TREAT-AND-EXTEND REGIMENS WITH ANTI-VEGF AGENTS IN RETINAL DISEASES: A Literature Review and Consensus Recommendations

PURPOSE A review of treat-and-extend regimens (TERs) with intravitreal anti-vascular endothelial growth factor agents in retinal diseases. METHODS There is a lack of consensus on the definition and optimal application of TER in clinical practice. This article describes the supporting evidence and subsequent development of a generic algorithm for TER dosing with anti-vascular endothelial growth factor agents, considering factors such as criteria for extension. RESULTS A TER algorithm was developed; TER is defined as an individualized proactive dosing regimen usually initiated by monthly injections until a maximal clinical response is observed (frequently determined by optical coherence tomography), followed by increasing intervals between injections (and evaluations) depending on disease activity. The TER regimen has emerged as an effective approach to tailoring the dosing regimen and for reducing treatment burden (visits and injections) compared with fixed monthly dosing or monthly visits with optical coherence tomography-guided regimens (as-needed or pro re nata). It is also considered a suitable approach in many retinal diseases managed with intravitreal anti-vascular endothelial growth factor therapy, given that all eyes differ in the need for repeat injections. CONCLUSION It is hoped that this practical review and TER algorithm will be of benefit to health care professionals interested in the management of retinal diseases.

TrypanoCyc: a community-led biochemical pathways database for Trypanosoma brucei.

The metabolic network of a cell represents the catabolic and anabolic reactions that interconvert small molecules (metabolites) through the activity of enzymes, transporters and non-catalyzed chemical reactions. Our understanding of individual metabolic networks is increasing as we learn more about the enzymes that are active in particular cells under particular conditions and as technologies advance to allow detailed measurements of the cellular metabolome. Metabolic network databases are of increasing importance in allowing us to contextualise data sets emerging from transcriptomic, proteomic and metabolomic experiments. Here we present a dynamic database, TrypanoCyc (http://www.metexplore.fr/trypanocyc/), which describes the generic and condition-specific metabolic network of Trypanosoma brucei, a parasitic protozoan responsible for human and animal African trypanosomiasis. In addition to enabling navigation through the BioCyc-based TrypanoCyc interface, we have also implemented a network-based representation of the information through MetExplore, yielding a novel environment in which to visualise the metabolism of this important parasite.