Systematic Living Evidence for Clinical Trials (SyLECT): a data-driven framework for drug selection in clinical trials in motor neuron disease

Despite many promising preclinical studies and decades of clinical trials, there remains a paucity of effective disease-modifying drugs in motor neuron disease. We aimed to develop a systematic and structured data-driven framework to identify, evaluate and prioritise candidate drugs for clinical trials, specifically for the Motor Neuron Disease-Systematic Multi-Arm Adaptive Randomised Trial (MND-SMART; NCT040302870). We developed the Systematic Living Evidence for Clinical Trials (SyLECT) platform as a modular framework integrating emerging data from different domains to inform prioritisation of candidate drugs. Current domains incorporated include published clinical, animal in vivo, and in vitro literature; in house in vitro high throughput drug screening; pathway and network analysis; and pharmacological, feasibility and clinical trial data from drug, chemical, and clinical trial databases. In this approach, we first identify a list of candidate drugs from these domains then select drugs for further consideration based on drug properties, feasibility, and expert opinion. For prioritised drugs we then generate, evaluate, and synthesise further evidence from across data domains. Using automated workflows and interactive web applications, we produce snapshot “living evidence summaries” to inform expert panel decisions on prioritisation of candidate drugs for MND-SMART. The third drug selected for MND-SMART and the first using this framework is amantadine. We demonstrated the feasibility of a systematic data-driven framework to inform prioritisation of candidate drugs for clinical trials in motor neuron disease, with potential for wider application across diseases where there is unmet clinical need.