What is the name of your organization?
Munai
What is the name of your solution?
Antibiotic Stewardship Copilot
Provide a one-line summary or tagline for your solution.
AI-powered decision support with patient engagement that detects substandard antibiotics in low and middle-income communities.
In what city, town, or region is your solution team headquartered?
Curitiba, State of Paraná, Brazil
In what country is your solution team headquartered?
Brazil
What type of organization is your solution team?
For-profit, including B-Corp or similar models
Film your elevator pitch.
What specific problem are you solving?
Antimicrobial resistance (AMR) threatens global health with disproportionate impact on low and middle-income countries. Our solution addresses two critical drivers of AMR in community settings: inappropriate antibiotic prescribing and substandard/falsified antibiotics.
In Latin America, approximately 50% of antibiotic prescriptions are inappropriate, accelerating resistance development while failing to effectively treat infections. This misuse stems from limited diagnostic resources, outdated guidelines, and minimal oversight for community physicians.
Simultaneously, 10-12.4% of antibiotics in LMICs are substandard or falsified, containing insufficient active ingredients that promote resistance by exposing pathogens to subtherapeutic concentrations. These products create ideal conditions for resistant strains to emerge and spread throughout communities.
Access issues further complicate this landscape. Antibiotic stockouts force patients to seek alternatives that may be substandard, falsified, or inappropriate for their condition. The WHO has highlighted these shortages as a critical challenge, with supply chain disruptions affecting even essential first-line treatments.
These challenges converge in community settings where oversight is limited and patients navigate healthcare systems with minimal guidance. Our solution directly addresses these interconnected problems by providing AI-powered decision support for appropriate prescribing while simultaneously generating community-level data on antibiotic access and quality through patient engagement.
What is your solution?
Our solution is an AI-powered Copilot for antibiotic decision support in community settings, designed specifically for Latin America. Building on Munai's hospital expertise, we've created a mobile-first system, which can also be integrated into the EMR workflow as an add-on, combining clinical guidance with patient engagement to address both inappropriate prescribing and substandard antibiotics.
The Copilot consists of three integrated components:
AI Clinical Decision Support: A web application providing physicians with guideline-based recommendations for appropriate antibiotic prescriptions, drawing on a specialized model trained on regional antibiotic guidelines.
Patient Engagement Layer: Automated follow-ups via WhatsApp at key treatment milestones to collect feedback on medication access, adherence, and outcomes.
Quality Monitoring: Patients submit photos of antibiotic packaging with QR codes, building a trusted registry of product performance without complex technology.
This creates a continuous feedback loop: the AI guides prescribing, patient data reveals access issues and treatment failures, and the system identifies potential substandard products—all without requiring integration with existing healthcare infrastructure.
We'll offer free access to 1,000 infectious disease specialists and aim to reach 5,000 physicians and 50,000 patients monthly by the end of 24 months.
Who does your solution serve, and in what ways will the solution impact their lives?
Our solution serves two interconnected populations in Latin America: community-based healthcare providers and the patients they treat with antibiotics.
For healthcare providers, particularly those in primary care settings, our Copilot addresses daily challenges they face. These clinicians often work with limited diagnostic resources, outdated guidelines, and minimal oversight, yet must make rapid decisions about antibiotic prescribing. Our solution provides evidence-based recommendations tailored to local resistance patterns, reducing cognitive burden and improving prescription quality.
For patients, who ultimately bear the consequences of inappropriate prescribing and substandard medications, our solution creates a direct communication channel throughout their treatment journey. This underserved population frequently lacks follow-up care and has limited means to verify medication quality. Through simple WhatsApp interactions, patients contribute valuable data while receiving reminders to improve adherence.
By connecting these populations through technology, we create a virtuous cycle: physicians prescribe more appropriately, patients receive better care and contribute real-world data, and the system continuously improves its ability to detect access issues and quality problems. This patient-centered approach transforms passive recipients of care into active participants in antibiotic stewardship.
