Coupling kinetic and techno-economic models reveals hidden biodesign targets

Metabolic and bioprocess engineering aim to achieve high fermentation titer, rate and yield (TRY), yet no general framework connects these interdependent metrics to facility-scale economics. We introduce NSKinetics, an agile computational framework embedding biochemically structured kinetic models within facility-scale process simulation, techno-economic analysis, uncertainty analysis, global sensitivity analysis, and optimization. We find that for yeast-based ethanol and isobutanol production in a corn biorefinery, cost uncertainty for today's technology is governed by scale, feedstock price, and co-product value rather than ethanol fermentation kinetics. Nonintuitively, while eliminating ethanol inhibition enables a 3.7-fold increase in ethanol productivity, it makes the facility unprofitable by diverting too much carbon to cell growth. Across eight Bayesian optimization campaigns over 12 enzyme-expression, tolerance, and substrate-feeding decisions, TRY-optimized strains were poorly profitable, and a profitability-only campaign stalled at an ethanol-only optimum (15.8% internal rate of return, IRR). However, combining the approaches with a profitability campaign informed by the TRY campaigns' exploration revealed the potential to engineer an ethanol-isobutanol co-producing strain with 27.3% IRR. Fermentation metrics are therefore insufficient proxies for profitability, but valuable guides across the rugged profitability landscape.