RNAi-based bioinsecticides for sustainable agriculture: from molecular discovery to field deployment and global policy perspectives
Abstract
RNA interference (RNAi) is an effective technique for sustainable insect management by providing effective, targeted and species-specific solutions that can be deployed as an alternative to traditional chemical-based synthetic pesticides. RNAi is highly specific in nature, with a remarkable safety profile, rapid biodegradation and minimum risk to non-target organisms and reduces the environmental risk. In addition, the changing environmental and regulatory dynamics have made intergovernmental agencies and bodies initiate the approval of RNAi products, reflecting growing acceptability. Moreover, with the current advances in synthetic biology and artificial intelligence, the design and deployment of RNA-mediated insect control will be further facilitated. Thus, RNAi, which is regarded today as mostly a lab-scale experimental technique, can cement its place as a next-generation and sustainable integrated pest management solution. This review encompasses the theory and scientific principles behind RNAi-based biopesticides, from sequence identification to field deployment. It further addresses other critical issues in RNAi-mediated insect control, such as the discovery of target insect genes, double-stranded RNA degradation affecting efficacy and emerging delivery strategies, including foliar sprays, nanoparticle encapsulation and systemic approaches to enhance stability and cellular uptake. Moreover, the review provides an end-to-end comprehension and comparison of the molecular discovery, deployment and policy perspectives related to RNAi-based insect management. Together, these advances position RNAi as a promising but still evolving platform for sustainable pest management, with its impact ultimately depending on delivery efficiency, biosafety and regulatory readiness. Future progress will require coordinated advances in formulation science, target validation and policy support to enable reliable field deployment.