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

Amorphous solid dispersion of a binary formulation with felodipine and HPMC for 3D printed floating tablets

This study focuses on the combination of three-dimensional printing (3DP) and amorphous solid dispersion (ASD) technologies for the manufacturing of gastroretentive floating tablets. Employing hot melt extrusion (HME) and fused deposition modeling (FDM), the study investigates the development of drug-loaded filaments and 3D printed (3DP) tablets containing felodipine as model drug and hydroxypropyl methylcellulose (HPMC) as the polymeric carrier. Prior to fabrication, solubility parameter estimation and molecular dynamics simulations were applied to predict drug-polymer interactions, which are crucial for ASD formation. Physical bulk and surface characterization complemented the quality control of both drug-loaded filaments and 3DP tablets. The analysis confirmed a successful amorphous dispersion of felodipine within the polymeric matrix. Furthermore, the low infill percentage and enclosed design of the 3DP tablet allowed for obtaining low-density systems. This structure resulted in buoyancy during the entire drug release process until a complete dissolution of the 3DP tablets (more than 8 h) was attained. The particular design made it possible for a single polymer to achieve a zero-order controlled release of the drug, which is considered the ideal kinetics for a gastroretentive system. Accordingly, this study can be seen as an advancement in ASD formulation for 3DP technology within pharmaceutics.

Stability Challenges of Amorphous Solid Dispersions of Drugs: A Critical Review on Mechanistic Aspects

The most common drawback of the existing and novel drug molecules is their low bioavailability because of their low solubility. One of the most important approaches to enhance the bioavailability in the enteral route for poorly hydrophilic molecules is amorphous solid dispersion (ASD). The solubility of compounds in amorphous form is comparatively high because of the availability of free energy produced during formulation. This free energy results in the change of crystalline nature of the prepared ASD to the stable crystalline form leading to the reduced solubility of the product. Due to the intrinsic chemical and physical uncertainty and the restricted knowledge about the interactions of active molecules with the carriers making, this ASD is a challenging task. This review focused on strategies to stabilize ASD by considering the various theories explaining the free-energy concept, physical interactions, and thermal properties. This review also highlighted molecular modeling and machine learning computational advancement to stabilize ASD.

Molecular Dynamics Simulations of Selected Amorphous Stilbenoids and Their Amorphous Solid Dispersions with Poly(Vinylpyrrolidone)

Amorphous solid dispersions (ASDs) are one of the promising strategies to improve the solubility and dissolution rate of poorly soluble compounds. In this study, Molecular Dynamics simulations were used to investigate the interactions between three selected stilbenoids with important biological activity (resveratrol, pinostilbene and pterostilbene) and poly(vinylpyrrolidone). The analysis of the pair distribution functions and hydrogen bond distributions reveals a significant weakening of the hydrogen bond network of the stilbenoids in ASDs compared to the pure (no polymer) amorphous systems. This is accompanied by an increase in the mobility of the stilbenoid molecules in the ASDs, both in the translational dynamics determined from the molecular mean square displacements, and in the molecular reorientations followed by analysing several torsional distributions.

Can Pure Predictions of Activity Coefficients from PC-SAFT Assist Drug-Polymer Compatibility Screening?

The bioavailability of poorly water-soluble active pharmaceutical ingredients (APIs) can be improved via the formulation of an amorphous solid dispersion (ASD), where the API is incorporated into a suitable polymeric carrier. Optimal carriers that exhibit good compatibility (i.e., solubility and miscibility) with given APIs are typically identified through experimental means, which are routinely labor- and cost-inefficient. Therefore, the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state, a popular thermodynamic model in pharmaceutical applications, is examined in terms of its performance regarding the computational pure prediction of API-polymer compatibility based on activity coefficients (API fusion properties were taken from experiments) without any binary interaction parameters fitted to API-polymer experimental data (that is, kij = 0 in all cases). This kind of prediction does not need any experimental binary information and has been underreported in the literature so far, as the routine modeling strategy used in the majority of the existing PC-SAFT applications to ASDs comprised the use of nonzero kij values. The predictive performance of PC-SAFT was systematically and thoroughly evaluated against reliable experimental data for almost 40 API-polymer combinations. We also examined the effect of different sets of PC-SAFT parameters for APIs on compatibility predictions. Quantitatively, the total average error calculated over all systems was approximately 50% in the weight fraction solubility of APIs in polymers, regardless of the specific API parametrization. The magnitude of the error for individual systems was found to vary significantly from one system to another. Interestingly, the poorest results were obtained for systems with self-associating polymers such as poly(vinyl alcohol). Such polymers can form intramolecular hydrogen bonds, which are not accounted for in the PC-SAFT variant routinely applied to ASDs (i.e., that used in this work). However, the qualitative ranking of polymers with respect to their compatibility with a given API was reasonably predicted in many cases. It was also predicted correctly that some polymers always have better compatibility with the APIs than others. Finally, possible future routes to improve the cost-performance ratio of PC-SAFT in terms of parametrization are discussed.

Investigating and Comparing the Applicability of the R3m Molecular Descriptor and Solubility Parameter Estimation Approaches in Predicting Dispersion Formation Potential of APIs in a Random Co-Polymer Polyvinylpyrrolidone Vinyl Acetate and its Homopolymer

Evaluation of different amorphous solid dispersion carrier matrices is enabled by active pharmaceutical ingredient (API) structure-based predictions. This study compares the utility of Hansen Solubility Parameters with the R3m molecular descriptor for identifying dispersion polymers based on the structure of the drug molecule. Twelve API-polymer combinations (4 APIs and 3 interrelated polymers) were used to test each approach. Co-solidified mixtures containing 75% API were prepared by melt-quenching. Phase behavior was evaluated and classified using differential scanning calorimetry, powder X-ray diffraction, polarized light microscopy, and hot stage microscopy. Observations of dispersion behavior were compared to predictions made using the Hansen Solubility Parameter and R3m. The solubility parameter approach misclassified the dispersion behavior of 1 API-polymer combination and also did not produce definite predictions in 3 out of 12 of the API-polymer combinations. In contrast, R3m classifications of dispersion behavior were correct in all but two cases, with one misclassification and one ambiguous prediction. The solubility parameters best classify dispersion behavior when specific drug-polymer intermolecular interactions are present, but may be less useful otherwise. Ultimately, these two methods are most effectively used together, as they are based on distinct features of the same molecular structure.

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.

Continuous Manufacturing and Molecular Modeling of Pharmaceutical Amorphous Solid Dispersions

Amorphous solid dispersions enhance solubility and oral bioavailability of poorly water-soluble drugs. The escalating number of drugs with poor aqueous solubility, poor dissolution, and poor oral bioavailability is an unresolved problem that requires adequate interventions. This review article highlights recent solubility and bioavailability enhancement advances using amorphous solid dispersions (ASDs). The review also highlights the mechanism of enhanced dissolution and the challenges faced by ASD-based products, such as stability and scale-up. The role of process analytical technology (PAT) supporting continuous manufacturing is highlighted. Accurately predicting interactions between the drug and polymeric carrier requires long experimental screening methods, and this is a space where computational tools hold significant potential. Recent advancements in data science, computational tools, and easy access to high-end computation power are set to accelerate ASD-based research. Hence, particular emphasis has been given to molecular modeling techniques that can address some of the unsolved questions related to ASDs. With the advancement in PAT tools and artificial intelligence, there is an increasing interest in the continuous manufacturing of pharmaceuticals. ASDs are a suitable option for continuous manufacturing, as production of a drug product from an ASD by direct compression is a reality, where the addition of multiple excipients is easy to avoid. Significant attention is necessary for ongoing clinical studies based on ASDs, which is paving the way for the approval of many new ASDs and their introduction into the market.

Amorphous Solid Dispersions: Role of the Polymer and Its Importance in Physical Stability and In Vitro Performance

Amorphous solid dispersions stabilized by one or more polymer(s) have been widely used for delivering amorphous drugs with poor water solubilities, and they have gained great market success. Polymer selection is important for preparing robust amorphous solid dispersions, and considerations should be given as to how the critical attributes of a polymer can enhance the physical stability, and the in vitro and in vivo performances of a drug. This article provides a comprehensive overview for recent developments in the understanding the role of polymers in amorphous solid dispersions from the aspects of nucleation, crystal growth, overall crystallization, miscibility, phase separation, dissolution, and supersaturation. The critical properties of polymers affecting the physical stability and the in vitro performance of amorphous solid dispersions are also highlighted. Moreover, a perspective regarding the current research gaps and novel research directions for better understanding the role of the polymer is provided. This review will provide guidance for the rational design of polymer-based amorphous pharmaceutical solids with desired physicochemical properties from the perspective of physical stability and in vitro performance.

Recent advances in versatile inverse lyotropic liquid crystals

Owing to the rapid and significant progress in advanced materials and life sciences, nanotechnology is increasingly gaining in popularity. Among numerous bio-mimicking carriers, inverse lyotropic liquid crystals are known for their unique properties. These carriers make accommodation of molecules with varied characteristics achievable due to their complicated topologies. Besides, versatile symmetries of inverse LCNPs (lyotropic crystalline nanoparticles) and their aggregating bulk phases allow them to be applied in a wide range of fields including drug delivery, food, cosmetics, material sciences etc. In this review, in-depth summary, discussion and outlook for inverse lyotropic liquid crystals are provided.

Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives

Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for rationalizing drug interactions with their pharmacological targets. Despite the obvious utility and increasing impact of computational approaches, their development is not progressing at the same speed in different fields of pharmacology. Here, we review current in silico techniques used in cardiovascular diseases (CVDs), cardiological drug discovery, and assessment of cardiotoxicity. In silico techniques are paving the way to a new era in cardiovascular medicine, but their use somewhat lags behind that in other fields.

Analytical and Computational Methods for the Determination of Drug-Polymer Solubility and Miscibility

In the pharmaceutical industry, poorly water-soluble drugs require enabling technologies to increase apparent solubility in the biological environment. Amorphous solid dispersion (ASD) has emerged as an attractive strategy that has been used to market more than 20 oral pharmaceutical products. The amorphous form is inherently unstable and exhibits phase separation and crystallization during shelf life storage. Polymers stabilize the amorphous drug by antiplasticization, reducing molecular mobility, reducing chemical potential of drug, and increasing glass transition temperature in ASD. Here, drug-polymer miscibility is an important contributor to the physical stability of ASDs. The current Review discusses the basics of drug-polymer interactions with the major focus on the methods for the evaluation of solubility and miscibility of the drug in the polymer. Methods for the evaluation of drug-polymer solubility and miscibility have been classified as thermal, spectroscopic, microscopic, solid-liquid equilibrium-based, rheological, and computational methods. Thermal methods have been commonly used to determine the solubility of the drug in the polymer, while other methods provide qualitative information about drug-polymer miscibility. Despite advancements, the majority of these methods are still inadequate to provide the value of drug-polymer miscibility at room temperature. There is still a need for methods that can accurately determine drug-polymer miscibility at pharmaceutically relevant temperatures.

Additives-directed lyotropic liquid crystals architecture: Simulations and experiments

In this study, alkanes and sucrose esters are employed to investigate the influence of additives on lyotropic liquid crystal architecture. After molecular dynamic simulations and experiment characterization, we showed how the additives control the structure of LLCs. By controlling the polarity of additives, the phase behavior of LLCs can be engineered to form the required structure. Dissipative particle dynamics (DPD) is introduced for simulating the self-assembly of phytantriol (PT), providing intuitionistic images and structure information, which shows that additives with low-polarity complicate the internal structure of liquid crystal systems. Then the ternary phase diagrams of additives, PT, and water are constructed to systematically study the effects of additives on the phase behavior of LLCs. Consistent with DPD simulation results, there is a certain regularity in the effects of additives on the structure of liquid crystals. The difference in the structure of LLCs is due to the variability in the critical packing parameter (CPP) obtained by changing the polarity of additives. Our findings demonstrate that additives polarity is a key factor in LLCs structure, and may pave a promising avenue for novel LLCs development and translation, determining the self-assembly process and the resulting phase of LLCs.

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.

Stabilization mechanism of amorphous carbamazepine by transglycosylated rutin, a non-polymeric amorphous additive with a high glass transition temperature

α-Glycosyl rutin (Rutin-G), composed of a flavonol skeleton and sugar groups, is a promising non-polymeric additive for stabilizing amorphous drug formulations. In this study, the mechanism of the stabilization of the amorphous state of carbamazepine (CBZ) by Rutin-G was investigated. In comparison with hypromellose (HPMC), which is commonly used as a crystallization inhibitor for amorphous drugs, Rutin-G significantly stabilized amorphous CBZ. Moreover, the dissolution rate and the resultant supersaturation level of CBZ were significantly improved in the CBZ/Rutin-G spray-dried samples (SPDs) owing to the rapid dissolution property of Rutin-G. Differential scanning calorimetry measurement demonstrated a high glass transition temperature (T_g) of 186.4°C corresponding to Rutin-G. The CBZ/Rutin-G SPDs with CBZ weight ratios up to 80% showed single glass transitions, indicating the homogeneity of CBZ and Rutin-G. A solid-state NMR experiment using ¹³C- and ¹⁵N-labeled CBZ demonstrated the interaction between the flavonol skeleton of Rutin-G and the amide group of CBZ. A ¹H-¹³C two-dimensional heteronuclear correlation NMR experiment and quantum mechanical calculations confirmed the presence of a possible hydrogen bond between the amino proton in CBZ and the carbonyl oxygen in the flavonol skeleton of Rutin-G. This specific hydrogen bond could contribute to the strong interaction between CBZ and Rutin-G, resulting in the high stability of amorphous CBZ in the CBZ/Rutin-G SPD. Hence, Rutin-G, a non-polymeric amorphous additive with high T_g, high miscibility with drugs, and rapid and pH-independent dissolution properties could be useful in the preparation of amorphous formulations.

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.

Multiple approaches for achieving drug solubility: an in silico perspective

Discovering new therapeutically active molecules is the ultimate destination in pharmaceutical research and development. Most drugs discovered are lipophilic and, hence, exhibit poor aqueous solubility, resulting in low bioavailability. Thus, there is a need to use various solubility enhancement techniques. Computational approaches enable the analysis of drug-carrier interactions or the numerous conformational changes in the carrier matrix that might establish an appropriate balance between cohesive and adhesive stability in a formulation. In this review, we discuss research approaches that provided molecular insight into drugs and their modifiers to unravel their solubility, stability, and bioavailability.

Myth or Truth: The Glass Forming Ability Class III Drugs Will Always Form Single-Phase Homogenous Amorphous Solid Dispersion Formulations

The physical stability of amorphous solid dispersions (ASD) of active pharmaceutical ingredients (APIs) of high glass forming ability (GFA class III) is generally expected to be high among the scientific community. In this study, the ASD of ten-selected class III APIs with the two polymers, PVPVA 64 and HPMC-E5, have been prepared by spray-drying, film-casting, and their amorphicity at T0 was investigated by modulated differential scanning calorimetry and powder X-ray diffraction. It was witnessed that only five out of ten APIs form good quality amorphous solid dispersions with no phase separation and zero crystalline content, immediately after the preparation and drying process. Hence, it was further established that the classification of an API as GFA class III does not guarantee the formulation of single phase amorphous solid dispersions.

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.

Molecular simulation as a computational pharmaceutics tool to predict drug solubility, solubilization processes and partitioning

In this review we will discuss how computational methods, and in particular classical molecular dynamics simulations, can be used to calculate solubility of pharmaceutically relevant molecules and systems. To the extent possible, we focus on the non-technical details of these calculations, and try to show also the added value of a more thorough and detailed understanding of the solubilization process obtained by using computational simulations. Although the main focus is on classical molecular dynamics simulations, we also provide the reader with some insights into other computational techniques, such as the COSMO-method, and also discuss Flory-Huggins theory and solubility parameters. We hope that this review will serve as a valuable starting point for any pharmaceutical researcher, who has not yet fully explored the possibilities offered by computational approaches to solubility calculations.

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.

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.