Building on the success of anti-vascular endothelial growth factor therapy: a vision for the next decade

Eye (Lond). 2020 Nov;34(11):1966-1972. doi: 10.1038/s41433-020-0895-z. Epub 2020 Jun 15.

Abstract

This article aims to identify key opportunities for improvement in the diagnosis and treatment of retinal disease, and describe recent innovations that will potentially facilitate improved outcomes with existing intravitreal vascular endothelial growth factor (VEGF) therapies and lay the groundwork for new treatment approaches. The review begins with a summary of the key discoveries that led to the development of anti-VEGF therapies and briefly reviews their impact on clinical practice. Opportunities for improvements in diagnosis, real-world outcomes with existing therapies, long-acting therapeutics and personalised health care are discussed, as well as the need to identify new targets for therapeutic intervention. Low-cost, remote patient screening and monitoring using artificial intelligence (AI)-based technologies can help improve diagnosis rates and enable remote disease monitoring with minimal patient burden. AI-based tools can be applied to generate patient-level prognostic data and predict individual treatment needs, reducing the time needed to optimise a patient's treatment regimen. Long-acting therapeutics can help improve visual outcomes by reducing the treatment burden. When paired with AI-generated prognoses, long-acting therapeutics enable the possibility of vision loss prevention. Dual-acting drugs may help improve efficacy and/or durability beyond what is possible with anti-VEGF agents alone. Recent developments and ongoing innovations will help build upon the success of anti-VEGF therapies to further reduce vision loss owing to retinal disease while lowering the overall burden of care.

摘要: 本文旨在挖掘提高视网膜疾病诊断和治疗方面的契机, 描述了近年来可能有助于改善现有玻璃体腔内注射血管内皮生长因子 (vascular endothelial growth factor, VEGF) 治疗结局的新思路, 以及它们如何为今后新的治疗奠定基础。本综述首先概述了促使抗VEGF治疗实现临床转化过程中一些关键性发现, 并简要回顾了它们对临床实践的影响。本文也讨论了如何提高诊断、现有治疗的真实世界结局、长效以及个体化治疗策略, 以及确定治疗干预目标的必要性。利用人工智能 (artificial intelligence, AI) 技术的低成本、远程患者筛查和监测功能有助于提高诊断效率, 以最小的患者负担成本实现远程疾病监测。AI设备可提供患者的疾病预后数据以及预测个体治疗的需求, 减少优化患者治疗方案所需的时间。长效治疗通过减轻治疗负担改善视力结局。长效治疗与AI提供的患者预后相结合可预防视力丧失。与抗VEGF单药治疗相较, 联合治疗药物有助于提高疗效和/或持久性。近年来的不断发展以及创新将有助于在抗VEGF治疗成功的基础上, 进一步减少视网膜疾病所致的视力损失, 同时降低总体医疗负担。.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Angiogenesis Inhibitors / therapeutic use
  • Artificial Intelligence
  • Bevacizumab
  • Humans
  • Ranibizumab*
  • Vascular Endothelial Growth Factor A*

Substances

  • Angiogenesis Inhibitors
  • Vascular Endothelial Growth Factor A
  • Bevacizumab
  • Ranibizumab