Neural networks speed up simulations of engineered bacteria in fermentation tanks

Researchers replaced slow mathematical calculations with neural networks to make computer simulations of how engineered bacteria metabolize nutrients run faster and more reliably. This matters because biotech companies need to simulate fermentation processes thousands of times to optimize production, and this approach removes a major computational bottleneck that previously made some simulations fail entirely.

For the first time, genome-scale metabolic models—which describe all the biochemical reactions inside a cell—can be embedded directly into dynamic bioreactor simulations without causing numerical crashes or requiring researchers to wait hours for results; this removes a barrier that has kept these detailed models confined to static analysis rather than real-time optimization.