LAUSR

Purpose of review We comprehensively examined recent advancements in developing novel cognitive measures that could significantly enhance detection of outcome changes in Alzheimer's disease clinical trials. Previously established measures were largely limited in their ability to detect subtle cognitive declines in preclinical stages of Alzheimer's disease, particularly due to weak psychometric properties (including practice effects and ceiling effects) and requirement of in-person visits that impacted ascertainment. Recent findings We present novel cognitive measures that were designed to exhibit reduced practice effects and stronger correlations with Alzheimer's disease biomarkers. In addition, we summarized some recent efforts in developing remote testing measures protocols that are aimed to overcome the limitations and inconvenience of in-person testing, and digital phenotyping, which analyses subtle forms of digital behaviour indicative of cognitive phenotypes. We discuss each measure's prognostic accuracy and potential utility in Alzheimer's disease research while also commenting on their limitations. We also describe our study, the Development of Novel Measures for Alzheimer's Disease Prevention Trials (NoMAD), that employed a parallel group design in which novel measures and established measures are compared in a clinical trials armature. Summary Overall, we believe that these recent developments offer promising improvements in accurately detecting clinical and preclinical cognitive changes in the Alzheimer's disease spectrum; however, further validation of their psychometric properties and diagnostic accuracies is warranted before reliably implementing these novel measures in Alzheimer's disease clinical trials.