Standard computational models of disease rely on population-level data and average tissue parameters. The problem is that individual patients don't behave like averages. Microfluidic organ-on-chip systems generate patient-specific, dynamic biological data at the tissue and cellular level that conventional in vitro models can't provide. That data is exactly what VHT models need to become genuinely patient-specific rather than just demographically adjusted.

• For example, in building a VHT for a patient with cardiovascular disease coupled with a chronic inflammatory disease; in order to obtain blood vessel wall responses to that specific patient's immune system, that patient's cells will be used to seed a vascular chip, and an experiment performed, yielding calibrating data which cannot be generated in any other way in silico.
• Multi-organ coupling requires interface data: gut-liver and kidney-cardiovascular interactions cannot be reasonably simulated computationally, without measurements of transference parameters, which can be obtained in an organ-specific, controlled, and reproducible manner through multi-organ microfluidics, under variable experimental conditions.
• Microfluidics could also play an important role in validation, so that prior to human trials, your consortium will have tested if the VHT's predictions regarding drug response or disease development can be supported by observing the response of actual tissue under physiological challenge; results will be repeatable.
• With regard to use case in rare diseases: small patient populations and lack of longitudinal data can lead to difficulties with model training and validation with clinical data, something a chip model can potentially address where VHT literature largely ignores this; this gap would also be significant for any potential consortium.

Microfluidics is not a substitute for the computational core of a VHT but would make for a stronger proposal by bridging an experimental (chip) and computational (model) system, using data rather than estimates. MIC could act as a bridge between the chip and the model in a consortium geared toward clinical validation.