Optimized glycemic control of type 2 diabetes with reinforcement learning: a proof-of-concept trial.

The personalized titration and optimization of insulin regimens for treatment of type 2 diabetes (T2D) are resource-demanding healthcare tasks. Here we propose a model-based reinforcement learning (RL) framework (called RL-DITR), which learns the optimal insulin regimen by analyzing glycemic state rewards through patient model interactions. When evaluated during the development phase for managing hospitalized patients with T2D, RL-DITR achieved superior insulin titration optimization (mean absolute error (MAE) of 1.10 ± 0.03 U) compared to other deep learning models and standard clinical methods. We performed a stepwise clinical validation of the artificial intelligence system from simulation to deployment, demonstrating better performance in glycemic control in inpatients compared to junior and intermediate-level physicians through quantitative (MAE of 1.18 ± 0.09 U) and qualitative metrics from a blinded review. Additionally, we conducted a single-arm, patient-blinded, proof-of-concept feasibility trial in 16 patients with T2D. The primary outcome was difference in mean daily capillary blood glucose during the trial, which decreased from 11.1 (±3.6) to 8.6 (±2.4) mmol L-1 (P < 0.01), meeting the pre-specified endpoint. No episodes of severe hypoglycemia or hyperglycemia with ketosis occurred. These preliminary results warrant further investigation in larger, more diverse clinical studies. ClinicalTrials.gov registration: NCT05409391 .

The Role of Inflammation in Age-Related Macular Degeneration-Therapeutic Landscapes in Geographic Atrophy.

Age-related macular degeneration (AMD) is the leading cause of vision loss and visual impairment in people over 50 years of age. In the current therapeutic landscape, intravitreal anti-vascular endothelial growth factor (anti-VEGF) therapies have been central to the management of neovascular AMD (also known as wet AMD), whereas treatments for geographic atrophy have lagged behind. Several therapeutic approaches are being developed for geographic atrophy with the goal of either slowing down disease progression or reversing sight loss. Such strategies target the inflammatory pathways, complement cascade, visual cycle or neuroprotective mechanisms to slow down the degeneration. In addition, retinal implants have been tried for vision restoration and stem cell therapies for potentially a dual purpose of slowing down the degeneration and restoring visual function. In particular, therapies focusing on the complement pathway have shown promising results with the FDA approved pegcetacoplan, a complement C3 inhibitor, and avacincaptad pegol, a complement C5 inhibitor. In this review, we discuss the mechanisms of inflammation in AMD and outline the therapeutic landscapes of atrophy AMD. Improved understanding of the various pathway components and their interplay in this complex neuroinflammatory degeneration will guide the development of current and future therapeutic options, such as optogenetic therapy.

Deep-learning-enabled protein-protein interaction analysis for prediction of SARS-CoV-2 infectivity and variant evolution.

Host-pathogen interactions and pathogen evolution are underpinned by protein-protein interactions between viral and host proteins. An understanding of how viral variants affect protein-protein binding is important for predicting viral-host interactions, such as the emergence of new pathogenic SARS-CoV-2 variants. Here we propose an artificial intelligence-based framework called UniBind, in which proteins are represented as a graph at the residue and atom levels. UniBind integrates protein three-dimensional structure and binding affinity and is capable of multi-task learning for heterogeneous biological data integration. In systematic tests on benchmark datasets and further experimental validation, UniBind effectively and scalably predicted the effects of SARS-CoV-2 spike protein variants on their binding affinities to the human ACE2 receptor, as well as to SARS-CoV-2 neutralizing monoclonal antibodies. Furthermore, in a cross-species analysis, UniBind could be applied to predict host susceptibility to SARS-CoV-2 variants and to predict future viral variant evolutionary trends. This in silico approach has the potential to serve as an early warning system for problematic emerging SARS-CoV-2 variants, as well as to facilitate research on protein-protein interactions in general.

PHOTORECEPTOR DAMAGE IN TERSON SYNDROME.

PURPOSE: To describe photoreceptor damage in patients with Terson syndrome as a potential cause for inconsistent clinical outcomes. METHODS: Clinical evaluation and retinal imaging in six patients. RESULTS: Four patients were women and two men, with an average age of 46.8 years (SD 8.9). Four patients suffered aneurysmal subarachnoid hemorrhage, one vertebral artery dissection, and one superior sagittal sinus thrombosis. In 11 eyes, a consistent pattern of outer retinal changes within the central retina affecting the ellipsoid zone and the outer nuclear layer was observed, indicating photoreceptor damage. Areas of photoreceptor damage showed poor spatial correlation with intraocular hemorrhage, particularly subinternal limiting membrane hemorrhage. The observed retinal abnormalities demonstrated incomplete recovery over long-term follow-up 3.5 to 8 years posthemorrhage, irrespective of surgical or conservative treatment strategy, and had variable impact on the patients' visual function. CONCLUSION: The observations suggest that photoreceptor damage in Terson syndrome likely represents a distinct manifestation of this condition, which could be caused by transient ischemia of the outer retina secondary to acute rise in intracranial pressure.

Erratum: Enhancement of Adeno-Associated Virus-Mediated Gene Therapy Using Hydroxychloroquine in Murine and Human Tissues.

[This corrects the article DOI: 10.1016/j.omtm.2019.05.012.].

A Network Meta-Analysis of Retreatment Rates following Bevacizumab, Ranibizumab, Aflibercept, and Laser for Retinopathy of Prematurity.

TOPIC: To compare bevacizumab, ranibizumab, aflibercept, and laser treatment as primary therapies for retinopathy of prematurity (ROP) in terms of retreatment rate. CLINICAL RELEVANCE: Anti-VEGF agents are increasingly used as primary treatment for ROP and may provide superior outcomes compared with laser in posterior disease. Head-to-head comparisons between different anti-VEGFs are lacking. METHODS: We searched CENTRAL, Embase, MEDLINE, and CINAHL databases for randomized controlled trials and nonrandomized comparative studies that had been reported as of March 2022. We included studies that used bevacizumab, ranibizumab, aflibercept or laser for ROP with comparable cohorts and treatment criteria. Studies were evaluated by the Grading of Recommendations, Assessment, Development and Evaluation framework, and those with biased case selection, nonrandomized case-control, or lack of control group were excluded. Frequentist meta-analyses of proportions determined the absolute primary retreatment rate of each modality and Bayesian network meta-analyses compared pairs of treatments in type 1 and Zone I ROP. RESULTS: In all, 30 studies (4686 eyes) were included in the network meta-analyses. For type 1 ROP, single-treatment success rates (i.e., likelihood of needing no further treatment) were 89.3% (95% confidence interval [CI]: 83.8%-93.8%; n = 1552) for laser, 87.0% (95% CI: 78.6%-93.8%; n = 2081) for bevacizumab, 80.7% (95% CI: 62.0%-94.4%; n = 326) for aflibercept, and 74.0% (95% CI: 62.7%-84.1%; n = 727) for ranibizumab. Bayesian network meta-analysis indicates that laser treatment is associated with a significant 62% (95% credible interval [CrI]: 16%-83%) reduction in retreatment risk compared with ranibizumab, while no significant difference was found among other pairwise comparisons. The mean ± standard error of the mean times to secondary treatment following primary aflibercept (12.96 ± 0.47 weeks) and bevacizumab (11.36 ± 0.54 weeks) therapy were significantly longer than that for primary ranibizumab (9.29 ± 0.43weeks) therapy (P = 7 × 10-7 and P = 9 × 10-3, respectively). For Zone I ROP, single-treatment success rates were 91.2% (95% CI: 83.6-96.9; n = 231) for bevacizumab, 78.3% (95% CI: 61.4-91.9; n = 100) for ranibizumab, and 65.9% (95% CI: 41.4-87.2; n = 158) for laser treatment. In this case, Bayesian network meta-analysis suggests that primary bevacizumab is associated with a significant 67% (95% CrI:10%-90%) reduction in retreatment risk compared with laser treatment. CONCLUSIONS: Laser was associated with a lower rate of retreatment than ranibizumab in type 1 ROP (Zones I and II combined), while bevacizumab was associated with a lower rate of retreatment than laser in Zone I ROP. Aflibercept and bevacizumab demonstrate longer duration of action than ranibizumab for ROP.

A deep-learning system predicts glaucoma incidence and progression using retinal photographs.

BackgroundDeep learning has been widely used for glaucoma diagnosis. However, there is no clinically validated algorithm for glaucoma incidence and progression prediction. This study aims to develop a clinically feasible deep-learning system for predicting and stratifying the risk of glaucoma onset and progression based on color fundus photographs (CFPs), with clinical validation of performance in external population cohorts.MethodsWe established data sets of CFPs and visual fields collected from longitudinal cohorts. The mean follow-up duration was 3 to 5 years across the data sets. Artificial intelligence (AI) models were developed to predict future glaucoma incidence and progression based on the CFPs of 17,497 eyes in 9346 patients. The area under the receiver operating characteristic (AUROC) curve, sensitivity, and specificity of the AI models were calculated with reference to the labels provided by experienced ophthalmologists. Incidence and progression of glaucoma were determined based on longitudinal CFP images or visual fields, respectively.ResultsThe AI model to predict glaucoma incidence achieved an AUROC of 0.90 (0.81-0.99) in the validation set and demonstrated good generalizability, with AUROCs of 0.89 (0.83-0.95) and 0.88 (0.79-0.97) in external test sets 1 and 2, respectively. The AI model to predict glaucoma progression achieved an AUROC of 0.91 (0.88-0.94) in the validation set, and also demonstrated outstanding predictive performance with AUROCs of 0.87 (0.81-0.92) and 0.88 (0.83-0.94) in external test sets 1 and 2, respectively.ConclusionOur study demonstrates the feasibility of deep-learning algorithms in the early detection and prediction of glaucoma progression.FUNDINGNational Natural Science Foundation of China (NSFC); the High-level Hospital Construction Project, Zhongshan Ophthalmic Center, Sun Yat-sen University; the Science and Technology Program of Guangzhou, China (2021), the Science and Technology Development Fund (FDCT) of Macau, and FDCT-NSFC.

First-in-Human Robot-Assisted Subretinal Drug Delivery Under Local Anesthesia.

PURPOSE: To report the results of a first-in-human study using a robotic device to assist subretinal drug delivery in patients undergoing vitreoretinal surgery for macular hemorrhage. DESIGN: Double-armed, randomized controlled surgical trial (ClinicalTrials.gov identifier: NCT03052881). METHODS: The study was performed at the Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom. In total, 12 participants were recruited-6 in the robot-assisted and 6 in the control manual surgery arm according to the prespecified inclusion and exclusion criteria. All subjects presented with acute loss of vision owing to a subfoveal hemorrhage secondary to neovascular age-related macular degeneration. After standard vitrectomy, intraoperative optical coherence tomography-guided subretinal injection of tissue plasminogen activator (TPA) was performed by either robot-assisted or conventional manual technique under local anesthesia. The robotic part of the procedure involved advancement of a cannula through the retina and stabilizing it during foot-controlled injection of up to 100 µL of TPA solution. We assessed surgical success, duration of surgery, adverse events, and tolerability of surgery under local anesthesia. RESULTS: The procedure was well tolerated by all participants and safely performed in all cases. Total duration of surgery, time taken to complete the injection, and retinal microtrauma were similar between the groups and not clinically significant. Subretinal hemorrhage was successfully displaced at 1 month postintervention, except for 1 control subject, and the median gain in visual acuity was similar in both arms. CONCLUSIONS: This first-in-human study demonstrates the feasibility and safety of high-precision robot-assisted subretinal drug delivery as part of the surgical management of submacular hemorrhage, simulating its potential future application in gene or cell therapy.

Gene-agnostic therapeutic approaches for inherited retinal degenerations.

Inherited retinal diseases (IRDs) are associated with mutations in over 250 genes and represent a major cause of irreversible blindness worldwide. While gene augmentation or gene editing therapies could address the underlying genetic mutations in a small subset of patients, their utility remains limited by the great genetic heterogeneity of IRDs and the costs of developing individualised therapies. Gene-agnostic therapeutic approaches target common pathogenic pathways that drive retinal degeneration or provide functional rescue of vision independent of the genetic cause, thus offering potential clinical benefits to all IRD patients. Here, we review the key gene-agnostic approaches, including retinal cell reprogramming and replacement, neurotrophic support, immune modulation and optogenetics. The relative benefits and limitations of these strategies and the timing of clinical interventions are discussed.

Characterizing the cellular immune response to subretinal AAV gene therapy in the murine retina.

Although adeno-associated viral (AAV) vector-mediated retinal gene therapies have demonstrated efficacy, the mechanisms underlying dose-dependent retinal inflammation remain poorly understood. Here, we present a quantitative analysis of cellular immune response to subretinal AAV gene therapy in mice using multicolor flow cytometry with a panel of key immune cell markers. A significant increase in CD45+ retinal leukocytes was detected from day 14 post-subretinal injection of an AAV8 vector (1 × 109 genome copies) encoding green fluorescent protein (GFP) driven by a ubiquitous promoter. These predominantly consisted of infiltrating peripheral leukocytes including macrophages, natural killer cells, CD4 and CD8 T cells, and natural killer T cells; no significant change in resident microglia population was detected. This cellular response was persistent at 28 days and suggestive of type 1 cell-mediated effector immunity. High levels (80%) of GFP fluorescence were found in the microglia, implicating their role in viral antigen presentation and peripheral leukocyte recruitment. When compared against AAV.GFP in paired eyes, an equivalent dose of an otherwise identical vector encoding the human therapeutic transgene Rab-escort protein 1 (REP1) elicited a significantly diminished cellular immune response (4.2-fold; p = 0.0221). However, the distribution of immune cell populations remained similar, indicating a common mechanism of AAV-induced immune activation.

Interactions between Apolipoprotein E Metabolism and Retinal Inflammation in Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is a multifactorial retinal disorder that is a major global cause of severe visual impairment. The development of an effective therapy to treat geographic atrophy, the predominant form of AMD, remains elusive due to the incomplete understanding of its pathogenesis. Central to AMD diagnosis and pathology are the hallmark lipid and proteinaceous deposits, drusen and reticular pseudodrusen, that accumulate in the subretinal pigment epithelium and subretinal spaces, respectively. Age-related changes and environmental stressors, such as smoking and a high-fat diet, are believed to interact with the many genetic risk variants that have been identified in several major biochemical pathways, including lipoprotein metabolism and the complement system. The APOE gene, encoding apolipoprotein E (APOE), is a major genetic risk factor for AMD, with the APOE2 allele conferring increased risk and APOE4 conferring reduced risk, in comparison to the wildtype APOE3. Paradoxically, APOE4 is the main genetic risk factor in Alzheimer's disease, a disease with features of neuroinflammation and amyloid-beta deposition in common with AMD. The potential interactions of APOE with the complement system and amyloid-beta are discussed here to shed light on their roles in AMD pathogenesis, including in drusen biogenesis, immune cell activation and recruitment, and retinal inflammation.

Expression of Rab Prenylation Pathway Genes and Relation to Disease Progression in Choroideremia.

Purpose: Choroideremia results from the deficiency of Rab Escort Protein 1 (REP1), encoded by CHM, involved in the prenylation of Rab GTPases. Here, we investigate whether the transcription and expression of other genes involved in the prenylation of Rab proteins correlates with disease progression in a cohort of patients with choroideremia. Methods: Rates of retinal pigment epithelial area loss in 41 patients with choroideremia were measured using fundus autofluorescence imaging for up to 4 years. From lysates of cultured skin fibroblasts donated by patients (n = 15) and controls (n = 14), CHM, CHML, RABGGTB and RAB27A mRNA expression, and REP1 and REP2 protein expression were compared. Results: The central autofluorescent island area loss in patients with choroideremia occurred with a mean half-life of 5.89 years (95% confidence interval [CI] = 5.09-6.70), with some patients demonstrating relatively fast or slow rates of progression (range = 3.3-14.1 years). Expression of CHM mRNA and REP1 protein were significantly decreased in all patients. No difference in expression of CHML, RABGGTB, RAB27A, or REP2 was seen between patients and controls. No correlation was seen between expression of the genes analyzed and rates of retinal degeneration. Non-sense induced transcriptional compensation of CHML, a CHM-like retrogene, was not observed in patients with CHM variants predicted to undergo non-sense mediated decay. Conclusions: Patients with choroideremia, who are deficient for REP1, show normal levels of expression of other genes involved in Rab prenylation, which do not appear to play any modifying role in the rate of disease progression. Translational Relevance: There remains little evidence for selection of patients for choroideremia gene therapy based on genotype.

Safety and Acceptability of a Natural Language Artificial Intelligence Assistant to Deliver Clinical Follow-up to Cataract Surgery Patients: Proposal.

BACKGROUND: Due to an aging population, the demand for many services is exceeding the capacity of the clinical workforce. As a result, staff are facing a crisis of burnout from being pressured to deliver high-volume workloads, driving increasing costs for providers. Artificial intelligence (AI), in the form of conversational agents, presents a possible opportunity to enable efficiency in the delivery of care. OBJECTIVE: This study aims to evaluate the effectiveness, usability, and acceptability of Dora agent: Ufonia's autonomous voice conversational agent, an AI-enabled autonomous telemedicine call for the detection of postoperative cataract surgery patients who require further assessment. The objectives of this study are to establish Dora's efficacy in comparison with an expert clinician, determine baseline sensitivity and specificity for the detection of true complications, evaluate patient acceptability, collect evidence for cost-effectiveness, and capture data to support further development and evaluation. METHODS: Using an implementation science construct, the interdisciplinary study will be a mixed methods phase 1 pilot establishing interobserver reliability of the system, usability, and acceptability. This will be done using the following scales and frameworks: the system usability scale; assessment of Health Information Technology Interventions in Evidence-Based Medicine Evaluation Framework; the telehealth usability questionnaire; and the Non-Adoption, Abandonment, and Challenges to the Scale-up, Spread and Suitability framework. RESULTS: The evaluation is expected to show that conversational technology can be used to conduct an accurate assessment and that it is acceptable to different populations with different backgrounds. In addition, the results will demonstrate how successfully the system can be delivered in organizations with different clinical pathways and how it can be integrated with their existing platforms. CONCLUSIONS: The project's key contributions will be evidence of the effectiveness of AI voice conversational agents and their associated usability and acceptability. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/27227.

CRISPR genome engineering for retinal diseases.

Novel gene therapy treatments for inherited retinal diseases have been at the forefront of translational medicine over the past couple of decades. Since the discovery of CRISPR mechanisms and their potential application for the treatment of inherited human conditions, it seemed inevitable that advances would soon be made using retinal models of disease. The development of CRISPR technology for gene therapy and its increasing potential to selectively target disease-causing nucleotide changes has been rapid. In this chapter, we discuss the currently available CRISPR toolkit and how it has been and can be applied in the future for the treatment of inherited retinal diseases. These blinding conditions have until now had limited opportunity for successful therapeutic intervention, but the discovery of CRISPR has created new hope of achieving such, as we discuss within this chapter.

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidney disease and type 2 diabetes solely from fundus images or in combination with clinical metadata (age, sex, height, weight, body-mass index and blood pressure) with areas under the receiver operating characteristic curve of 0.85-0.93. The models were trained and validated with a total of 115,344 retinal fundus photographs from 57,672 patients and can also be used to predict estimated glomerulal filtration rates and blood-glucose levels, with mean absolute errors of 11.1-13.4 ml min-1 per 1.73 m2 and 0.65-1.1 mmol l-1, and to stratify patients according to disease-progression risk. We evaluated the generalizability of the models for the identification of chronic kidney disease and type 2 diabetes with population-based external validation cohorts and via a prospective study with fundus images captured with smartphones, and assessed the feasibility of predicting disease progression in a longitudinal cohort.

Is subretinal AAV gene replacement still the only viable treatment option for choroideremia?

INTRODUCTION: Choroideremia is an X-linked inherited retinal degeneration resulting from mutations in the CHM gene, encoding Rab escort protein-1 (REP1), a protein regulating intracellular vesicular transport. Loss-of-function mutations in CHM lead to progressive loss of retinal pigment epithelium (RPE) with photoreceptor and choriocapillaris degeneration, leading to progressive visual field constriction and loss of visual acuity. Three hundred and fifty-four unique mutations have been reported in CHM. While gene augmentation remains an ideal therapeutic option for choroideremia, other potential future clinical strategies may exist. AREAS COVERED: The authors examine the pathophysiology and genetic basis of choroideremia. They summarize the status of ongoing gene therapy trials and discuss CHM mutations amenable to other therapeutic approaches including CRISPR/Cas-based DNA and RNA editing, nonsense suppression of premature termination codons, and antisense oligonucleotides for splice modification. The authors undertook a literature search in PubMed and NIH Clinical Trials in October 2020. EXPERT OPINION: The authors conclude that AAV-mediated gene augmentation remains the most effective approach for choroideremia. Given the heterogeneity of CHM mutations and potential risks and benefits, genome-editing approaches currently do not offer significant advantages. Nonsense suppression strategies and antisense oligonucleotides are exciting novel therapeutic options; however, their clinical viability remains to be determined.

Genome-Editing Strategies for Treating Human Retinal Degenerations.

Inherited retinal degenerations (IRDs) are a leading cause of blindness. Although gene-supplementation therapies have been developed, they are only available for a small proportion of recessive IRD mutations. In contrast, genome editing using clustered-regularly interspaced short palindromic repeats (CRISPR) CRISPR-associated (Cas) systems could provide alternative therapeutic avenues for treating a wide range of genetic retinal diseases through targeted knockdown or correction of mutant alleles. Progress in this rapidly evolving field has been highlighted by recent Food and Drug Administration clinical trial approval for EDIT-101 (Editas Medicine, Inc., Cambridge, MA), which has demonstrated efficacious genome editing in a mouse model of CEP290-associated Leber congenital amaurosis and safety in nonhuman primates. Nonetheless, there remains a significant number of challenges to developing clinically viable retinal genome-editing therapies. In particular, IRD-causing mutations occur in more than 200 known genes, with considerable heterogeneity in mutation type and position within each gene. Additionally, there are remaining safety concerns over long-term expression of Cas9 in vivo. This review highlights (i) the technological advances in gene-editing technology, (ii) major safety concerns associated with retinal genome editing, and (iii) potential strategies for overcoming these challenges to develop clinical therapies.

Flying baby optical coherence tomography alters the staging and management of advanced retinopathy of prematurity.

PURPOSE: To report the use of flying baby spectral domain optical coherence tomography (SD-OCT) on infants with advanced retinopathy of prematurity (ROP), where clinical findings alone failed to differentiate between retinoschisis and retinal detachment. METHODS: Prospective, non-interventional case-series study of three premature infants with advanced ROP of clinically uncertain stage, after examination by indirect ophthalmoscopy. To confirm the diagnosis, table-mounted SD-OCT retinal imaging was performed with the infant held in the flying baby position under topical ocular anaesthesia only. Spectral domain optical coherence tomography (SD-OCT) findings were correlated with clinical examination and ultra-widefield scanning laser ophthalmoscopy to determine disease stage and appropriate management. RESULTS: The flying baby position was well tolerated, and SD-OCT images of central and peripheral retina were successfully obtained in all three cases. Additional information provided by the SD-OCT changed the ROP staging from 3 to 4 in one case, which subsequently required surgical treatment. In two other cases, clinical suspicion of stage 4 ROP was overruled as SD-OCT revealed tractional retinoschisis rather than full-thickness retinal detachment, thereby avoiding the need for immediate surgical intervention. CONCLUSIONS: In this case-series study, flying baby SD-OCT provided a rapid and widely accessible imaging approach that overruled clinical findings and altered classification and management of infants with advanced ROP. The methodology was suitable for outpatient settings with no risks associated with systemic anaesthesia. The increased use of OCT imaging will make apparent how structural information is useful in management of ROP and may influence future classification of the disease.

Antisense oligonucleotide therapeutics in clinical trials for the treatment of inherited retinal diseases.

INTRODUCTION: Antisense oligonucleotides (ASOs) represent a class of drugs which can be rationally designed to complement the coding or non-coding regions of target RNA transcripts. They could modulate pre-messenger RNA splicing, induce mRNA knockdown, or block translation of disease-causing genes, thereby slowing disease progression. The pharmacokinetics of intravitreal delivery may enable ASOs to be effective in the treatment of inherited retinal diseases. AREAS COVERED: We review the current status of clinical trials of ASO therapies for inherited retinal diseases, which have demonstrated safety, viable durability, and early efficacy. Future applications are discussed in the context of alternative genetic approaches, including gene augmentation and gene editing. EXPERT OPINION: Early efficacy data suggest that the splicing-modulating ASO, sepofarsen, is a promising treatment for Leber congenital amaurosis associated with the common c.2991+1655A>G mutation in CEP290. However, potential variability in clinical response to ASO-mediated correction of splicing defect on one allele in patients who are compound heterozygotes needs to be assessed. ASOs hold great therapeutic potential for numerous other inherited retinal diseases with common deep-intronic and dominant gain-of-function mutations. These would complement viral vector-mediated gene augmentation which is generally limited by the size of the transgene and to the treatment of recessive diseases.