Streamlining the Design‐Build‐Test‐Learn Process in Automated Biofoundries

View at publisher
Authors: Enrico Orsi, Nicolás Gurdo, Pablo I. Nikel
Cited by: 1
References: 150

Abstract

Bioengineering is increasingly contributing to solving societal challenges in biomedical, environmental, agricultural, and industrial setups. To facilitate standardization of bioengineering, the field has adopted the concept of design-build-test-learn cycles (DBTLc) from engineering. The DBTLc offers the advantages of being both modular and iterative, allowing it to be automated and scaled for high throughput. In this chapter, we provide an overview of how the DBTLc has evolved from a low-throughput, ad hoc system used in early bioengineering campaigns into a fully scalable and automatable paradigm of synthetic biology and metabolic engineering. The chapter begins with an overview of the DBTLc, explaining how it can be automated in biofoundries – specialized infrastructures for high-throughput bioengineering. Then, we present an analysis of the global distribution of biofoundries, followed by a discussion on current challenges in streamlining their workflows and, finally, the future perspectives for their realization.

Publication details

Journal / source
Machine Learning and Big Data‐enabled Biotechnology
Publisher
Wiley
Pages
341–366
Publication date
9 January 2026
Language
EN