Case Study: Hoxton Farms achieves faster, scalable cultivated-fat R&D with Benchling

Creating a sustainable future by applying machine learning to cultivated fat R&D

Hoxton Farms is a London-based food-tech company developing cruelty-free, cultivated fats to combine with plant protein and create realistic meat alternatives. Their R&D challenge was to drive down cell-culture costs and increase yield at scale while managing massive, non‑siloed datasets, tracking reagents and cell lineages across experiments, and reducing time lost to manual, ad hoc data entry — all so machine-learning workflows could reliably generate and test new experiments.

Hoxton Farms implemented Benchling across R&D to standardize data capture, customize schemas, and centralize data as a single source of truth. Automated analysis and 200+ Insights dashboards gave teams fast, cross-functional visibility, improving data quality, enabling general machine-learning models, and freeing scientists to run and analyze experiments. The result: increased efficiency, better-informed optimization of processes, and progress toward scalable, cost‑effective bioprocessing.

Hoxton Farms

Ed Steele

Co-Founder