Lipid-Based Inhalable Nanoformulations Against Lung Cancer: Systematic Review & Meta-Analysis

This project is a systematic review with quantitative synthesis evaluating the aerosol/aerodynamic performance of lipid-based inhalable nanoformulations developed for lung cancer–relevant applications. The central premise is that the translational plausibility of pulmonary nano-delivery is constrained by aerosol performance—most importantly mass median aerodynamic diameter (MMAD) and fine particle fraction (FPF)—yet the literature reports these endpoints across heterogeneous devices, impactors, flow conditions, and multiple formulations per study, generating dependent effect sizes that violate assumptions of conventional meta-analysis. The review identifies and characterizes lipid-based systems intended for inhalation (e.g., liposomes, SLN/NLC, nanoemulsions, cubosomes/sterosomes, lipid-rich hybrids) and extracts data at the formulation–device–method condition level (i.e., one row per unique experimental condition such as nebulizer model/class, impactor type, flow rate, induction port/throat, and FPF cut-off definition). Study selection follows PRISMA-aligned screening with transparent documentation of exclusions. Risk of bias/quality is appraised at the study level using an appropriate critical appraisal tool for quasi-experimental/preclinical designs. For quantitative synthesis, the primary outcomes MMAD (µm) and FPF (%) are pooled using a cluster-robust variance estimation (CRVE) framework with study-level clustering to accommodate multiple correlated observations within studies. Between-study variance is estimated with a random-effects approach (τ²), and inference uses small-sample robust corrections appropriate for a limited number of clusters. Where FPF definitions vary (cut-off, denominator), definitions are recorded verbatim and handled via pre-specified subgrouping and sensitivity restrictions to harmonized definitions when feasible. Expected outputs include: (i) a structured evidence map of lipid formulation classes and aerosol platforms used in lung cancer-targeted inhalation research, (ii) pooled estimates for MMAD and FPF with robust uncertainty bounds, (iii) subgroup findings by nebulizer/device class, cascade impactor/method (e.g., NGI/ACI/APS), and formulation class, and (iv) a transparent, reusable dataset and analysis scripts supporting reproducibility and downstream meta-research.