therapeutic strategies with effective mechanisms of action. Also, due to the remarkable progress of personalized medicine, the effort is to reduce the side effects of treatment paths as much as possible and to provide targeted treatments. Therefore, the targeted delivery of drugs is important in different diseases, especially in patients who receive combined drugs, because the delivery of different drug structures requires different systems so that there is no change in the drug and its effectiveness. Niosomes are polymeric nanoparticles that show favorable characteristics in drug delivery. In addition to biocompatibility and high absorption, these nanoparticles also provide the possibility of reducing the drug dosage and targeting the release of drugs, as well as the delivery of both hydrophilic and lipophilic drugs by Niosome vesicles. Since various factors such as components, preparation, and optimization methods are effective in the size and formation of niosomal structures, in this review, the characteristics related to niosome vesicles were first examined and then the in silico tools for designing, prediction, and optimization were explained. Finally, anticancer drugs delivered by niosomes were compared and discussed to be a suitable model for designing therapeutic strategies. In this research, it has been tried to examine all the aspects required for drug delivery engineering using niosomes and finally, by presenting clinical examples of the use of these nanocarriers in cancer, its clinical characteristics were also expressed.

Emerging Landscape of Computational Modeling in Pharmaceutical Development

Computational chemistry applications have become an integral part of the drug discovery workflow over the past 35 years. However, computational modeling in support of drug development has remained a relatively uncharted territory for a significant part of both academic and industrial communities. This review considers the computational modeling workflows for three key components of drug preclinical and clinical development, namely, process chemistry, analytical research and development, as well as drug product and formulation development. An overview of the computational support for each step of the respective workflows is presented. Additionally, in context of solid form design, special consideration is given to modern physics-based virtual screening methods. This covers rational approaches to polymorph, coformer, counterion, and solvent virtual screening in support of solid form selection and design.

Pharmaceutical profiling and molecular dynamics simulations reveal crystallization effects in amorphous formulations

Robust and reliable in vivo performance of medicines based on amorphous solid dispersions (ASDs) depend on maintenance of physical stability and efficient supersaturation. However, molecular drivers of these two kinetic processes are poorly understood. Here we used molecular dynamics (MD) simulations coupled with experimental assessments to explore supersaturation, nucleation, and crystal growth. The effect of drug loading on physical stability and supersaturation potential was highly drug specific. Storage under humid conditions influenced crystallization, but also resulted in morphological changes and particle fusion. This led to increased particle size, which significantly reduced dissolution rate. MD simulations identified the importance of nano-compartmentalization in the crystallization rate of the ASDs. Nucleation during storage did not inherently compromise the ASD. Rather, the poorer performance resulted from a combination of properties of the compound, nanostructures formed in the formulation, and crystallization.

Water Dissolved in a Variety of Polymers Studied by Molecular Dynamics Simulation and a Theory of Solutions

The performance of a polymer medium as a separation membrane is determined by the dissolution free energy ΔG and diffusion coefficient D of the permeant. In this work, ΔG and D of water are investigated with all-atom molecular dynamics simulation in a wide variety of polymer species in the amorphous state. The computed ΔG is shown to agree well with the experimental value for linear homopolymers, and the degrees of polymerization of the homopolymers do not affect ΔG when they are beyond ∼10. The copolymers of ethylene-vinylidene difluoride, ethylene-vinyl acetate, and ethylene-acrylamide are then examined by changing the repeating patterns of the constituent monomers in both the periodic and graft forms. It is found that ΔG is determined primarily by the overall compositions of the monomers and is not affected by the copolymerization topology (periodic or graft). The hydrophobicity of the copolymer is enhanced, furthermore, when the hydrophobicity and hydrophilicity of the ethylene and non-ethylene parts are well contrasted and those parts are fragmented along the polymer chain. According to the computed D, the diffusivity of water tends to be larger when the (co)polymer is more hydrophobic and ΔG is more positive. D is actually seen to vary by orders of magnitude with the polymer structures, while the effect of the polymer species on the water permeation is stronger for ΔG than for D.

Automation and data-driven design of polymer therapeutics

Polymers are uniquely suited for drug delivery and biomaterial applications due to tunable structural parameters such as length, composition, architecture, and valency. To facilitate designs, researchers may explore combinatorial libraries in a high throughput fashion to correlate structure to function. However, traditional polymerization reactions including controlled living radical polymerization (CLRP) and ring-opening polymerization (ROP) require inert reaction conditions and extensive expertise to implement. With the advent of air-tolerance and automation, several polymerization techniques are now compatible with well plates and can be carried out at the benchtop, making high throughput synthesis and high throughput screening (HTS) possible. To avoid HTS pitfalls often described as "fishing expeditions," it is crucial to employ intelligent and big data approaches to maximize experimental efficiency. This is where the disruptive technologies of machine learning (ML) and artificial intelligence (AI) will likely play a role. In fact, ML and AI are already impacting small molecule drug discovery and showing signs of emerging in drug delivery. In this review, we present state-of-the-art research in drug delivery, gene delivery, antimicrobial polymers, and bioactive polymers alongside data-driven developments in drug design and organic synthesis. From this insight, important lessons are revealed for the polymer therapeutics community including the value of a closed loop design-build-test-learn workflow. This is an exciting time as researchers will gain the ability to fully explore the polymer structural landscape and establish quantitative structure-property relationships (QSPRs) with biological significance.

Molecular Simulation and Statistical Learning Methods toward Predicting Drug-Polymer Amorphous Solid Dispersion Miscibility, Stability, and Formulation Design

Amorphous solid dispersions (ASDs) have emerged as widespread formulations for drug delivery of poorly soluble active pharmaceutical ingredients (APIs). Predicting the API solubility with various carriers in the API-carrier mixture and the principal API-carrier non-bonding interactions are critical factors for rational drug development and formulation decisions. Experimental determination of these interactions, solubility, and dissolution mechanisms is time-consuming, costly, and reliant on trial and error. To that end, molecular modeling has been applied to simulate ASD properties and mechanisms. Quantum mechanical methods elucidate the strength of API-carrier non-bonding interactions, while molecular dynamics simulations model and predict ASD physical stability, solubility, and dissolution mechanisms. Statistical learning models have been recently applied to the prediction of a variety of drug formulation properties and show immense potential for continued application in the understanding and prediction of ASD solubility. Continued theoretical progress and computational applications will accelerate lead compound development before clinical trials. This article reviews in silico research for the rational formulation design of low-solubility drugs. Pertinent theoretical groundwork is presented, modeling applications and limitations are discussed, and the prospective clinical benefits of accelerated ASD formulation are envisioned.

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

Using Acetone/Water Binary Solvent to Enhance the Stability and Bioavailability of Spray Dried Enzalutamide/HPMC-AS Solid Dispersions

We demonstrated a facile approach, by adjusting the solvent ratio of water/acetone binary mixture, to alter the intermolecular interactions between Enzalutamide (ENZ) and hydroxypropyl methylcellulose acetate succinate (HPMC-AS) for spray drying process, which can be readily implemented to produce spray-dried dispersions (SDD) with enhanced stability and bioavailability. The prepared SDD of ENZ/HPMC-AS were examined systematically in terms of particle size, morphology, dissolution, solubility, stability, and bioavailability. Our results show that the introduction of water (up to 30% volume fraction) can effectively reduce the hydrodynamic diameter of HPMC-AS from approximately 220 nm to 160 nm (a reduction of c.a. 20%), which increases the miscibility of the drug and polymer, delaying or inhibiting the crystallization of ENZ during the spray drying process, resulting in a homogeneous amorphous phase. The benefits of using acetone/water binary mixture were subsequently evidenced by an increased specific surface area, improved dissolution profile and relative bioavailability, enhanced stability, and elevated drug release rate. This fundamental finding underpins the great potential of using binary mixture for spray drying process to process active pharmaceutical ingredients (APIs) that are otherwise challenging to handle.

Evaluation of the Physico-mechanical Properties and Electrostatic Charging Behavior of Different Capsule Types for Inhalation Under Distinct Environmental Conditions

Capsule-based dry powder inhaler (DPI) products can be influenced by a multitude of interacting factors, including electrostatic charging. Tribo-charging is a process of charge transfer impacted by various factors, i.e., material surface characteristics, mechanical properties, processing parameters and environmental conditions. Consequently, this work aimed to assess how the charging behavior of capsules intended for inhalation might be influenced by environmental conditions. Capsules having different chemical compositions (gelatin and hydroxypropyl methylcellulose (HPMC)) and distinct inherent characteristics from manufacturing (thermally and cold-gelled) were exposed to various environmental conditions (11%, 22% and 51% RH). Their resulting properties were characterized and tribo-charging behavior was measured against stainless steel and PVC. It was observed that all capsule materials tended to charge to a higher extent when in contact with PVC. The tribo-charging of the thermally gelled HPMC capsules (Vcaps^® Plus) was more similar to the gelatin capsules (Quali-G™-I) than to their HPMC cold-gelled counterparts (Quali-V^®-I). The sorption of water by the capsules at different relative humidities notably impacted their properties and tribo-charging behavior. Different interactions between the tested materials and water molecules were identified and are proposed to be the driver of distinct charging behaviors. Finally, we showed that depending on the capsule types, distinct environmental conditions are necessary to mitigate charging and assure optimal behavior of the capsules.

Recent Advances in Understanding the Micro- and Nanoscale Phenomena of Amorphous Solid Dispersions

Many pharmaceutical drugs in the marketplace and discovery pipeline suffer from poor aqueous solubility, thereby limiting their effectiveness for oral delivery. The use of an amorphous solid dispersion (ASD), a mixture of an active pharmaceutical ingredient and a polymer excipient, greatly enhances the aqueous dissolution performance of a drug without the need for chemical modification. Although this method is versatile and scalable, deficient understanding of the interactions between drugs and polymers inhibits ASD rational design. This current Review details recent progress in understanding the mechanisms that control ASD performance. In the solid-state, the use of high-resolution theoretical, computational, and experimental tools resolved the influence of drug/polymer phase behavior and dynamics on stability during storage. During dissolution in aqueous media, novel characterization methods revealed that ASDs can form complex nanostructures, which maintain and improve supersaturation of the drug. The studies discussed here illustrate that nanoscale phenomena, which have been directly observed and quantified, strongly affect the stability and bioavailability of ASD systems, and provide a promising direction for optimizing drug/polymer formulations.

Predicting physical stability of solid dispersions by machine learning techniques

Amorphous solid dispersion (SD) is an effective solubilization technique for water-insoluble drugs. However, physical stability issue of solid dispersions still heavily hindered the development of this technique. Traditional stability experiments need to be tested at least three to six months, which is time-consuming and unpredictable. In this research, a novel prediction model for physical stability of solid dispersion formulations was developed by machine learning techniques. 646 stability data points were collected and described by over 20 molecular descriptors. All data was classified into the training set (60%), validation set (20%), and testing set (20%) by the improved maximum dissimilarity algorithm (MD-FIS). Eight machine learning approaches were compared and random forest (RF) model achieved the best prediction accuracy (82.5%). Moreover, the RF models revealed the contribution of each input parameter, which provided us the theoretical guidance for solid dispersion formulations. Furthermore, the prediction model was confirmed by physical stability experiments of 17β-estradiol (ED)-PVP solid dispersions and the molecular mechanism was investigated by molecular modeling technique. In conclusion, an intelligent model was developed for the prediction of physical stability of solid dispersions, which benefit the rational formulation design of this technique. The integrated experimental, theoretical, modeling and data-driven AI methodology is also able to be used for future formulation development of other dosage forms.

Successful oral delivery of poorly water-soluble drugs both depends on the intraluminal behavior of drugs and of appropriate advanced drug delivery systems

Poorly water-soluble drugs continue to be a problematic, yet important class of pharmaceutical compounds for treatment of a wide range of diseases. Their prevalence in discovery is still high, and their development is usually limited by our lack of a complete understanding of how the complex chemical, physiological and biochemical processes that occur between administration and absorption individually and together impact on bioavailability. This review defines the challenge presented by these drugs, outlines contemporary strategies to solve this challenge, and consequent in silico and in vitro evaluation of the delivery technologies for poorly water-soluble drugs. The next steps and unmet needs are proposed to present a roadmap for future studies for the field to consider enabling progress in delivery of poorly water-soluble compounds.

Fluoroquinolone Amorphous Polymeric Salts and Dispersions for Veterinary Uses

Enrofloxacin (ENRO) is a poorly soluble drug used in veterinary medicine. It differs from the more widely used fluoroquinolone ciprofloxacin (CIP) by the presence of an ethyl substituent on its piperazine amino group. While a number of recent studies have examined amorphous composite formulations of CIP, little research has been conducted with ENRO in this area. Therefore, the main purpose of this work was to produce amorphous solid dispersions (ASDs) of ENRO. The solid-state properties of these samples were investigated and compared to those of the equivalent CIP ASDs, and their water uptake behavior, solubility, dissolution, and antibacterial activity were assessed. Like CIP, X-ray amorphous solid dispersions were obtained when ENRO was ball milled with acidic polymers, whereas the use of neutral polymers resulted in semi-crystalline products. Proton transfer from the carboxylic acids of the polymers to the tertiary amine of ENRO’s piperazine group appears to occur in the ASDs, resulting in an ionic bond between the two components. Therefore, these ASDs can be referred to as amorphous polymeric salts (APSs). The glass transition temperatures of the APSs were significantly higher than that of ENRO, and they were also resistant to crystallization when exposed to high humidity levels. Greater concentrations were achieved with the APSs than the pure drug during solubility and dissolution studies, and this enhancement was sustained for the duration of the experiments. In addition, the antimicrobial activity of ENRO was not affected by APS formation, while the minimum inhibitory concentrations and minimum bactericidal concentrations obtained with the APS containing hydroxypropyl methylcellulose acetate succinate grade MG (HPMCAS-MG) were significantly lower than those of the pure drug. Therefore, APS formation is one method of improving the pharmaceutical properties of this drug.

Investigating molecular interactions of high-loaded glipizide-HPMCAS microparticles by integrated experimental and modeling techniques

Molecular interactions between drug and polymeric carriers are believed to be the key for high drug loading and better physical stability of micro-particles. However, molecular interactions between drug and polymer are still difficult to investigate using only experimental tools. In this study, high-loaded glipizide (GLP)/hydroxypropyl methylcellulose acetate succinate (HPMCAS) (1/1 w/w) micro-particles were prepared using an in situ pH-dependent solubility method. Molecular interactions within the micro-particles were investigated by integrated experimental and modeling techniques. The dissolution rate of GLP/HPMCAS micro-particles was significantly better than those of solid dispersions and physical mixtures. Scanning electron microscopy images showed that the polymer inhibited GLP recrystallization. Experimental (FTIR spectroscopy, differential scanning calorimetry, powder X-ray diffraction and nuclear magnetic resonance spectroscopy) and molecular dynamics simulation revealed that hydrogen-bonding was the key to the properties of the micro-particles. Our research developed high drug-loading GLP/HPMCAS micro-particles and investigated the interactions between drug and polymer at the molecular level. This integrated approach could be practical methodology for future formulation design.

Molecular modelling and simulation of fusion-based amorphous drug dispersions in polymer/plasticizer blends

A realistic molecular description of amorphous drug-polymer-plasticizer matrices, suitable for the preparation of amorphous solid dispersions (ASDs) with the aid of fusion-based techniques, was evaluated. Specifically, the incorporation of two model drugs (i.e. ibuprofen, IBU, and carbamazepine, CBZ) having substantially different thermal properties and glass forming ability, on the molecular representation of polyvinyl caprolactam-polyvinyl acetate-polyethylene glycol graft copolymer (SOL)/polyethylene glycol (PEG, working as a plasticizer) molecular and thermal properties were evaluated with the aid of classical molecular dynamics (MD) and docking simulations. Results showed good agreement between molecular modelling estimations and experimentally determined properties. Specifically, the computed T_g values that resulted from MD simulations for IBU-SOL/PEG and CBZ-SOL/PEG (53.8 and 54.2 °C, respectively) were in reasonable agreement with the corresponding values resulting from differential scanning calorimetry (DSC) measurements (49.8 and 50.1 °C), while both molecular modelling and experimental obtained results suggested miscibility among system components. Additionally, interactions between CBZ and SOL observed during MD simulations were verified by FTIR analysis, while MD simulations of the hydration process suggested strong molecular interactions between IBU-SOL and CBZ-SOL.

In Silico Screening for Solid Dispersions: The Trouble with Solubility Parameters and χFH

The problem of predicting small molecule-polymer compatibility is relevant to many areas of chemistry and pharmaceutical science but particularly drug delivery. Computational methods based on Hildebrand and Hansen solubility parameters, and the estimation of the Flory-Huggins parameter, χ, have proliferated across the literature. Focusing on the need to develop amorphous solid dispersions to improve the bioavailability of poorly soluble drug candidates, an innovative, high-throughput 2D printing method has been employed to rapidly assess the compatibility of 54 drug-polymer pairings (nine drug compounds in six polymers). In this study, the first systematic assessment of the in silico methods for this application, neither the solubility parameter approach nor the calculated χ, correctly predicted drug-polymer compatibility. The theoretical limitations of the solubility parameter approach are discussed and used to explain why this approach is fundamentally unsuitable for predicting polymer-drug interactions. Examination of the original sources describing the method for calculating χ shows that only the enthalpic contributions to the term have been included, and the corrective entropic term is absent. The development and application of new in silico techniques, that consider all parts of the free energy of mixing, are needed in order to usefully predict small molecule-polymer compatibility and to realize the ambition of a drug-polymer screening method.

Relative Contributions of Solubility and Mobility to the Stability of Amorphous Solid Dispersions of Poorly Soluble Drugs: A Molecular Dynamics Simulation Study

Amorphous solid dispersions are considered a promising formulation strategy for the oral delivery of poorly soluble drugs. The limiting factor for the applicability of this approach is the physical (in)stability of the amorphous phase in solid samples. Minimizing the risk of reduced shelf life for a new drug by establishing a suitable excipient/polymer-type from first principles would be desirable to accelerate formulation development. Here, we perform Molecular Dynamics simulations to determine properties of blends of eight different polymer–small molecule drug combinations for which stability data are available from a consistent set of literature data. We calculate thermodynamic factors (mixing energies) as well as mobilities (diffusion rates and roto-vibrational fluctuations). We find that either of the two factors, mobility and energetics, can determine the relative stability of the amorphous form for a given drug. Which factor is rate limiting depends on physico-chemical properties of the drug and the excipients/polymers. The methods outlined here can be readily employed for an in silico pre-screening of different excipients for a given drug to establish a qualitative ranking of the expected relative stabilities, thereby accelerating and streamlining formulation development.

Multiscale Computational Modeling of the Nanostructure of Solid Dispersions of Hydroxypropyl Methylcellulose Acetate Succinate (HPMCAS) and Phenytoin

We recently developed coarse-grained (CG) force fields for hydroxypropyl methylcellulose acetate succinate (HPMCAS) polymers and the model drug molecule phenytoin, and a continuum transport model to study the polymer-drug nanostructures presented during a dissolution test after solvation of solid dispersion particles. We model the polymer-drug interactions that contribute to suppression of drug aggregation, release, and crystal growth during the dissolution process, and we take these as indicators of polymer effectiveness. We find that the size and the intermolecular interaction strength of the functional group and the drug loading concentration are the major factors that impact the effectiveness of the polymeric excipient. The hydroxypropyl acetyl group is the most effective functional group, followed by the acetyl group, while the deprotonated succinyl group is the least effective functional group, except that the deprotonated succinyl group at the 6-position is very effective in slowing down the phenytoin crystal growth. Our simulation results thus suggest HPMCAS with higher acetyl and lower succinyl content is more effective in promoting phenytoin solubility in dissolution media, and polymers become less effective when drug loading becomes high (i.e., 50% of the mass of the polymer/drug solid dispersion), agreeing with previous experimental studies. In addition, our transport model indicates that the drug release time from a solid dispersion particle of 2 μm diameter is less than 10 min, correlating well with the experimental time scale for a typical dissolution profile to reach maximum peak concentration. Our modeling effort, therefore, provides new avenues to understand the dissolution behavior of complex HPMCAS-phenytoin solid dispersions and offers a new design tool to optimize the formulation. Moreover, the systematic and robust approach used in our computational models can be extended to other polymeric excipients and drug candidates.

Amorphous Polymeric Drug Salts as Ionic Solid Dispersion Forms of Ciprofloxacin

Ciprofloxacin (CIP) is a poorly soluble drug that also displays poor permeability. Attempts to improve the solubility of this drug to date have largely focused on the formation of crystalline salts and metal complexes. The aim of this study was to prepare amorphous solid dispersions (ASDs) by ball milling CIP with various polymers. Following examination of their solid state characteristics and physical stability, the solubility advantage of these ASDs was studied, and their permeability was investigated via parallel artificial membrane permeability assay (PAMPA). Finally, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the ASDs were compared to those of CIP. It was discovered that acidic polymers, such as Eudragit L100, Eudragit L100-55, Carbopol, and HPMCAS, were necessary for the amorphization of CIP. In each case, the positively charged secondary amine of CIP was found to interact with carboxylate groups in the polymers, forming amorphous polymeric drug salts. Although the ASDs began to crystallize within days under accelerated stability conditions, they remained fully X-ray amorphous following exposure to 90% RH at 25 °C, and demonstrated higher than predicted glass transition temperatures. The solubility of CIP in water and simulated intestinal fluid was also increased by all of the ASDs studied. Unlike a number of other solubility enhancing formulations, the ASDs did not decrease the permeability of the drug. Similarly, no decrease in antibiotic efficacy was observed, and significant improvements in the MIC and MBC of CIP were obtained with ASDs containing HPMCAS-LG and HPMCAS-MG. Therefore, ASDs may be a viable alternative for formulating CIP with improved solubility, bioavailability, and antimicrobial activity.

The Need for Restructuring the Disordered Science of Amorphous Drug Formulations

The alarming numbers of poorly soluble discovery compounds have centered the efforts towards finding strategies to improve the solubility. One of the attractive approaches to enhance solubility is via amorphization despite the stability issue associated with it. Although the number of amorphous-based research reports has increased tremendously after year 2000, little is known on the current research practice in designing amorphous formulation and how it has changed after the concept of solid dispersion was first introduced decades ago. In this review we try to answer the following questions: What model compounds and excipients have been used in amorphous-based research? How were these two components selected and prepared? What methods have been used to assess the performance of amorphous formulation? What methodology have evolved and/or been standardized since amorphous-based formulation was first introduced and to what extent have we embraced on new methods? Is the extent of research mirrored in the number of marketed amorphous drug products? We have summarized the history and evolution of amorphous formulation and discuss the current status of amorphous formulation-related research practice. We also explore the potential uses of old experimental methods and how they can be used in tandem with computational tools in designing amorphous formulation more efficiently than the traditional trial-and-error approach.

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.

Computational Modeling of Hydroxypropyl-Methylcellulose Acetate Succinate (HPMCAS) and Phenytoin Interactions: A Systematic Coarse-Graining Approach

We present coarse-grained (CG) force fields for hydroxypropyl-methylcellulose acetate succinate (HPMCAS) polymers and the drug molecule phenytoin using a bead/stiff spring model, with each bead representing a HPMCAS monomer or monomer side group (hydroxypropyl acetyl, acetyl, or succinyl) or a single phenytoin ring. We obtain the bonded and nonbonded interaction parameters in our CG model using the RDFs from atomistic simulations of short HPMCAS model oligomers (20-mer) and atomistic simulations of phenytoin molecules. The nonbonded interactions are modeled using a LJ 12-6 potential, with separate parameters for each monomer substitution type, which allows heterogeneous polymer chains to be modeled. The cross interaction terms between the polymer and phenytoin CG beads are obtained explicitly from atomistic level polymer-phenytoin simulations, rather than from mixing rules. We study the solvation behavior of 50-mer and 100-mer polymer chains and find chain-length-dependent aggregation. We also compare the phenytoin CG force field developed in this work with that in Mandal et al. (Soft Matter, 2016, 12, 8246-8255) and conclude both are suitable for studying the interaction between polymer and drug in solvated solid dispersion formulation, in the absence of drug crystallization. Finally, we present simulations of heterogeneous HPMCAS model polymer chains and phenytoin molecules. Polymer and drug form a complex in a short period of simulation time due to strong intermolecular interactions. Moreover, the protonated polymer chains are more effective than deprotonated ones in inhibiting the drug aggregation in the polymer-drug complex.

Molecular Dynamics Simulation of Amorphous Hydroxypropylmethylcellulose and Its Mixtures With Felodipine and Water

Understanding drug-polymer molecular interactions, their miscibility, supersaturation potential, and the effects of water uptake may be invaluable for selecting amorphous polymer dispersions that can maximize the oral bioavailability of poorly water-soluble drugs. Molecular dynamics simulations were performed using a model for hydroxypropylmethylcellulose (HPMC) resembling the substitution patterns found experimentally. HPMC at low and high water contents (0.9%-23.0% wt/wt) and mixtures with a hydrophobic drug, felodipine (FEL), were constructed. T_g values and densities after ∼30 ns aging at 298 K were close to published results. Except for hydrogen bonds (HBs) between the 5-O- and a 3-OH group in a neighboring repeat unit, HPMC oxygen atoms have a low HB probability (p < 0.1) perhaps due to shielding by surrounding substituents. Water molecules tend to be isolated at low water content while clusters were prevalent at ≥10.7% water. The Flory-Huggins FEL-HPMC interaction parameter (-0.20 ± 0.07) predicts complete miscibility at all HPMC compositions, in agreement with experiments. However, HBs between the FEL-N-H and HPMC favoring miscibility are disrupted with increasing water. Apparent diffusion coefficients versus water content were generated for water and FEL and a theory for the non-Einsteinian nature of water diffusion is proposed.

Computational prediction of formulation strategies for beyond-rule-of-5 compounds

The physicochemical properties of some contemporary drug candidates are moving towards higher molecular weight, and coincidentally also higher lipophilicity in the quest for biological selectivity and specificity. These physicochemical properties move the compounds towards beyond rule-of-5 (B-r-o-5) chemical space and often result in lower water solubility. For such B-r-o-5 compounds non-traditional delivery strategies (i.e. those other than conventional tablet and capsule formulations) typically are required to achieve adequate exposure after oral administration. In this review, we present the current status of computational tools for prediction of intestinal drug absorption, models for prediction of the most suitable formulation strategies for B-r-o-5 compounds and models to obtain an enhanced understanding of the interplay between drug, formulation and physiological environment. In silico models are able to identify the likely molecular basis for low solubility in physiologically relevant fluids such as gastric and intestinal fluids. With this baseline information, a formulation scientist can, at an early stage, evaluate different orally administered, enabling formulation strategies. Recent computational models have emerged that predict glass-forming ability and crystallisation tendency and therefore the potential utility of amorphous solid dispersion formulations. Further, computational models of loading capacity in lipids, and therefore the potential for formulation as a lipid-based formulation, are now available. Whilst such tools are useful for rapid identification of suitable formulation strategies, they do not reveal drug localisation and molecular interaction patterns between drug and excipients. For the latter, Molecular Dynamics simulations provide an insight into the interplay between drug, formulation and intestinal fluid. These different computational approaches are reviewed. Additionally, we analyse the molecular requirements of different targets, since these can provide an early signal that enabling formulation strategies will be required. Based on the analysis we conclude that computational biopharmaceutical profiling can be used to identify where non-conventional gateways, such as prediction of 'formulate-ability' during lead optimisation and early development stages, are important and may ultimately increase the number of orally tractable contemporary targets.