Integration of multi-modal monitoring for dynamic control of large-scale 3D tissue bioreactors

The translation of tissue engineering toward clinically relevant large-scale biofabrication requires continuous and non-invasive monitoring of tissue maturation. However, few studies provide an integrated and operational demonstration of how such tracking can be effectively achieved in real bioreactor environments. Here, we propose and experimentally validate a modular analytical framework that integrates physicochemical, metabolic, morphological, and perfusion monitoring strategies designed for centimeter-scale engineered tissues cultivated under perfusion. A custom perfusion bioreactor system was developed for the cultivation of 10 cm³ bioprinted fibroblast tissues, featuring real-time online monitoring of the physicochemical environment-i.e., temperature, pH, and O₂ content-thanks to dedicated probes, and metabolic assessment using Raman spectroscopy. Dual-gas PID (Proportional, Integral, Derivative) regulation improved oxygen control accuracy, with deviations reduced from 128% to 22%. Our online Raman probe was implemented to quantify lactic acid secretion as a first proof of concept for monitoring secreted metabolites, with a prediction error of 0.103 g L^-1. Additionally, tissue morphological evolution was non-destructively tracked by 7 Tesla MRI. This allowed us to measure, for the first time, the percentage of geometrical fidelity to the biofabrication-designed CAD model during tissue cultivation, which in our case was 87.6%, and to reveal internal tissue remodelling. Nutritive fluid perfusion, mapped either by CFD simulation or real measurements through MRI velocimetry, confirmed heterogeneous flow patterns and internal distribution. Altogether, these results demonstrate that combining established analytical modalities within a unified workflow enables quantitative, real-time characterisation of tissue maturation. This approach bridges the classical bioprocess monitoring with emerging tissue biofabrication workflows, paving the way for adaptive, feedback-driven control of tissue cultivation.