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Life sciences · Journal article
Frontiers in Cellular and Infection Microbiology · August 26, 2026
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This perspective article proposes the Intelligent Anti-Infective Ecosystem (IAIE) as a conceptual systems-level framework integrating multimodal diagnostics, AI-assisted decision support, and multiple antimicrobial modalities to address antimicrobial resistance. The authors explicitly state that IAIE is a prospective architecture and that its clinical value remains to be established through future computational, preclinical, and clinical investigations; no validation data are presented.
Journal article.
IAIE framework proposed to computationally integrate multimodal diagnostics, pathogen genomics, microbiome profiling, AI-assisted decision support, programmable precision therapeutics, ecological monitoring, and longitudinal clinical feedback Existing emerging technologies (antimicrobial peptides, bacteriophage therapy, CRISPR-based antimicrobials, microbiome therapeutics, anti-virulence approaches, nanotechnology-enabled drug delivery, and AI) are predominantly being developed as independent interventions rather than coordinated components IAIE emphasizes closed-loop coordination among complementary antimicrobial approaches to support precision-guided infection management while preserving microbiome integrity and mitigating resistance selection pressure
No comparative effectiveness, safety data, or outcome measures reported
This perspective does not report clinical outcomes and should be understood as a conceptual roadmap rather than evidence for practice change. Clinicians should recognize IAIE as a proposed future direction requiring substantial further research before implementation.
This is a conceptual perspective proposing a theoretical framework (IAIE) for integrating multiple anti-infective technologies with AI; no empirical data, clinical trials, or validation studies are presented.
This perspective does not report clinical outcomes and should be understood as a conceptual roadmap rather than evidence for practice change. Clinicians should recognize IAIE as a proposed future direction requiring substantial further research before implementation.
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The rapid global expansion of antimicrobial resistance (AMR) threatens to undermine decades of progress in infectious disease management and highlights the limitations of conventional antibiotic-centered therapeutic strategies. Although emerging technologies—including antimicrobial peptides, bacteriophage therapy, CRISPR-based antimicrobials, microbiome therapeutics, anti-virulence approaches, nanotechnology-enabled drug delivery, and artificial intelligence (AI)—have individually demonstrated considerable promise, they are predominantly being developed as independent interventions rather than as coordinated components of an integrated therapeutic strategy. This Perspective proposes the Intelligent Anti-Infective Ecosystem (IAIE) as a conceptual systems-level framework that computationally integrates multimodal diagnostics, pathogen genomics, microbiome profiling, AI-assisted decision support, programmable precision therapeutics, ecological monitoring, and longitudinal clinical feedback within a continuously learning dynamically optimized workflow. Unlike existing paradigms that primarily optimize individual technologies or therapeutic decisions, IAIE emphasizes closed-loop coordination among complementary antimicrobial approaches to support precision-guided infection management while preserving microbiome integrity and mitigating resistance selection pressure. We further outline the core components, operational principles, translational challenges, and technology readiness of the major therapeutic platforms that could contribute to such an ecosystem, while distinguishing clinically established interventions from emerging experimental strategies. Importantly, IAIE should be interpreted as a prospective conceptual architecture rather than an existing clinical platform. Its proposed clinical value remains to be established through sequential computational, preclinical, and prospective clinical investigations using standardized microbiological, ecological, and patient-centered outcome measures. By framing antimicrobial innovation within an responsive systems perspective, IAIE provides a roadmap for future multidisciplinary research aimed at integrating artificial intelligence and systems microbiology to enable sustainable management of antimicrobial resistance.
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