Experimental and mathematical approaches for drug delivery for the treatment of wet age-related macular degeneration

Advancements in Ocular Modelling and Simulations: Key Considerations and Case Studies

This review paper discusses the key aspects of ocular biopharmaceutics, with emphasis on the crucial role played by ocular compartmental modelling and simulation in deciphering physiological conditions related to various eye diseases. It describes eye's intricate structure and function and the need for precise and targeted drug delivery systems to address prevalent eye conditions. The review categorizes and discusses various formulations employed in ocular drug delivery, delineating their respective advantages and limitations. Additionally, it probes the challenges inherent in diverse routes of drug administration for ocular therapies and provides insights into the complexities of achieving optimal drug concentrations at the target site within the eye. The central theme of this work is the ocular compartmental modelling and simulations. Hence, this works discusses on the nuanced understanding of physiological conditions within the eye, drug distribution, drug release kinetics, and key considerations for ocular compartmental modelling and simulations. By combining information from various sources, this review aims to serve as a comprehensive reference for researchers, clinicians, and pharmaceutical developers. It covers the multifaceted landscape of ocular biopharmaceutics and the transformative impact of modelling and simulation in optimizing ocular drug delivery strategies.

Computer modeling of bevacizumab drug distribution after intravitreal injection in rabbit and human eyes

Age-related macular degeneration (AMD) is a progressive eye disease that causes loss of central vision and has no cure. Wet AMD is the late neovascular form treated with vascular endothelial growth factor (VEGF) inhibitors. VEGF is the critical driver of wet AMD. One common off-label anti-VEGF drug used in AMD treatment is bevacizumab. Experimental efforts have been made to investigate the pharmacokinetic (PK) behavior of bevacizumab in vitreous and aqueous humor. Still, the quantitative effect of elimination routes and drug concentration in the macula are not well understood. In this work, we developed two spatial models representing rabbit and human vitreous to better understand the PK behavior of bevacizumab. This study explores different cases of drug elimination and the effects of injection location on drug concentration profiles. The models are validated by comparing them with experimental data. Our results suggest that anterior elimination is dominant for bevacizumab clearance from rabbit vitreous, whereas both anterior and posterior elimination have similar importance in drug clearance from the human vitreous. Furthermore, results indicate that drug injections closer to the posterior segment of the vitreous help maintain relevant drug concentrations for longer, improving bevacizumab duration of action in the vitreous. The rabbit and human models predict bevacizumab concentration in the vitreous and fovea, enhancing knowledge and understanding of wet AMD treatment.

Artificial intelligence for diagnosing exudative age-related macular degeneration

BACKGROUND

Age-related macular degeneration (AMD) is a retinal disorder characterized by central retinal (macular) damage. Approximately 10% to 20% of non-exudative AMD cases progress to the exudative form, which may result in rapid deterioration of central vision. Individuals with exudative AMD (eAMD) need prompt consultation with retinal specialists to minimize the risk and extent of vision loss. Traditional methods of diagnosing ophthalmic disease rely on clinical evaluation and multiple imaging techniques, which can be resource-consuming. Tests leveraging artificial intelligence (AI) hold the promise of automatically identifying and categorizing pathological features, enabling the timely diagnosis and treatment of eAMD.

OBJECTIVES

To determine the diagnostic accuracy of artificial intelligence (AI) as a triaging tool for exudative age-related macular degeneration (eAMD).

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, three clinical trials registries, and Data Archiving and Networked Services (DANS) for gray literature. We did not restrict searches by language or publication date. The date of the last search was April 2024.

SELECTION CRITERIA

Included studies compared the test performance of algorithms with that of human readers to detect eAMD on retinal images collected from people with AMD who were evaluated at eye clinics in community or academic medical centers, and who were not receiving treatment for eAMD when the images were taken. We included algorithms that were either internally or externally validated or both.

DATA COLLECTION AND ANALYSIS

Pairs of review authors independently extracted data and assessed study quality using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool with revised signaling questions. For studies that reported more than one set of performance results, we extracted only one set of diagnostic accuracy data per study based on the last development stage or the optimal algorithm as indicated by the study authors. For two-class algorithms, we collected data from the 2x2 table whenever feasible. For multi-class algorithms, we first consolidated data from all classes other than eAMD before constructing the corresponding 2x2 tables. Assuming a common positivity threshold applied by the included studies, we chose random-effects, bivariate logistic models to estimate summary sensitivity and specificity as the primary performance metrics.

MAIN RESULTS

We identified 36 eligible studies that reported 40 sets of algorithm performance data, encompassing over 16,000 participants and 62,000 images. We included 28 studies (78%) that reported 31 algorithms with performance data in the meta-analysis. The remaining nine studies (25%) reported eight algorithms that lacked usable performance data; we reported them in the qualitative synthesis. Study characteristics and risk of bias Most studies were conducted in Asia, followed by Europe, the USA, and collaborative efforts spanning multiple countries. Most studies identified study participants from the hospital setting, while others used retinal images from public repositories; a few studies did not specify image sources. Based on four of the 36 studies reporting demographic information, the age of the study participants ranged from 62 to 82 years. The included algorithms used various retinal image types as model input, such as optical coherence tomography (OCT) images (N = 15), fundus images (N = 6), and multi-modal imaging (N = 7). The predominant core method used was deep neural networks. All studies that reported externally validated algorithms were at high risk of bias mainly due to potential selection bias from either a two-gate design or the inappropriate exclusion of potentially eligible retinal images (or participants). Findings Only three of the 40 included algorithms were externally validated (7.5%, 3/40). The summary sensitivity and specificity were 0.94 (95% confidence interval (CI) 0.90 to 0.97) and 0.99 (95% CI 0.76 to 1.00), respectively, when compared to human graders (3 studies; 27,872 images; low-certainty evidence). The prevalence of images with eAMD ranged from 0.3% to 49%. Twenty-eight algorithms were reportedly either internally validated (20%, 8/40) or tested on a development set (50%, 20/40); the pooled sensitivity and specificity were 0.93 (95% CI 0.89 to 0.96) and 0.96 (95% CI 0.94 to 0.98), respectively, when compared to human graders (28 studies; 33,409 images; low-certainty evidence). We did not identify significant sources of heterogeneity among these 28 algorithms. Although algorithms using OCT images appeared more homogeneous and had the highest summary specificity (0.97, 95% CI 0.93 to 0.98), they were not superior to algorithms using fundus images alone (0.94, 95% CI 0.89 to 0.97) or multimodal imaging (0.96, 95% CI 0.88 to 0.99; P for meta-regression = 0.239). The median prevalence of images with eAMD was 30% (interquartile range [IQR] 22% to 39%). We did not include eight studies that described nine algorithms (one study reported two sets of algorithm results) to distinguish eAMD from normal images, images of other AMD, or other non-AMD retinal lesions in the meta-analysis. Five of these algorithms were generally based on smaller datasets (range 21 to 218 participants per study) yet with a higher prevalence of eAMD images (range 33% to 66%). Relative to human graders, the reported sensitivity in these studies ranged from 0.95 and 0.97, while the specificity ranged from 0.94 to 0.99. Similarly, using small datasets (range 46 to 106), an additional four algorithms for detecting eAMD from other retinal lesions showed high sensitivity (range 0.96 to 1.00) and specificity (range 0.77 to 1.00).

AUTHORS' CONCLUSIONS

Low- to very low-certainty evidence suggests that an algorithm-based test may correctly identify most individuals with eAMD without increasing unnecessary referrals (false positives) in either the primary or the specialty care settings. There were significant concerns for applying the review findings due to variations in the eAMD prevalence in the included studies. In addition, among the included algorithm-based tests, diagnostic accuracy estimates were at risk of bias due to study participants not reflecting real-world characteristics, inadequate model validation, and the likelihood of selective results reporting. Limited quality and quantity of externally validated algorithms highlighted the need for high-certainty evidence. This evidence will require a standardized definition for eAMD on different imaging modalities and external validation of the algorithm to assess generalizability.

Intraocular drugs: pharmacokinetic strategies and the influence on efficacy and durability

INTRODUCTION

The modern treatment of chorioretinal vascular diseases follows the recent development and rapid adoption of drugs that inhibit vascular endothelial growth factor (VEGF). All anti-VEGF drugs are delivered intravitreally, with clinical behavior, including efficacy, durability, and safety, largely determined by their pharmacokinetic properties.

AREAS COVERED

Properties of these new drugs include additional binding targets (placental growth factor (PlGF) and angiopoietin 2 (Ang 2)), binding affinity, potency, intravitreal half-life, and increased molar dose. A PubMed search for 'pharmacokinetics of anti-VEGF drugs' was performed from 2000 to 2023. Relevant studies were reviewed and referred to in the manuscript.

EXPERT OPINION

Early developers concentrated on improving efficacy, but since maximum efficacy with VEGF inhibition has been reached, development has pivoted to extending the duration of action. Durability strategies include inhibiting additional pathways (faricimab), increasing molar dose (abicipar, brolucizumab, faricimab, and aflibercept 8 mg), and prolonging the intravitreal half-life (abicipar and KSI-301). Recent phase 3 trials demonstrated modest improvements in durability, but failures that might be attributed to these strategies (conjugation and manufacturing processes) have occurred. Future drug development focuses on extending duration of action with implantable reservoirs (ranibizumab port delivery system), sustained release devices (tyrosine kinase inhibitors), and gene therapy.

Drug polymer conjugates: Average release time from thin films

The reaction-diffusion problem describing the release of drugs conjugated through labile bonds to polymeric thin films has a known analytical solution, when the reaction kinetics is of first order. Using this solution, an exact formula is derived for the average release time of the system. This simple expression provides the characteristic time of release tav as the sum of the corresponding average diffusion time plus the inverse reaction rate constant: tav=(1/12)⋅(L2/D)+(1/k), where L is the slab thickness, D the diffusion coefficient, and k the reaction rate constant. The former term dominates in a diffusion-controlled release, while the latter one in a reaction-controlled delivery. The crossover regime is exactly described by their sum. The obtained result for the average release time is verified by direct numerical integration through the drug release profiles of the analytical solution. The value of fractional drug release at the characteristic average time is between 60-64%. These results can be used for the design of polymer-drug conjugates with a desired delivery time scale, as well as for the experimental determination of the values of microscopic parameters D and k in a conjugated system of interest.

Recent Review on Biological Barriers and Host-Material Interfaces in Precision Drug Delivery: Advancement in Biomaterial Engineering for Better Treatment Therapies

Preclinical and clinical studies have demonstrated that precision therapy has a broad variety of treatment applications, making it an interesting research topic with exciting potential in numerous sectors. However, major obstacles, such as inefficient and unsafe delivery systems and severe side effects, have impeded the widespread use of precision medicine. The purpose of drug delivery systems (DDSs) is to regulate the time and place of drug release and action. They aid in enhancing the equilibrium between medicinal efficacy on target and hazardous side effects off target. One promising approach is biomaterial-assisted biotherapy, which takes advantage of biomaterials' special capabilities, such as high biocompatibility and bioactive characteristics. When administered via different routes, drug molecules deal with biological barriers; DDSs help them overcome these hurdles. With their adaptable features and ample packing capacity, biomaterial-based delivery systems allow for the targeted, localised, and prolonged release of medications. Additionally, they are being investigated more and more for the purpose of controlling the interface between the host tissue and implanted biomedical materials. This review discusses innovative nanoparticle designs for precision and non-personalised applications to improve precision therapies. We prioritised nanoparticle design trends that address heterogeneous delivery barriers, because we believe intelligent nanoparticle design can improve patient outcomes by enabling precision designs and improving general delivery efficacy. We additionally reviewed the most recent literature on biomaterials used in biotherapy and vaccine development, covering drug delivery, stem cell therapy, gene therapy, and other similar fields; we have also addressed the difficulties and future potential of biomaterial-assisted biotherapies.

ROS-responsive celastrol-nanomedicine alleviates inflammation for dry eye disease

Dry eye disease (DED) is a major global eye disease leading to severe eye discomfort and even vision impairment. The incidence of DED has been gradually increasing with the high frequency of use of electronic devices. It has been demonstrated that celastrol (Cel) has excellent therapeutic efficacy in ocular disorders. However, the poor water solubility and short half-life of Cel limit its further therapeutic applications. In this work, a reactive oxygen species (ROS) sensitive polymeric micelle was fabricated for Cel delivery. The micelles improve the solubility of Cel, and the resulting Cel loaded micelles exhibit an enhanced intervention effect for DED. Thein vitroresults demonstrated that Cel-nanomedicine had a marked ROS responsive release behavior. The results ofin vitroandin vivoexperiments demonstrated that Cel has excellent biological activities to alleviate inflammation in DED by inhibiting TLR4 signaling activation and reducing pro-inflammatory cytokine expression. Therefore, the Cel nanomedicine can effectively eliminate ocular inflammation, promote corneal epithelial repair, and restore the number of goblet cells and tear secretion, providing a new option for the treatment of DED.

Mathematical Modeling of Drug Delivery from Bi-Layered Core-Shell Polymeric Microspheres

Chronic diseases usually require repetitive dosing. Depending on factors such as dosing frequency, mode of administration, and associated costs this can result in poor patient compliance. A better alternative involves using drug delivery systems to reduce the frequency of dosing and extend drug release. However, reaching the market stage is a time-consuming process. In this study, we used two numerical approaches for estimating the values of the critical parameters that govern the diffusion-controlled drug release within bilayered core-shell microspheres. Specifically, the estimated parameters include burst release, drug diffusion coefficient in two polymers, and the drug partition coefficient. Estimating these parameters provides insight for optimizing device design, guiding experimental efforts, and improving the device's effectiveness. We obtained good agreement between the models and the experimental data. The methods explored in this work apply not only to bi-layered spherical systems but can also be extended to multi-layered spherical systems.