A physicist trained in quantum computing is using the same high-throughput automation and artificial intelligence (AI) tools developed for quantum research to accelerate the discovery of bacteriophages that can kill antibiotic-resistant bacteria. This crossover between quantum materials science and infectious disease research reveals how cutting-edge lab infrastructure built for one purpose can solve entirely different problems when combined with robotics and machine learning.

What Are Bacteriophages and Why Are They Making a Comeback?

Bacteriophages, or phages, are viruses that infect bacteria. They were discovered between 1915 and 1917, more than a decade before penicillin, and Soviet scientists spent decades developing phage therapies for infections. However, phages fell out of favor in Western medicine because each phage targets only a narrow subset of bacterial strains. Where a single antibiotic like penicillin can kill multiple species of bacteria, you might need four to six different phages to treat a single uncomplicated E. coli infection.

Today, phage therapy is experiencing a renaissance because modern diagnostics have changed the game. Rapid genetic sequencing can now identify exactly which pathogen is causing an infection in hours rather than days. This precision makes phages attractive again, because their narrow targeting becomes a feature rather than a bug. As one researcher explained, phages work like "snipers instead of grenades," meaning a phage intervention for E. coli won't accidentally trigger antibiotic resistance in other bacteria like Staph aureus.

How Are Quantum Computing Tools Being Repurposed for Phage Discovery?

Aeron Tynes Hammack, a physicist by training and interim facility director of the Nanofabrication Facility at the Molecular Foundry at Berkeley Lab, works with nano-scale objects to solve problems. His work spans two seemingly unrelated domains: developing qubits for quantum computers and creating viral therapies to combat infectious diseases. Both require the same underlying capability: automated experimental tools that can test thousands of potential candidates and determine which performs best.

Hammack is currently using the quantum information science (QIS) cluster tool at the Molecular Foundry to investigate which materials produce the best Josephson junctions, a key component of qubits. A Josephson junction is essentially a sandwich of two superconductors separated by an ultrathin insulating layer. The cluster tool combines advanced robotics and AI to rapidly design, manufacture, and test candidates, massively speeding up the trial-and-error pipeline of traditional materials research.

Hammack realized this same automation infrastructure could be applied to phage screening. For ten years, he and collaborator Nick Conley developed an entire pipeline capable of screening thousands of bacteriophages against target bacteria using robotics and machine learning. Their automated machinery takes samples of microbes and phages, introduces them in tiny liquid environments, then uses microscopy and optical density assays to determine whether the phage killed the microbes. A computer vision program, a type of AI, rapidly processes these results, a task that previously required manual analysis by hand and eye.

How to Apply Quantum Automation Techniques to Biological Research

• High-throughput screening: Use robotics to test thousands of biological candidates simultaneously rather than testing them one at a time, reducing research timelines from years to months.
• Machine learning analysis: Deploy computer vision and AI algorithms to automatically process microscopy images and spectroscopy data, eliminating manual data entry and human error.
• Precision diagnostics: Combine rapid genetic sequencing with targeted treatments, allowing clinicians to prescribe the exact biological intervention needed for each patient's specific infection.

From Lab Discovery to Clinical Trials: A Real-World Success Story

Hammack and Conley's company, EpiBiome, was acquired by biotech firm Locus Biosciences, which refined and scaled their phage screening pipeline. The result is now in clinical trials. A recent paper published in Nature Communications describes the automated process that Hammack built at EpiBiome, which was brought to full production scale by researchers at Locus Biosciences.

"Any of the private industrial successes I've had have been on the foundation of DOE-scale research efforts. Industry rarely wants to fund the kind of 10- or 20-year research initiatives you need to understand the basic science principles needed before you can engineer anything," said Aeron Tynes Hammack.

Aeron Tynes Hammack, Interim Facility Director of the Nanofabrication Facility at the Molecular Foundry

The team focused on urinary tract infections because they are a common indication for antibiotic use. By introducing an alternative phage-based treatment, they can immediately reduce antibiotic prescriptions and help slow the pace of antibiotic resistance, which is an enormous mounting danger to public health.

What Does the Future of Precision Phage Medicine Look Like?

The full vision for phage therapy involves a workflow that sounds like science fiction but is becoming technically feasible. A patient arrives at the emergency room, and diagnostics so sensitive and precise they function like a medical tricorder identify exactly which pathogens are causing the infection. The patient is then treated with the exact cocktail of phages needed, dispensed by microfluidics-powered phage dispensaries that function essentially like inkjet printers for phages. Broad-spectrum treatments remain possible by mixing many different phages together.

This vision is becoming possible thanks to advances in diagnostics and projects like the Phage Foundry, a multi-institutional effort led by Berkeley Lab that is cataloging relevant phages for the scientific community. The convergence of quantum computing automation, AI-powered analysis, and precision diagnostics represents a new model for how fundamental physics research can accelerate solutions to urgent biological problems.

The story of Hammack's work illustrates a broader principle in modern science: the tools and techniques developed for one frontier often unlock solutions in entirely unexpected domains. Quantum computing infrastructure, built to explore the behavior of subatomic particles, is now helping humanity fight one of the most pressing threats to modern medicine.