From Microscale to Macroscale: Nine Orders of Magnitude for a Comprehensive Modeling of Hydrogels for Controlled Drug Delivery

Biomaterials and Cell Therapy Combination in Central Nervous System Treatments

Current pharmacological and surgical therapies for the central nervous system (CNS) show a limited capacity to reduce the damage progression; that together with the intrinsic limited capability of the CNS to regenerate greatly reduces the hopes of recovery. Among all the therapies proposed, the tissue engineering strategies supplemented with therapeutic stem cells remain the most promising. Neural tissue engineering strategies are based on the development of devices presenting optimal physical, chemical, and mechanical properties which, once inserted in the injured site, can support therapeutic cells, limiting the effect of a hostile environment and supporting regenerative processes. Thus, this review focuses on the employment of hydrogel and nanofibrous scaffolds supplemented with stem cells as promising therapeutic tools for the central and peripheral nervous systems in preclinical and clinical applications.

Exploring the Potential of Artificial Intelligence for Hydrogel Development-A Short Review

AI and ML have emerged as transformative tools in various scientific domains, including hydrogel design. This work explores the integration of AI and ML techniques in the realm of hydrogel development, highlighting their significance in enhancing the design, characterisation, and optimisation of hydrogels for diverse applications. We introduced the concept of AI train hydrogel design, underscoring its potential to decode intricate relationships between hydrogel compositions, structures, and properties from complex data sets. In this work, we outlined classical physical and chemical techniques in hydrogel design, setting the stage for AI/ML advancements. These methods provide a foundational understanding for the subsequent AI-driven innovations. Numerical and analytical methods empowered by AI/ML were also included. These computational tools enable predictive simulations of hydrogel behaviour under varying conditions, aiding in property customisation. We also emphasised AI's impact, elucidating its role in rapid material discovery, precise property predictions, and optimal design. ML techniques like neural networks and support vector machines that expedite pattern recognition and predictive modelling using vast datasets, advancing hydrogel formulation discovery are also presented. AI and ML's have a transformative influence on hydrogel design. AI and ML have revolutionised hydrogel design by expediting material discovery, optimising properties, reducing costs, and enabling precise customisation. These technologies have the potential to address pressing healthcare and biomedical challenges, offering innovative solutions for drug delivery, tissue engineering, wound healing, and more. By harmonising computational insights with classical techniques, researchers can unlock unprecedented hydrogel potentials, tailoring solutions for diverse applications.

Interplay between Diffusion and Bond Cleavage Reaction for Determining Release in Polymer-Drug Conjugates

In conjugated polymeric drug delivery systems, both the covalent bond degradation rate and the diffusion of the freely moving drug particles affect the release profile of the formulation. Using Monte Carlo simulations in spherical matrices, the release kinetics resulting from the competition between the reaction and diffusion processes is discussed. For different values of the relative bond cleavage rate, varied over four orders of magnitude, the evolution of (i) the number of bonded drug molecules, (ii) the fraction of the freely moved detached drug within the polymer matrix, and (iii) the resulting fractional release of the drug is presented. The characteristic release time scale is found to increase by several orders of magnitude as the cleavage reaction rate constant decreases. The two extreme rate-limiting cases where either the diffusion or the reaction dominates the release are clearly distinguishable. The crossover between the diffusion-controlled and reaction-controlled regimes is also examined and a simple analytical formula is presented that can describe the full dependence of the release time on the bond cleavage rate constant. This simple relation is provided simply by the sum of the characteristic time for purely diffusional release and the bond cleavage decay time, which equals the inverse of the reaction rate constant.

Analysis of diffusion of plant metabolites from polyethylene glycol hydrogels using free volume theory

The present work aims to comprehensively analyze the diffusion of plant metabolites from the polyethylene glycol (PEG) hydrogels for controlled release applications. For this study, a mathematical model based on free volume theory has been utilized to simulate the diffusion of low molecular weight plant metabolites. The results demonstrate that the mesh size of the crosslinked network, thereby the diffusion coefficient of the natural compound can be computed using the current framework. The proposed model has also been validated using the experimental data. The diffusion period has been observed to vary within a wide range of 3.42 h for Cinnamaldehyde to 49.25 h for Grandinin. An empirical parametric relationship between the diffusion time and molecular weight of both the hydrogels and natural compounds is established. It appears that the reported modeling approach will be clinically useful for improving the design of the sustained drug delivery systems.

Coarse-Grained Simulations of Release of Drugs Housed in Flexible Nanogels: New Insights into Kinetic Parameters

The diffusion-controlled release of drugs housed in flexible nanogels has been simulated with the help of a coarse-grained model that explicitly considers polymer chains. In these in silico experiments, the effect of its flexibility is assessed by comparing it with data obtained for a rigid nanogel with the same volume fraction and topology. Our results show that the initial distribution of the drug can exert a great influence on the release kinetics. This work also reveals that certain surface phenomena driven by steric interactions can lead to apparently counterintuitive behaviors. Such phenomena are not usually included in many theoretical treatments used for the analysis of experimental release kinetics. Therefore, one should be very careful in drawing conclusions from these formalisms. In fact, our results suggest that the interpretation of drug release curves in terms of kinetic exponents (obtained from the Ritger-Peppas Equation) is a tricky question. However, such curves can provide a first estimate of the drug diffusion coefficient.

Stochastic Lattice-Based Modeling of Macromolecule Release from Degradable Hydrogel

A three-dimensional lattice-based model has been developed to describe the release of a macromolecular drug encapsulated in a degradable hydrogel. The degradation-induced network heterogeneity is considered by assigning varying diffusion coefficients to the lattice sites based on the fitted exponential node-diffusivity relationship. As time passes, due to the degradation of crosslink nodes, diffusivity values in lattice sites progress to lower values. To overcome the size limitation of the computational model and to compare it with experimental data, a scaling ratio based on the random walk equation is developed. The model was able to describe the experimental release data from chemically crosslinked dextran hydrogels. The results showed that the effect of the initial network and the chemistry of crosslink nodes (hydrolysis rate) on the drug release profile cannot be decoupled.

Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials

Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is a major bottleneck, especially for high throughput protocols and for complex multi-component systems. To eliminate this bottleneck, we present the polyply software suite that provides 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution. We benchmark quality and performance of the approach by creating realistic coordinates for polymer melt simulations, single-stranded as well as circular single-stranded DNA. We further demonstrate the power of our approach by setting up a microphase-separated block copolymer system, and by generating a liquid-liquid phase separated system inside a lipid vesicle.

Poly(vinyl alcohol) Hydrogels: The Old and New Functional Materials

Hydrogels have three-dimensional network structures, high water content, good flexibility, biocompatibility, and stimulation response, which have provided a unique role in many fields such as industry, agriculture, and medical treatment. Poly(vinyl alcohol) PVA hydrogel is one of the oldest composite hydrogels. It has been extensively explored due to its chemical stability, nontoxic, good biocompatibility, biological aging resistance, high water-absorbing capacity, and easy processing. PVA-based hydrogels have been widely investigated in drug carriers, articular cartilage, wound dressings, tissue engineering, and other intelligent materials, such as self-healing and shape-memory materials, supercapacitors, sensors, and other fields. In this paper, the discovery, development, preparation, modification methods, and applications of PVA functionalized hydrogels are reviewed, and their potential applications and future research trends are also prospected.

Exploring space-energy matching via quantum-molecular mechanics modeling and breakage dynamics-energy dissipation via microhydrodynamic modeling to improve the screening efficiency of nanosuspension prepared by wet media milling

Introduction: The preparation of nanosuspensions by wet media milling is a promising technique that increases the bioavailability of insoluble drugs. The nanosuspension is thermodynamically unstable, where its stability might be influenced by the interaction energy between the stabilizers and the drugs after milling at a specific collision energy. However, it is difficult to screen the stabilizers and the parameters of milling accurately and quickly by using traditional analysis methods. Quantum-molecular mechanics and microhydrodynamic modeling can be applied to improve screening efficiency.Areas covered: Quantum-molecular mechanics model, which includes molecular docking, molecular dynamics simulations, and data on binding energy, provides insights into screening stabilizers based on their molecular behavior at the atomic level. The microhydrodynamic model explores the mechanical processes and energy dissipation in nanomilling, and even combines information on the mechanical modulus and an energy vector diagram for the milling parameters screening of drug crystals.Expert opinion: These modeling methods improve screening efficiency and support screening theories based on thermodynamics and physical dynamics. However, how to reasonably combine different modeling methods with their theoretical characteristics and further multidimensional and cross-scale simulations of nanosuspension formation remain challenges.

Universal description of steric hindrance in flexible polymer gels

In this work, the long-time diffusion of a solute in a chemically crosslinked and flexible hydrogel is computed from a bead-spring model of a polymeric network to assess the effect of steric obstruction. The relative diffusivities obtained for a wide variety of systems can be described by an exponential decay depending on a parameter that differs from that employed for rigid gels. The mathematical expression derived here can approximately predict the diffusivity in flexible gels if steric hindrance is the mechanism ruling diffusion.

The Martini Model in Materials Science

The Martini model, a coarse-grained force field initially developed with biomolecular simulations in mind, has found an increasing number of applications in the field of soft materials science. The model's underlying building block principle does not pose restrictions on its application beyond biomolecular systems. Here, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3.

Interaction of epoxy-based hydrogels and water: A molecular dynamics simulation study

Biomaterials play a crucial role in tissue engineering as a functional replacement, regenerative medicines, supportive scaffold for guided tissue growth, and drug delivery devices. The term biomaterial refers to metals, ceramics, and polymers account for the vast majority. In the case of polymers, hydrogels have emerged as active materials for an immense variety of applications. Epoxy-based hydrogels possess a unique network structure that enables very high levels of hydrophilicity and biocompatibility. Hydrogel such as Medipacs Epoxy Polymers (MEPs) models were constructed to understand water's behavior at the water/hydrogel interface and hydrogel network. We computed the Gibbs dividing surface (GDS) to define the MEP/water interface, and all the physicochemical properties were computed based on GDS. We calculated the radial distribution function (RDF), the 2D surface roughness of the immersed MEPs. RDF analysis confirmed that the first hydration shell is at a distance of 1.86 Å, and most of the water molecules are near the hydroxyl group of the MEPs network. Hydrogen bonds (H-bonds) analysis was performed, and the observation suggested that the disruption of the H-bonds between MEP chains leads to an increase in the polymer matrix's void spaces. These void spaces are filled with diffused water molecules, leading to swelling of the MEP hydrogel. The swelling parameter was estimated from the fitted curve of the yz-lattice of the simulation cell. The MEP/water interface simulation results provide insightful information regarding the design strategy of epoxy-based hydrogel and other hydrogels vital for biomedical applications.

Solute diffusion in gels: Thirty years of simulations

In this review, we present a summary of computer simulation studies on solute diffusion in gels carried out in the last three decades. Special attention is paid to coarse-grained simulations in which the role of steric and electrostatic interactions on the particle diffusion can be evaluated. In addition, other important characteristics of particle diffusion in gels, such as the stiffness of the gel structure and hydrodynamic interactions, can be taken into account through coarse-grained simulations. Emphasis is placed on how simulation results help to test phenomenological models and to improve the interpretation interof experimental results. Finally, coarse-grained simulations have also been employed to study the diffusion controlled release of drugs from gels. We believe that scientific advances in this line will be useful to better understand the mechanisms that control the diffusive transport of molecules in a wide variety of biological systems.

Comparative Study on Enzyme Immobilization Using Natural Hydrogel Matrices—Experimental Studies Supported by Molecular Models Analysis

Currently, great attention is focused on conducting manufacture processes using clean and eco-friendly technologies. This research trend also relates to the production of immobilized biocatalysts of industrial importance using matrices and methods that fulfill specified operational and environmental requirements. For that reason, hydrogels of natural origin and the entrapment method become increasingly popular in terms of enzyme immobilization. The presented work is the comparative research on invertase immobilization using two natural hydrogel matrices—alginate and gelatin. During the study, we provided the molecular insight into the structural characteristics of both materials regarding their applicability as effective enzyme carriers. In order to confirm our predictions of using these hydrogels for invertase immobilization, we performed the typical experimental studies. In this case, the appropriate conditions of enzyme entrapment were selected for both types of carrier. Next, the characterization of received invertase preparations was made. As a final experimental result, the gelatin-based hydrogel was selected as an effective carrier for invertase immobilization. Hereby, using mild conditions and a pro-ecological, biodegradable matrix, it was possible to obtain very stable and reactive biocatalyst. The choice of gelatin-immobilized invertase preparation was compatible with our predictions based on the molecular models of hydrogel matrices and enzyme used.

Designer Self-Assembling Peptide Hydrogels to Engineer 3D Cell Microenvironments for Cell Constructs Formation and Precise Oncology Remodeling in Ovarian Cancer

Designer self-assembling peptides form the entangled nanofiber networks in hydrogels by ionic-complementary self-assembly. This type of hydrogel has realistic biological and physiochemical properties to serve as biomimetic extracellular matrix (ECM) for biomedical applications. The advantages and benefits are distinct from natural hydrogels and other synthetic or semisynthetic hydrogels. Designer peptides provide diverse alternatives of main building blocks to form various functional nanostructures. The entangled nanofiber networks permit essential compositional complexity and heterogeneity of engineering cell microenvironments in comparison with other hydrogels, which may reconstruct the tumor microenvironments (TMEs) in 3D cell cultures and tissue-specific modeling in vitro. Either ovarian cancer progression or recurrence and relapse are involved in the multifaceted TMEs in addition to mesothelial cells, fibroblasts, endothelial cells, pericytes, immune cells, adipocytes, and the ECM. Based on the progress in common hydrogel products, this work focuses on the diverse designer self-assembling peptide hydrogels for instructive cell constructs in tissue-specific modeling and the precise oncology remodeling for ovarian cancer, which are issued by several research aspects in a 3D context. The advantages and significance of designer peptide hydrogels are discussed, and some common approaches and coming challenges are also addressed in current complex tumor diseases.

Coarse-grained Monte Carlo simulations of nanogel-polyelectrolyte complexes: electrostatic effects

Coarse-grained Monte-Carlo simulations of nanogel-polyelectrolyte complexes have been carried out. The results presented here capture two phenomena reported in experiments with real complexes: (i) the reduction in size after absorbing just a few chains and (ii) the charge inversion detected through electrophoretic mobility data. Our simulations reveal that charge inversion occurs if the polyelectrolyte charge is large enough. In addition, the distribution of chains inside the nanogel strongly depends on whether charge inversion takes place. It should also be stressed that the chain topology has little influence on most of the properties studied here.