High-throughput methods leveraging robotics and computer vision for the development of therapeutic phage cocktails

T Taylor J. R. Penke A Aeron Tynes Hammack L Lana J. McMillan E Ethan Baker P Pearl Wilcock N Nick Healy M Morgan K. Y. Wall N Naomi Chavez I Iain Wright H Hannah H. Tuson S Sara Woessner A Ashley Trama C Cameron J. Prybol E Eyra Dordi A Ava Ghobadian D David G. Ousterout N Nicholas R. Conley P Paul Garofolo

Abstract

Abstract We present the high-throughput automated screening techniques that are being used to develop bacteriophage-based therapeutic products currently under investigation in human clinical trials to combat urinary tract infections 1 . By integrating modern liquid handling robotics, standardized phenotypic assays, and computer vision-based enumeration, we established a platform capable of reproducibly screening large collections of phages against clinically derived bacterial strain panels. This approach enabled systematic assessment of phage-bacteria interactions at scale, facilitating the identification and optimization of phage cocktails with broad in vitro activity. Although bacteriophage therapy has long been investigated as a strategy for treating bacterial infections, few frameworks exist for developing phage combinations in a reproducible and scalable manner. The methods outlined here address this gap and aim to support the broader development of therapeutic assets available to combat antibiotic resistance.

Article Details

Volume / Issue Vol. 17, Issue 1
Published January 30, 2026
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (18)

T

Taylor J. R. Penke

A

Aeron Tynes Hammack

L

Lana J. McMillan

E

Ethan Baker

P

Pearl Wilcock

N

Nick Healy

M

Morgan K. Y. Wall

N

Naomi Chavez

I

Iain Wright

H

Hannah H. Tuson

S

Sara Woessner

A

Ashley Trama

C

Cameron J. Prybol

E

Eyra Dordi

A

Ava Ghobadian

D

David G. Ousterout

N

Nicholas R. Conley

P

Paul Garofolo