Topical Solution for Retinal Delivery: Bevacizumab and Ranibizumab Eye Drops in Anti-Aggregation Formula (AAF) in Rabbits.

PURPOSE: Wet age-related macular degeneration (AMD) is a blinding retinal disease. Monthly intravitreal anti-VEGF antibody injections of bevacizumab (off-label) and ranibizumab (FDA approved) are the standard of care. Antibody aggregation may interfere with ocular absorption/distribution. This study assessed topical delivery of dilute antibodies to the posterior segment of rabbit eyes using a novel anti-aggregation formula (AAF). METHODS: Bevacizumab, or biosimilar ranibizumab was diluted to 5 mg/ml in AAF. All rabbits were dosed twice daily. Substudy 1 rabbits (bevacizumab, 100 µl eye drops): Group 1 (bevacizumab/AAF, n = 6); Group 2 (bevacizumab/PBS, n = 7) and Vehicle control (AAF, n = 1). Substudy 2 rabbits (ranibizumab biosimilar/AAF, 50 µl eye drops): (ranibizumab biosimilar/AAF, n = 8). At 14.5 days, serum was drawn from rabbits. Aqueous, vitreous and retina samples were recovered from eyes and placed into AAF aliquots. Tissue analyzed using AAF as diluent. RESULTS: Bevacizumab in AAF permeated/accumulated in rabbit aqueous, vitreous and retina 10 times more, than when diluted in PBS. AAF/0.1% hyaluronic acid eye drops, dosed twice daily, provided mean tissue concentrations (ng/g) in retina (29.50), aqueous (12.34), vitreous (3.46), and serum (0.28 ng/ml). Additionally, the highest concentration (ng/g) of ranibizumab biosimilar was present in the retina (18.0), followed by aqueous (7.82) and vitreous (1.47). Serum concentration was negligible (< 0.04 ng/ml). No irritation was observed throughout the studies. CONCLUSIONS: Bevacizumab and ranibizumab, in an AAF diluent eye drop, can be delivered to the retina, by the twice daily dosing of a low concentration mAb formulation. This may prove to be an adjunct to intravitreal injections.

Spatial-Temporal Speckle Variance in the En-Face View as a Contrast for Optical Coherence Tomography Angiography (OCTA).

Optical Coherence Tomography (OCT) is an adaptable depth-resolved imaging modality capable of creating a non-invasive 'digital biopsy' of the eye. One of the latest advances in OCT is optical coherence tomography angiography (OCTA), which uses the speckle variance or phase change in the signal to differentiate static tissue from blood flow. Unlike fluorescein angiography (FA), OCTA is contrast free and depth resolved. By combining high-density scan patterns and image processing algorithms, both morphometric and functional data can be extracted into a depth-resolved vascular map of the retina. The algorithm that we explored takes advantage of the temporal-spatial relationship of the speckle variance to improve the contrast of the vessels in the en-face OCT with a single frame. It also does not require the computationally inefficient decorrelation of multiple A-scans to detect vasculature, as used in conventional OCTA analysis. Furthermore, the spatial temporal OCTA (ST-OCTA) methodology tested offers the potential for post hoc analysis to improve the depth-resolved contrast of specific ocular structures, such as blood vessels, with the capability of using only a single frame for efficient screening of large sample volumes, and additional enhancement by processing with choice of frame averaging methods. Applications of this method in pre-clinical studies suggest that the OCTA algorithm and spatial temporal methodology reported here can be employed to investigate microvascularization and blood flow in the retina, and possibly other compartments of the eye.

Semi-automated micro-computed tomography lung segmentation and analysis in mouse models.

Computed Tomography (CT) is a standard clinical tool utilized to diagnose known lung pathologies based on established grading methods. However, for preclinical trials and toxicity investigations in animal models, more comprehensive datasets are typically needed to determine discriminative features between experimental treatments, which oftentimes require analysis of multiple images and their associated differential quantification using manual segmentation methods. Furthermore, for manual segmentation of image data, three or more readers is the gold standard of analysis, but this requirement can be time-consuming and inefficient, depending on variability due to reader bias. In previous papers, microCT image manual segmentation was a valuable tool for assessment of lung pathology in several animal models; however, the manual segmentation approach and the commercial software used was typically a major rate-limiting step. To improve the efficiency, the semi-manual segmentation method was streamlined, and a semi-automated segmentation process was developed to produce:•Quantifiable segmentations: using manual and semi-automated analysis methods for assessing experimental injury and toxicity models,•Deterministic results and efficiency through automation in an unbiased and parameter free process, thereby reducing reader variance, user time, and increases throughput in data analysis,•Cost-Effectiveness: portable with low computational resource demand, based on a cross-platform open-source ImageJ program.