<p>Lung cancer remains one of the most prevalent and deadly forms of cancer worldwide, with a high mortality rate and limited treatment options available. Traditional chemotherapy and radiation therapy have been the mainstays of lung cancer treatment, but their efficacy is often limited by systemic toxicity and drug resistance. Recently, many nanoparticles have been identified and created for drug delivery with the ability to specifically target tumor cells while sparing healthy cells or organs. The nanoparticle-based drug delivery system offers distinct benefits over conventional medication delivery, including increased permeability and retention effect, precision targeting, and improved stability and biocompatibility. Therefore, this paper proposes the group decision making approach under linguistic q-rung orthopair fuzzy environment to select the best nanoparticle in drug delivery system for lung cancer treatment. Firstly, this paper proposes linguistic q-rung orthopair fuzzy Yager power weighted geometric aggregation operator for aggregating the linguistic q-rung orthopair fuzzy numbers based on the Yager’s norm. This paper also demonstrates several features of the proposed operator. Moreover, by using the proposed operator, this paper presents the group decision making approach. Furthermore, a case study is presented for the selection of optimal nanoparticle in drug delivery for the treatment of lung cancer to demonstrate the proposed decision making approach’s applicability. Finally, this paper presents comparison study, sensitivity analysis and superiority of proposed decision making approach with the other existing decision making methods to validate the proposed decision making approach.</p>