dc.creator | Ibáñez Espinel, Francisco | |
dc.creator | Puentes Cantor, Hernán Felipe | |
dc.creator | Barzaga Martell, Lisbel | |
dc.creator | Saa Higuera, Pedro | |
dc.creator | Agosin Trumper, Eduardo | |
dc.creator | Perez Correa, José Ricardo | |
dc.date.accessioned | 2024-05-08T17:20:57Z | |
dc.date.accessioned | 2024-07-17T21:27:14Z | |
dc.date.available | 2024-05-08T17:20:57Z | |
dc.date.available | 2024-07-17T21:27:14Z | |
dc.date.created | 2024-05-08T17:20:57Z | |
dc.date.issued | 2024 | |
dc.identifier | 10.1016/j.compchemeng.2024.108706 | |
dc.identifier | https://doi.org/10.1016/j.compchemeng.2024.108706 | |
dc.identifier | https://repositorio.uc.cl/handle/11534/85511 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/9509895 | |
dc.description.abstract | Fed-batch cultures are the preferred operation mode for industrial bioprocesses requiring high cellular densities. Avoids accumulation of major fermentation by-products due to metabolic overflow, increasing process productivity. Reproducible operation at high cell densities is challenging (> 100 gDCW/L), which has precluded rigorous model evaluation. Here, we evaluated three phenomenological models and proposed a novel hybrid model including a neural network. For this task, we generated highly reproducible fedbatch datasets of a recombinant yeast growing under oxidative, oxygen-limited, and respiro-fermentative metabolic regimes. The models were reliably calibrated using a systematic workflow based on pre-and post-regression diagnostics. Compared to the best-performing phenomenological model, the hybrid model substantially improved performance by 3.6- and 1.7-fold in the training and test data, respectively. This study illustrates how hybrid modeling approaches can advance our description of complex bioprocesses that could support more efficient operation strategies | |
dc.language | en | |
dc.rights | acceso restringido | |
dc.subject | Hybrid models | |
dc.subject | Dynamic optimization | |
dc.subject | High-density cultures | |
dc.subject | Overflow metabolism | |
dc.subject | Fed-batch fermentation | |
dc.subject | Physics-informed neural networks | |
dc.title | Reliable calibration and validation of phenomenological and hybrid models of high-cell-density fed-batch cultures subject to metabolic overflow | |
dc.type | artículo | |