Effect of aging on heat transfer, fluid flow and drug transport in anterior human eye: A computational study

Model order reduction and sensitivity analysis for complex heat transfer simulations inside the human eyeball

Heat transfer in the human eyeball, a complex organ, is significantly influenced by various pathophysiological and external parameters. Particularly, heat transfer critically affects fluid behavior within the eye and ocular drug delivery processes. Overcoming the challenges of experimental analysis, this study introduces a comprehensive three-dimensional mathematical and computational model to simulate the heat transfer in a realistic geometry. Our work includes an extensive sensitivity analysis to address uncertainties and delineate the impact of different variables on heat distribution in ocular tissues. To manage the model's complexity, we employed a very fast model reduction technique with certified sharp error bounds, ensuring computational efficiency without compromising accuracy. Our results demonstrate remarkable consistency with experimental observations and align closely with existing numerical findings in the literature. Crucially, our findings underscore the significant role of blood flow and environmental conditions, particularly in the eye's internal tissues. Clinically, this model offers a promising tool for examining the temperature-related effects of various therapeutic interventions on the eye. Such insights are invaluable for optimizing treatment strategies in ophthalmology.

Image-based insilico investigation of hemodynamics and biomechanics in healthy and diabetic human retinas

Retinal hemodynamics and biomechanics play a significant role in understanding the pathophysiology of several ocular diseases. However, these parameters are significantly affected due to changed blood vessel morphology ascribed to pathological conditions, particularly diabetes. In this study, an image-based computational fluid dynamics (CFD) model is applied to examine the effects of changed vascular morphology due to diabetes on blood flow velocity, vorticity, wall shear stress (WSS), and oxygen distribution and compare it with healthy. The 3D patient-specific vascular architecture of diabetic and healthy retina is extracted from Optical Coherence Tomography Angiography (OCTA) images and fundus to extract the capillary level information. Further, Fluid-structure interaction (FSI) simulations have been performed to compare the induced tissue stresses in diabetic and healthy conditions. Results illustrate that most arterioles possess higher velocity, vorticity, WSS, and lesser oxygen concentration than arteries for healthy and diabetic cases. However, an opposite trend is observed for venules and veins. Comparisons show that, on average, the blood flow velocity in the healthy case decreases by 42 % in arteries and 21 % in veins, respectively, compared to diabetic. In addition, the WSS and von Mises stress (VMS) in healthy case decrease by 49 % and 72 % in arteries and by 6 % and 28 % in veins, respectively, when compared with diabetic, making diabetic blood vessels more susceptible to wall rupture and tissue damage. The in-silico results may help predict the possible abnormalities region early, helping the ophthalmologists use these estimates as prognostic tools and tailor patient-specific treatment plans.

How can machine learning and multiscale modeling benefit ocular drug development?

The eyes possess sophisticated physiological structures, diverse disease targets, limited drug delivery space, distinctive barriers, and complicated biomechanical processes, requiring a more in-depth understanding of the interactions between drug delivery systems and biological systems for ocular formulation development. However, the tiny size of the eyes makes sampling difficult and invasive studies costly and ethically constrained. Developing ocular formulations following conventional trial-and-error formulation and manufacturing process screening procedures is inefficient. Along with the popularity of computational pharmaceutics, non-invasive in silico modeling & simulation offer new opportunities for the paradigm shift of ocular formulation development. The current work first systematically reviews the theoretical underpinnings, advanced applications, and unique advantages of data-driven machine learning and multiscale simulation approaches represented by molecular simulation, mathematical modeling, and pharmacokinetic (PK)/pharmacodynamic (PD) modeling for ocular drug development. Following this, a new computer-driven framework for rational pharmaceutical formulation design is proposed, inspired by the potential of in silico explorations in understanding drug delivery details and facilitating drug formulation design. Lastly, to promote the paradigm shift, integrated in silico methodologies were highlighted, and discussions on data challenges, model practicality, personalized modeling, regulatory science, interdisciplinary collaboration, and talent training were conducted in detail with a view to achieving more efficient objective-oriented pharmaceutical formulation design.

Characterizing the Aging Process of the Human Eye: Tear Evaporation, Fluid Dynamics, Blood Flow, and Metabolism-Based Comparative Study

Eye temperature and intraocular pressure are two measurable parameters that can be monitored as a health index with aging. Deviations from the normal range of intraocular pressure and temperature lead to the formation of many diseases. This study has been carried out to evaluate the relations between the physiological and anatomical changes of the eye with aging using mathematical modeling. 2D computer-aided design of the human eye has been developed for two major groups: 21 to 30 years and 41 to 50 years. The computer simulation has been carried out to determine the effects of physiological changes of tear evaporation, fluid dynamics, blood flow, and metabolism of eye tissues with aging. The simulation has been carried out in the standing and the supine position of a human body. The rate of temperature change is – 0.0075 K per year in the standing position and – 0.007 K per year in the supine position because of the modeled anatomical and physiological effects. All the three simulation parameters of this study, the temperature of the human eye, the intraocular pressure, and the aqueous humor flow velocity, have been compared with the recent practical and simulation-based experiments to validate our results.

Ocular Fluid Mechanics and Drug Delivery: A Review of Mathematical and Computational Models

The human eye is a complex biomechanical structure with a range of biomechanical processes involved in various physiological as well as pathological conditions. Fluid flow inside different domains of the eye is one of the most significant biomechanical processes that tend to perform a wide variety of functions and when combined with other biophysical processes play a crucial role in ocular drug delivery. However, it is quite difficult to comprehend the effect of these processes on drug transport and associated treatment experimentally because of ethical constraints and economic feasibility. Computational modeling on the other hand is an excellent means to understand the associated complexity between these aforementioned processes and drug delivery. A wide range of computational models specific to different types of fluids present in different domains of the eye as well as varying drug delivery modes has been established to understand the fluid flow behavior and drug transport phenomenon in an insilico manner. These computational models have been used as a non-invasive tool to aid ophthalmologists in identifying the challenges associated with a particular drug delivery mode while treating particular eye diseases and to advance the understanding of the biomechanical behavior of the eye. In this regard, the author attempts to summarize the existing computational and mathematical approaches proposed in the last two decades for understanding the fluid mechanics and drug transport associated with different domains of the eye, together with their application to modify the existing treatment processes.

Analysis of topical dosing and administration effects on ocular drug delivery in a human eyeball model using computational fluid dynamics

Predicting the spatial and temporal drug concentration distributions in the eyes is essential for quantitative analysis of the therapeutic effect and overdose issue via different topical administration strategies. To address such needs, an experimentally validated computational fluid dynamics (CFD) based virtual human eye model with physiologically realistic multiple ophthalmic compartments was developed to study the effect of administration frequency and interval on drug concentration distributions. Timolol was selected as the topical dosing drug for the numerical investigation of how administration strategy can influence drug transport and concentration distribution over time in the human eye. Administration frequencies employed in this study are 1-4 times per day, and the administration time intervals are Δt = 900 s, 1800 s, and 3600 s. Numerical results indicate that the administration frequency can significantly affect the temporal timolol concentration distributions in the ophthalmic compartments. More administrations per day can prolong the mediations at relatively high levels in all compartments. CFD simulation results also show that shorter administration intervals can help the medication maintain a relatively higher concentration during the initial hours. Longer administration intervals can provide a more stable medication concentration during the entire dosing time. Furthermore, numerical parametric analysis in this study indicates that the elimination rate in the aqueous humor plays a dominant role in affecting the drug concentrations in multiple ophthalmic compartments. However, it still needs additional clinical data to identify how much drugs can be transported into the cardiac and/or respiratory systems via blood circulation for side effect assessment.