People with type 1 diabetes mellitus rely on a basal-bolus insulin regimen to roughly emulate how a non-diabetic person’s body delivers insulin. Adjusting such regime is a challenging process usually conducted by an expert clinical. Despite several guidelines exist for such purpose, they are usually impractical and fall short in achieving optimal glycemic outcomes. Therefore, there is a need for more automated and efficient strategies to adjust such regime. This paper presents, and in silico validates, a novel technique to automatically adapt the basal insulin profile of a person with person with type 1 diabetes. The presented technique, which is based on Run-to-Run control and Case-Based Reasoning, overcomes some of the limitations of previously proposed approaches and has been proved to be robust in front of realistic intra-day variability. Over a period of 5 weeks on 10 virtual adult subjects, a significant reduction on the percentage of time in hyperglycemia (180mg/dl) (from 10.2±5.9 to 1.6±1.7, p=0.1), was achieved
