Tailoring the Barrier Properties of PLA: A State-of-the-Art Review for Food Packaging Applications

It is now well recognized that the production of petroleum-based packaging materials has created serious ecological problems for the environment due to their resistance to biodegradation. In this context, substantial research efforts have been made to promote the use of biodegradable films as sustainable alternatives to conventionally used packaging materials. Among several biopolymers, poly(lactide) (PLA) has found early application in the food industry thanks to its promising properties and is currently one of the most industrially produced bioplastics. However, more efforts are needed to enhance its performance and expand its applicability in this field, as packaging materials need to meet precise functional requirements such as suitable thermal, mechanical, and gas barrier properties. In particular, improving the mass transfer properties of materials to water vapor, oxygen, and/or carbon dioxide plays a very important role in maintaining food quality and safety, as the rate of typical food degradation reactions (i.e., oxidation, microbial development, and physical reactions) can be greatly reduced. Since most reviews dealing with the properties of PLA have mainly focused on strategies to improve its thermal and mechanical properties, this work aims to review relevant strategies to tailor the barrier properties of PLA-based materials, with the ultimate goal of providing a general guide for the design of PLA-based packaging materials with the desired mass transfer properties.

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.

Investigation of nanoparticle-polymer interaction in bio-based nanosilica-filled PLA/NR nanocomposites: molecular dynamics simulation

Molecular dynamics (MD) simulation, by employing the COMPASS force field, was utilized to investigate structural and thermal characteristics as well as interfacial interactions between components of nanocomposite consisting of poly(lactic acid) (PLA)/natural rubber (NR)/nanosilica, abbreviated as PSxN, where 1 ≤ x ≤ 7 and it represents the parts of SiO₂ nanoparticles added to the PLA/NR (PN) blend. Analysis of the obtained results including density (ρ), fractional free volume (FFV), glass transition temperature (T_g), interaction energy (E_interaction), and radial distribution function (RDF) of these nanocomposites was performed. Comparing E_interaction of nanocomposites with that of the PN blend showed that the interactions between the chains of the two polymers are highly dependent on the added amounts of silica nanoparticles, so that by adding silica to the PN blend to obtain PS1N and PS3N nanocomposites, the amount of E_interaction was reduced to a smaller positive value, which indicates the tendency of the nanocomposite's components to interact with each other. By further addition of silica nanoparticles to have PS5N and PS7N nanocomposites and then by analysis of the RDF results, it was found that the nanoparticles were not well dispersed in these two nanocomposites and they were accumulated in the NR rubbery phase. Therefore, the percolation threshold for silica loading on the PN blend is at most 3 parts (x = 3). These results as well as the other obtained simulation results were compared with the available experimental data, and the agreement observed between them approved the simulation procedure and validated the obtained results.

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.

Solvation of Carbon Nanoparticles in Water/Alcohol Mixtures: Using Molecular Simulation To Probe Energetics, Structure, and Dynamics

Molecular dynamics simulations were used to examine the solvation behavior of buckminsterfullerene and single-walled carbon nanotubes (SWCNT) in a range of water/alcohol solvent compositions at 1 atm and 300 K. Results indicate that the alcohols assume the role of pseudosurfactants by shielding the nanotube from the more unfavorable interactions with polar water molecules. This is evident in both the free energies of transfer (ΔΔG_water→xOH = -68.1 kJ/mol and -86.5 kJ/mol for C₆₀ in methanol and ethanol; ΔΔG_water→xOH = -345.6 kJ/mol and -421.2 kJ/mol for the (6,5)-SWCNT in methanol and ethanol) and the composition of the solvation shell at intermediate alcohol concentrations. Additionally, we have observed the retardation of both the translational and rotational dynamics of molecules near the nanoparticle surface through use of time correlation functions. A 3-fold increase in the residence times of the alcohol molecules within the solvation shells at low concentrations further reveals their surfactant-like behavior. Such interactions are important when considering the complex molecular environment present in many schemes used for nanoparticle purification techniques.

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.

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.

Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets

Prediction of the dynamic properties of water uptake across polymer libraries can accelerate polymer selection for a specific application. We first built semiempirical models using Artificial Neural Networks and all water uptake data, as individual input. These models give very good correlations (R² > 0.78 for test set) but very low accuracy on cross-validation sets (less than 19% of experimental points within experimental error). Instead, using consolidated parameters like equilibrium water uptake a good model is obtained (R² = 0.78 for test set), with accurate predictions for 50% of tested polymers. The semiempirical model was applied to the 56-polymer library of L-tyrosine-derived polyarylates, identifying groups of polymers that are likely to satisfy design criteria for water uptake. This research demonstrates that a surrogate modeling effort can reduce the number of polymers that must be synthesized and characterized to identify an appropriate polymer that meets certain performance criteria.

Understanding solid-state properties of triglycerides used in pharmaceutical and food microencapsulation

Hydrophobic materials, in particular hydrogenated vegetable oils, HVO, are extensively used as coating materials in food and pharmaceutical systems. Correct application of these coatings requires an evaluation of their behaviour as a function of various parameters such as melting temperature, solubility, concentration and/or pH. The purpose of this study was to assess the physico-chemical properties of an HVO in terms of composition, crystallisation, phase transition and polymorphism using a variety of analytical techniques, such as electrospray mass spectrometry (ESI-MS), differential scanning calorimetry (DSC) and X-ray diffraction (XRD). High-resolution ESI-MS allowed establishment of the HVO main composition of long-chain triglycerides (average molecular weight 1183 Da). DSC results showed that thermal history determines the formation of at least two polymorphs of HVO, namely two different crystal forms, assigned as form α, melting point (m.p.) 48 °C, and form β', m.p. 60 °C. A third polymorph, the more thermodynamically stable β-form, having a melting point at 62 °C, is obtained by solution-mediated re-crystallisation. Phase transformation paths were investigated by isothermal DSC experiments, which evidenced that the α-form is kinetically stable at temperatures lower than 25 °C. These data are of particular interest in practical applications such as spray freezing or pan coating where significant heat transfer phenomena are involved.

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

Molecular models for HPMCAS polymer have been developed for molecular dynamics (MD) simulation that attempt to mimic the complex substitution patterns in HPMCAS observed experimentally. These molecular models were utilized to create amorphous HPMCAS solids by cooling of the polymeric melts at different water contents to explore the influence of water on molecular mobility, which plays a critical role in stability and drug release from HPMCAS-based solid matrices. The densities found for the simulated amorphous HPMCAS were 1.295, 1.287, and 1.276 g/cm(3) at 0.7, 5.7, and 13.2% w/w water, indicating swelling of the polymer with increasing water content. These densities compare favorably with the experimental density of 1.285 g/cm(3) for commercial HPMCAS-(AQOAT AS-MF) supporting the present HPMCAS models as a realistic representation of amorphous HPMCAS solids. Water molecules were observed to be mostly isolated from each other at a low water content (0.7% w/w), while clusters or strands of water were pervasive and broadly distributed in size at 13.2% w/w water. The average number of first-shell water molecules (n(w)) increased from 0.17 to 3.5, though the latter is still far below that (8.9) expected for the onset of a separate water phase. Increasing water content from 0.7 to 13.2% w/w was found to reduce the T(g) by ~81 K, similar to experimental observations. Plasticization with increasing water content resulted in increasing polymer mobility and water diffusivity. From 0.7 to 13.2% w/w water, the apparent water diffusivity increased from 1.1 × 10(-9) to 7.0 × 10(-8) cm(2)/s, though non-Einsteinian behavior persisted at all water contents explored. This and the water trajectories in the polymers suggest that water diffusion at 0.7% w/w water follows a "hopping" mechanism. At a higher water content (13.2% w/w) water diffusion follows dual diffusive processes: (1) fast water motions within water clusters; and (2) slower diffusion through the more rigid polymer matrix.