To overcome these barriers, this work argues for standardized protocols in model design, calibration and validation, alongside enhanced data collection and reconciliation efforts. Integrating innovative approaches, such as metabolic modelling, machine learning and hybrid modelling into digital twins, will be essential to unlock the full potential of phototrophic systems, bridging the gap between theoretical models and industrial implementation.