Breaking the bottleneck of asthma treatment: the future of omni-targeted therapy

Bronchial asthma is a complex, highly heterogeneous disease involving multiple pathological mechanisms and inflammatory pathways. Traditional pharmacotherapies, including glucocorticoids, leukotriene modifiers, β₂-adrenergic agonists, and muscarinic antagonists, and new targeted biologics can alleviate symptoms and prevent acute exacerbations; however, achieving clinical remission or a cure remains a major challenge.

To systematically outline the definition, epidemiology, and multifactorial pathogenesis of asthma; to explore potential therapeutic targets incorporating the latest advances from clinical trials and targeted interventions; and to emphasize the development of multi-target ("omni-targeted") combination strategies based on individualized diagnosis, potentially guided by artificial intelligence (AI), to improve asthma control, clinical outcomes, and exacerbation rates, with an eye toward a definitive cure.

We propose that the current therapeutic dilemma largely reflects the inability of single-target therapies to address an individual's multiple pathogenic pathways. In contrast, multi-target, personalized strategies can modulate diverse pathological pathways simultaneously and precisely. Realizing these strategies will require AI-enabled guidance, precise identification of individual pathogenic mechanisms, and further development of targeted therapeutics.