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Optic 3D Modeling in Ophthalmic Treatment

Optic 3D Modeling in Ophthalmic Treatment

Visual impairment is a global health concern. Visually impaired patients are at high risk for accidents, depression, and social withdrawal. Eye disorders like age-related macular degeneration (AMD), diabetic retinopathy, glaucoma, and retinitis pigmentosa (RP) cause irreparable vision loss and affect the quality of life of millions of people. Currently, only a limited number of 3D systems exist that can accurately mimic human ocular pathophysiology. This is especially true for retinal degenerative diseases. Optic 3D modeling is important for drug research and design at biomarkers identified by 2D models.  In this study, the researchers discussed various developments in the optic 3D modeling and describe its use in the treatment of optic neuropathy. They analyzed its effectiveness according to the associated disease models and their applications in drug screening, mechanism studies, and cell and gene therapies. 

In order to understand the 3D environment of in vivo tissues, tissue engineering and microfluidic model systems are created for drug discovery during the preclinical stages. 3D Assays are important as they can reduce animal testing, evaluate targeted drug delivery, and speed up the drug development process. Conventional 3D engineering is a precise tool to create relevant 3D tissues with defined properties that benefits from: 

  • 3D bioprinters with defined 3D geometries
  • biocompatible materials and hydrogels as 3D cell support
  • bioreactors for providing mechanical and chemical cues
  • autologous cells from different stem cell resources
  • available noninvasive technologies for high-resolution imaging analysis. 

RGC disorders, Glaucoma, and Optic Neuropathies

Retinal ganglion cell (RGC) death is one of the major endpoints of optic neuropathies. While current management and strategies of optic neuropathies tend to focus on intraocular pressure-lowering treatment, this is ineffective. More and more patients suffer from irreversible visual impairment. RGC disorders affect the neurons of the eye that are connected to the optic nerve. Because of this, the RGC layer is severely affected by optic neuropathies. In fact, optic neuropathies are always associated with RGC disorders. 

In glaucoma, the common characteristic show in the form of nerve degeneration and loss of RGCs. This is also accompanied by the thinning of the neuroretinal rim and nerve fiber layer.

The link between high intraocular pressure (IOP) and RGC mortality is still a mystery. Theories that it is is likely caused by mechanical stress at the lamina cribrosa have been shown in various medical studies. 

Although high IOP is a huge risk factor, many studies have also found that glaucomatous RGC degeneration can occur with normal IO, especially in primary open-angle glaucoma, which is often linked with risk factors such as ethnicity, age, and family history. This suggests that other mechanisms for glaucoma and RGC death exist. 

When a patient has glaucoma, he or she experiences a variety of signals including hypoxia, oxidative stress, and trophic factor deprivation which have been reported to trigger RGC apoptosis. Naturally, neurotrophic factors are used for the development of RGC survival after injury. Furthermore, brain-derived neurotrophic factor (BDNF), nerve growth factor (NGF), glial cell-derived neurotrophic factor, insulin-like growth factor-1(IGF-1), and leukemia inhibitory factor might all prevent or delay RGC death. The ultimate goal of optic 3D modeling would be the ability to replace damaged or dead RGCs with stem-cell replacements grown on a scaffolding made possible by accurate 3D models. This could slow or eliminate further retinal degradation.

The Cellular Structure of the Retina

The retina is a layer of tissue near the optic nerve that borders the back of the eye on the inside. Retinas have layers of photoreceptor cells, bipolar cells, horizontal cells, amacrine cells, and RGCs. But they are mainly comprised of neuronal cells derived from ectoderm. They are the part of the eye that receives light upon which the lens has focused. The retina converts the light into neural signals and sends them to the brain for visual recognition. The retina has a very important role in vision and damage can cause blindness. Disorders such as retinal detachment can prevent the retina from processing light. 

Understanding the retina’s structure and function is important for diagnosing and treating patients who have optic nerve damage. RGS in the retina collects signals from bipolar and amacrine cells. Death of RGC death causes various degenerative diseases, optic neuropathies, and vision loss. This is also true for photoreceptor damage and destruction in addition to the primary involvement of the overlying RGC layer. 

Optic 3D Modeling for Retinal Models

Retinal organoids with a striking similarity to the human retina are now being studied by scientists. However, retinas present modeling challenges due to existing functional complexities. Because of this, only a limited number of functions can be studied in a single model.

Today, 3D engineering’s most promising technology includes 3D cellular in vitro systems, microfluidics, self-organized organoids, and 3D biofabrication. With the invention of human-induced pluripotent stem cell (iPSC) technology, 3D cellular vitro systems further allow wide access to human-like tissue models such as the retina. Using these modern technologies, drug screening in 3D tissue models is slowly becoming a reality. However, to screen thousands of compounds, machine learning is needed to maximize outcomes. 

Disadvantages of 3D Organoids and Cellular models

When compared with the mammalian retina in vivo, most in vitro organoid systems lack several important features. To work around these limitations, endothelial cells are incorporated in retinal organoids via external addition. This has resulted in positive outcomes. However, scientists have found that it is extremely time-consuming for human retinal organoids to follow the embryonic development process. Any solution to shorten the timeline is also very challenging. 

Another issue can be found in the current protocols which still suffer human iPSC cell line variability and difficulties in creating maturated retinal cells. To some extent, the introduction of micro materials can improve the overall reproducibility of the internal cytoarchitecture of the model. But they are found to be inefficient and tend to exhibit more complicated intercellular connectivity and arrangement of rods and cones. Scientists have also found that there’s no way to reproduce the effect of aging to achieve precise developmental timing in optic 3D models of retinal tissues. Another major disadvantage is the structure’s shape. The lack of orientation surrounding tissues and extracellular matrix can prohibit OC development and peripheral-central specialization. 

Conclusion 

Generation of precise tissue structures is now possible with surface-engineering and modern technologies. The creation of ‘human organoids-on-a-chip’ is also quickly progressing and is beneficial in the creation of reliable optic 3D models.

With the combination of scaffolds and 3D bioprinting, it’ll be easier to control RGC positioning. For the neurons that are difficult to manipulate for bioprinting, RGC replacement using multi responsive self-healing materials which can also result in novel cell therapies 

Problems that need to be overcome for this technology include the purification of donor cells, targeting the cell surface, biomarkers for RGC isolation, and immune rejection for transplantation. Although it’s not perfect, the present methodologies offer amazing opportunities in treating what was once untreatable degenerative retinal diseases and optic neuropathies.

 

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