Computational modelling has become an integral component of modern cardiovascular research, from academia to industry. Beyond their predictive capabilities, simulations now play a central role in shaping scientific investigation: generating hypotheses that can be tested experimentally and providing frameworks to interpret resulting data. Crucially, computer models are valuable not only when they agree with experimental data, but also when they disagree. Such discrepancies are often the most informative, revealing gaps in our current understanding of complex physiological systems.

To demonstrate the benefits of integrated dry-and-wet-lab approaches, I will focus on two areas. First, I will argue that improving data quality is currently more critical than improving computer models for better in silico drug safety and efficacy studies, and propose a strategy whereby computer models actively guide new data acquisition. Second, I will demonstrate how simulations and experiments can be used synergistically to maximise relevance of animal and in vitro models for human health, enhancing both mechanistic understanding and translational value.

I will conclude by outlining key future directions for integrated dry-wet lab studies, including the development of more general and life-like virtual cells, bridging subcellular to tissue phenomena, and the integration of physiology-based modelling with emerging AI-driven approaches.