Systems engineering of engineered live biotherapeutics: A discovery-to-translation framework for streamlining...

Despite the vast opportunities for therapeutic manipulation of the gut microbiome, recent late-stage clinical failures of engineered live biotherapeutic products (eLBPs) highlight critical knowledge gaps in ecological barriers and community dynamics. In this review, we propose repurposing the current eLBP toolkit as a set of discovery instruments that yield quantitative outputs for predictive modeling. We examine cutting-edge approaches in microbiome engineering and outline opportunities for their use in tandem with systems engineering methodology to conduct functional probing that establishes quantitative parameters describing community resilience, metabolic flux, and host-microbe interactions. Next, in light of FDA guidance on New Approach Methodologies, we detail how in silico and in vitro modeling approaches can be combined and leveraged not only for a priori triage of unviable designs, but can also be integrated into design-build-test-learn (DBTL) pipelines for functional forecasting. Building off an emerging cellular kinetics/pharmacodynamics (CK/PD) framework, we develop a Bayesian updating workflow that encapsulates eLBP-adapted equivalents of pharmacological parameters such as Cmax, Tmax, and AUC. Further, we adapt this framework for adaptive or prospective use, rather than purely retrospective application, supporting trial design rather than post-hoc analysis. This approach repositions eLBP development from an empirical, intuition-based process toward a predictive, model-informed pipeline that aligns with emerging regulatory frameworks.