Bottom-up design of hydrogels for programmable drug release

Harnessing the power of machine learning into tissue engineering: current progress and future prospects

Tissue engineering is a discipline based on cell biology and materials science with the primary goal of rebuilding and regenerating lost and damaged tissues and organs. Tissue engineering has developed rapidly in recent years, while scaffolds, growth factors, and stem cells have been successfully used for the reconstruction of various tissues and organs. However, time-consuming production, high cost, and unpredictable tissue growth still need to be addressed. Machine learning is an emerging interdisciplinary discipline that combines computer science and powerful data sets, with great potential to accelerate scientific discovery and enhance clinical practice. The convergence of machine learning and tissue engineering, while in its infancy, promises transformative progress. This paper will review the latest progress in the application of machine learning to tissue engineering, summarize the latest applications in biomaterials design, scaffold fabrication, tissue regeneration, and organ transplantation, and discuss the challenges and future prospects of interdisciplinary collaboration, with a view to providing scientific references for researchers to make greater progress in tissue engineering and machine learning.

Sequential delivery of cardioactive drugs via microcapped microneedle patches for improved heart function in post myocardial infarction rats

After myocardial infarction, the heart undergoes adverse remodeling characterized by a series of pathological changes, including inflammation, apoptosis, fibrosis, and hypertrophy. In addition to cardiac catheter-based re-establishment of blood flow, patients typically receive multiple medications that aim to address these different mechanisms underlying left ventricular remodeling. The current study aims to establish a versatile multi-drug delivery platform for the controlled and sequential delivery of multiple therapeutic agents in a single treatment. Toward this goal, we generated a microcapped microneedle patch carrying methylprednisolone, interleukin-10, and vascular endothelial growth factor. In vitro characterization demonstrated a time-sequenced release pattern of these drug: methylprednisolone for the first 3 days, interleukin-10 from day 1 to 15, and vascular endothelial growth factor from day 3 to 25. The therapeutic effects of the microneedle patch were evaluated in a rat model of acute myocardial infarction induced by permanent ligation of left anterior descending coronary artery. Heart function was measured using trans-thoracic echocardiography. Heart inflammation, apoptosis, hypertrophy and angiogenesis were evaluated using histology. Our data indicated that, at 28 days after patch transplantation, animals receiving the microneedle patch with sequential release of these three agents showed reduced inflammation, apoptosis and cardiac hypertrophy compared to the animals receiving control patch without sequential release of these agents, which is associated with the improved angiogenesis and heart function. In conclusion, the microneedle patch can be utilized to deliver multiple therapeutic agents in a controlled and sequential manner that aligns with the pathological phases following myocardial infarction. STATEMENT OF SIGNIFICANCE: The post-myocardial infarction heart remodeling is characterized by a series of pathological events including acute inflammation, apoptosis, fibrosis, cardiac hypertrophy, and depressed heart function. In current clinical practice, multiple procedures and drugs given at different time points are necessary to combat these series of pathological events. In this study, we developed a novel microcapped microneedle patch for the controlled sequential delivery of triple cardioprotective drugs aiming to combat acute inflammation and cardiac hypertrophy, and promote angiogenesis. This study presents a comprehensive therapeutic approach, with the microneedle patch addressing multifaceted pathological processes during post-myocardial infarction left ventricular remodeling. This cardiac drug delivery system has the potential to improve patient treatment by delivering drugs in alignment with the series of time-dependent pathological phases following myocardial infarction, ultimately improving clinical outcomes.

Nanotechnology-empowered combination therapy for rheumatoid arthritis: principles, strategies, and challenges

Rheumatoid arthritis (RA) is an autoimmune disease with multifactorial etiology and intricate pathogenesis. In RA, repeated monotherapy is frequently associated with inadequate efficacy, drug resistance, and severe side effects. Therefore, a shift has occurred in clinical practice toward combination therapy. However, conventional combination therapy encounters several hindrances, including low selectivity to arthritic joints, short half-lives, and varying pharmacokinetics among coupled drugs. Emerging nanotechnology offers an incomparable opportunity for developing advanced combination therapy against RA. First, it allows for co-delivering multiple drugs with augmented physicochemical properties, targeted delivery capabilities, and controlled release profiles. Second, it enables therapeutic nanomaterials development, thereby expanding combination regimens to include multifunctional nanomedicines. Lastly, it facilitates the construction of all-in-one nanoplatforms assembled with multiple modalities, such as phototherapy, sonodynamic therapy, and imaging. Thus, nanotechnology offers a promising solution to the current bottleneck in both RA treatment and diagnosis. This review summarizes the rationale, advantages, and recent advances in nano-empowered combination therapy for RA. It also discusses safety considerations, drug-drug interactions, and the potential for clinical translation. Additionally, it provides design tips and an outlook on future developments in nano-empowered combination therapy. The objective of this review is to achieve a comprehensive understanding of the mechanisms underlying combination therapy for RA and unlock the maximum potential of nanotechnology, thereby facilitating the smooth transition of research findings from the laboratory to clinical practice.

AI energized hydrogel design, optimization and application in biomedicine

Traditional hydrogel design and optimization methods usually rely on repeated experiments, which is time-consuming and expensive, resulting in a slow-moving of advanced hydrogel development. With the rapid development of artificial intelligence (AI) technology and increasing material data, AI-energized design and optimization of hydrogels for biomedical applications has emerged as a revolutionary breakthrough in materials science. This review begins by outlining the history of AI and the potential advantages of using AI in the design and optimization of hydrogels, such as prediction and optimization of properties, multi-attribute optimization, high-throughput screening, automated material discovery, optimizing experimental design, and etc. Then, we focus on the various applications of hydrogels supported by AI technology in biomedicine, including drug delivery, bio-inks for advanced manufacturing, tissue repair, and biosensors, so as to provide a clear and comprehensive understanding of researchers in this field. Finally, we discuss the future directions and prospects, and provide a new perspective for the research and development of novel hydrogel materials for biomedical applications.

Recent advances in peptide-based bioactive hydrogels for nerve repair and regeneration: from material design to fabrication, functional tailoring and applications

The injury of both central and peripheral nervous systems can result in neurological disorders and severe nervous diseases, which has been one of the challenges in the medical field. The use of peptide-based hydrogels for nerve repair and regeneration (NRR) provides a promising way for treating these problems, but the effects of the functions of peptide hydrogels on the NRR efficiency have been not understood clearly. In this review, we present recent advances in the material design, matrix fabrication, functional tailoring, and NRR applications of three types of peptide-based hydrogels, including pure peptide hydrogels, other component-functionalized peptide hydrogels, and peptide-modified polymer hydrogels. The case studies on the utilization of various peptide-based hydrogels for NRR are introduced and analyzed, in which the effects and mechanisms of the functions of hydrogels on NRR are illustrated specifically. In addition, the fabrication of medical NRR scaffolds and devices for pre-clinical application is demonstrated. Finally, we provide potential directions on the development of this promising topic. This comprehensive review could be valuable for readers to know the design and synthesis strategies of bioactive peptide hydrogels, as well as their functional tailoring, in order to promote their practical applications in tissue engineering, biomedical engineering, and materials science.

Revolutionizing targeting precision: microfluidics-enabled smart microcapsules for tailored delivery and controlled release

As promising delivery systems, smart microcapsules have garnered significant attention owing to their targeted delivery loaded with diverse active materials. By precisely manipulating fluids on the micrometer scale, microfluidic has emerged as a powerful tool for tailoring delivery systems based on potential applications. The desirable characteristics of smart microcapsules are associated with encapsulation capacity, targeted delivery capability, and controlled release of encapsulants. In this review, we briefly describe the principles of droplet-based microfluidics for smart microcapsules. Subsequently, we summarize smart microcapsules as delivery systems for efficient encapsulation and focus on target delivery patterns, including passive targets, active targets, and microfluidics-assisted targets. Additionally, based on release mechanisms, we review controlled release modes adjusted by smart membranes and on/off gates. Finally, we discuss existing challenges and potential implications associated with smart microcapsules.

Dual-controlled guest release from coordination cages

Despite having significant applications in the construction of controlled delivery systems with high anti-interference capability, to our knowledge dual-controlled molecular release has not yet been achieved based on small molecular/supramolecular entities. Herein, we report a dual-controlled release system based on coordination cages, for which releasing the guest from the cage demands synchronously altering the coordinative metal cations and the solvent. The cages, Hg5L2 and Ag5L2, are constructed via coordination-driven self-assembly of a corannulene-based ligand. While Hg5L2 shows a solvent-independent guest encapsulation in all the studied solvents, Ag5L2 is able to encapsulate the guests in only some of the solvents, such as acetone-d6, but will liberate the encapsulated guests in 1,1,2,2-tetrachloroethane-d2. Hg5L2 and Ag5L2 are interconvertible. Thus, the release of guests from Hg5L2 in acetone-d6 can be achieved, but requires two separate operations, including metal substitutions and a change of the solvent. Dual-controlled systems as such could be useful in complicated molecular release process to avoid those undesired stimulus-responses.

Single-Particle Tracking in Poly(Ethylene Glycol) Diacrylate: Probe Size Effect on the Diffusion Behaviors of Nanoparticles in Unentangled Polymer Solutions

A thorough understanding of the relevant factors governing the transport of nanoparticles in poly(ethylene glycol) diacrylate (PEGDA) is crucial for many applications utilizing this polymer. Here, single-particle tracking (SPT) was used to systematically investigate the role of the probe size (3-200 nm) on the diffusion behaviors of individual fluorescent nanoparticles in semidilute and unentangled PEGDA solutions. The quantitative assessment of the SPT data via the recorded single-particle trajectories and diffusion coefficients (D) not only showed that the observed probe dynamics in PEGDA were temporally and spatially heterogeneous, but more importantly that the measured D were observed to be significantly reduced (vs in solvent) and strongly size-dependent. We explained these results based on a modified multiscale model for particle diffusion, built upon well-established hydrodynamics and obstruction theories. We furthermore showed that the presence of steric interactions and probe confinement effects in highly crowded, unentangled PEGDA microstructures can lead to deviations in the single-particle displacements from the expected Gaussian behavior, as revealed by the van Hove displacement distributions and the associated non-Gaussian parameters. This study has demonstrated the power of SPT methods in offering an advanced characterization of the transport characteristics in complex polymer structures, overcoming challenges posed by traditional characterization techniques.

Sustained release of GLP-1 analog from γ-PGA-PAE copolymers for management of type 2 diabetes

GLP-1 has been clinically exploited for treating type 2 diabetes, while its short circulation half-life requires multiple daily injections to maintain effective glycemic control, thus limiting its widespread application. Here we developed a drug delivery system based on self-assembling polymer-amino acid conjugates (γ-PGA-PAE) to provide sustained release of GLP-1 analog (DLG3312). The DLG3312 loaded γ-PGA based nanoparticles (DLG3312@NPs) exhibited a spherical shape with a good monodispersity under transmission electron microscope (TEM) observation. The DLG3312 encapsulation was optimized, and the loading efficiency was as high as 78.4 ± 2.2 %. The transformation of DLG3312@NPs to network structures was observed upon treatment with the fresh serum, resulting in a sustained drug release. The in vivo long-term hypoglycemic assays indicated that DLG3312@NPs significantly reduced blood glucose and glycosylated hemoglobin level. Furthermore, DLG3312@NPs extended the efficacy of DLG3312, leading to a decrease in the dosing schedule that from once a day to once every other day. This approach combined the molecular and materials engineering strategies that offered a unique solution to maximize the availability of anti-diabetic drug and minimize its burdens to type 2 diabetic patients.

Solute diffusion and partitioning in multi-arm poly(ethylene glycol) hydrogels

Controlling solute transport in hydrogels is critical for numerous chemical separation applications, tissue engineering, and drug delivery systems. In previous review work, we have pointed out that proposed theoretical models and associated experiments tend to oversimplify the influence of the hydrogel structure on solute transport by addressing only the effects of the polymer volume fraction and mesh size of the networks on solute transport. Here, we reexamine these models by experimenting with a library of multi-arm poly(ethylene glycol) (PEG) hydrogels with simultaneous variations in four independent structural parameters. Standardized, high-throughput fluorescence recovery after photobleaching (FRAP) experiments in hydrogels characterize size-dependent solute diffusion and partitioning in each hydrogel formulation. Solute diffusivity dependence on junction functionality shows an influence from network geometry that is not addressed by mesh size-based models, experimentally validating the use of the geometry-responsive mesh radius in solute diffusivity modeling. Furthermore, the Richbourg-Peppas swollen polymer network (SPN) model accurately predicts how three of the four structural parameters affect solute diffusivity in hydrogels. Comparison with the large pore effective medium (LPEM) model showed that the SPN model better predicts solute size and hydrogel structure effects on diffusivity. This study provides a framework for investigating solute transport in hydrogels that will continue to improve hydrogel design for tissue engineering and drug delivery.