Why Reactive Approaches to Antimicrobial Resistance Are Failing

Resistance rates are accelerating, and the patients who can least afford treatment failure—immunocompromised, transplant, oncology—face the highest stakes.

Impact

40M

deaths by 2050

The Lancet 2024
$159B

global economic burden by 2050

CGDev
40%

increase in resistance rates from 2018-2023

WHO GLASS
0

tests that forecast resistance

Biology

The Science Behind Antimicrobial Resistance

Understanding how bacteria outsmart our best defenses

Mutation

Bacteria develop resistance to antimicrobials through genetic mutations that allow them to survive drug exposure.

DNA Acquisition

Bacteria acquire resistance genes from other organisms, rapidly spreading resistance mechanisms across species.

Rapid Evolution

Bacteria develop multidrug resistance (MDR) and evolve faster than we can develop new antimicrobials.

Challenges

We have a learning system gap

We don't just need faster results, we need better information.

Snapshot diagnostics, not foresight

Current results describe susceptibilities as a moment in time, when they are dynamic, constantly in flux, and subject to evolution and population dynamics. No currently available diagnostic technology appreciates this and captures information regarding pathogen evolution under drug pressure.

Treatment-emergent resistance is a blind spot

Resistance often emerges during therapy, especially in high-risk patients and pathogens. We lack an early warning signal to identify which pathogens are on the brink of acquiring new resistance, until treatment fails and it's clinically obvious.

No learning system linking evolution to outcomes

Genomics, microbiology, prescribing, and outcomes live in silos. Without a feedback loop that connects pathogen evolution to real patient trajectories, hospitals can't continuously improve decisions—and drug development can't systematically design for resistance avoidance.

Solution

Breaking the Reactive Cycle

From waiting for failure to forecasting it before it happens

01

New Clinical Signal

First forecast of treatment-emergent resistance risk to help prevent failures in vulnerable patients.

02

Results in 24 Hours

Actionable insights designed for stewardship to optimize appropriate therapy.

03

Learn Continuously

Build the intelligence layer that links bacterial evolution to patient outcomes across health systems.

The Paradigm Shift

The technology to analyze bacterial genomes exists. What's been missing is the ability to translate genomic data into clinically actionable insights.

Informuta's Approach

We pioneered bacterial mutational signature mapping to forecast resistance evolution. Our biologically explainable AI delivers clinician-ready forecasts that transform antimicrobial prescribing from reactive to predictive.

Take Action

Stop Resistance Before It Starts

For the patients who can't afford treatment failure, forecasting resistance before therapy changes everything.