Early detection relies increasingly on minimally invasive molecular biomarkers, which are detectable in blood, urine, or bronchoalveolar lavage. The main classes include circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), tumor-derived extracellular vesicles/exosomes, and tumor-associated proteins and microRNAs. Advances in ultra-sensitive sequencing, PCR-based assays, and nanomaterial-enhanced biosensors have improved the limit of detection (LOD) for low burden disease (Kim and Park, 2023; Harisha et al., 2025). The combined biomarker, such as ctDNA alongwith protein or extracellular vesicle (EV) signatures, shows greater sensitivity and specificity than single analytes. Recent studies reported that ctDNA assays, especially when paired with other markers or imaging, hold the most promise for early stage lung cancer screening and minimal residual disease surveillance, though sensitivity in stage I disease remains a challenge. Smart nanodiagnostic platforms can amplify these weak signals through molecular capture, signal transduction, and multiplexed readouts (Lam et al., 2024; Ma et al., 2024; Li et al., 2025).

Lung tumors employ multiple overlapping immune escape strategies. These strategies include upregulation of immune checkpoints (PD-L1/PD-1), polarization of immunosuppressive myeloid populations (tumour-associated macrophages, myeloid-derived suppressor cells), secretion of suppressive cytokines (TGF-β, IL-10), metabolic competition (tryptophan depletion via IDO, lactate accumulation), and shedding of PD-L1 on exosomes (Jeong et al., 2025). These mechanisms blunt cytotoxic T-cell function and reduce antigen presentation, which limits the responses to immunotherapy in many patients. Targeting or reprogramming suppressive elements, such as repolarizing tumor associated macrophages (TAMs), blocking exosomal PD-L1, or locally delivering checkpoint inhibitors with nanoparticles, represents a rational route to restore antitumor immunity while minimizing systemic toxicity (Lin X. et al., 2024; Lv et al., 2025). The summary of main biomarkers, nanoplatform designs, and diagnostic/therapeutic strategies for lung cancer are given in Table 1.

Smart nanoplatforms for the cancer diagnostics and therapy are engineered from interchangeable modules (core, payload, targeting ligand, and biomimetic shell) to allow tailored pharmacokinetics and multi functionality (Sun et al., 2023). TME cues pH, redox state, enzymes, and hypoxia are commonly exploited to trigger on-site drug release or immune stimulating activity, improving specificity and reducing off-target effects (Zhou W. et al., 2022). Stimuli-responsive polymers and nanogels enable controlled release kinetics and cargo protection (small molecules, nucleic acids, or adjuvants), supporting both early detection and immune modulation roles (Chang et al., 2021). Biomimetic strategies (cell membrane coatings and exosomes) enhance circulation time and immune compatibility while enabling antigen presentation or immune cell targeting for vaccination or reprogramming (Hu T. et al., 2023). Finally, modern designs emphasize TME remodeling and integrated theranostics to monitor response in real time, key for translation to lung cancer immunotherapy (Lu Q. et al., 2024). A stimulus-responsive drug delivery platform for the diagnosis and therapy of lung cancer is shown in Figure 1. In which oxygen and doxorubicin were loaded on nanodroplets, and high-intensity focused ultrasound (HIFU) was employed to trigger their controlled release while simultaneously enhancing ultrasound imaging for image-guided drug delivery. The application of mild temperature HIFU slightly increased the tumor temperature and improved local blood flow. As a result, ultrasound-induced oxygen release combined with moderate thermal elevation effectively alleviated tumor hypoxia and multidrug resistance. These synergistic effects significantly enhanced the therapeutic efficacy of doxorubicin against lung metastases (Lin et al., 2022). The nanomaterials used for lung cancer can be grouped into four major classes, each with distinct strengths and limitations for detection and immune modulation. A concise classification and representative examples of nanomaterials used for lung cancer are given in Table 2.

POC wearable nano-diagnostic devices and POC biomedical sensors are transforming decentralized and rapid lung cancer screening by facilitating sensitive and real-time testing at the bedside. New nanotechnology breath-based chemiresistive sensor arrays and nose on chip systems employing functionalized nanomaterials can reliably identify volatile organic compounds (VOC) identifies unique to lung tumors, as a highly specific, noninvasive diagnosis (Chaudhary et al., 2024). While paper or microfluidic-based nanoparticle-assisted lateral flow and smartphone read electrochemical tests enable near-patient ctDNA/protein readouts and Cancer Antigen, like CA-125 (Pourmadadi et al., 2023; Yang et al., 2024). Wearable patches and flexible sensors constructed from bioinspired nanomaterials offer continuous physiological and biomarker monitoring, potentially identifying temporal variations and early signs of malignancy. Ensuring robustness, minimizing user variability, and maintaining data accuracy remain active research areas that must be addressed before these technologies achieve reliable and widespread clinical application (Khalifa and Albadawy, 2024).

Data integration and Artificial Intelligence (AI) have greatly improved the diagnosis of cancer. AI is revolutionizing how nano diagnostic results are interpreted and merged with clinical data. Machine learning algorithms enhance signal amplification from noisy outputs of nano-sensors, assist in multi-analyte signature classification, such as integrating ctDNA fragment patterns and VOC panels, and allow multimodal imaging, biomarker, and patient metadata fusion for enhancing diagnostic accuracy and risk stratification (Carrillo-Perez et al., 2022; Chaddad et al., 2023). These centers, such as multimodal data fusion, integrate with imaging, biomarker, and patient metadata to enhance diagnostic accuracy, risk assessment, and individualized treatment planning. In addition, AI technologies are speeding up nanoparticle design by forecasting ideal physicochemical features, optimizing targeting performance, and calibrating assay parameters for more efficient and reproducible performance (Alavinejad et al., 2025). Currently, collaborative methods are under development to enable collaborative model training across institutions while not violating the privacy of patient data, and explainable AI models seek to enhance transparency and clinical trust. Despite the various challenges that still exist, such as dataset heterogeneity, possible algorithmic bias, restricted access to large annotated clinical datasets, and the absence of standardized regulatory mechanisms for validation and approval of AI-fused diagnostic tools (Zhu et al., 2025). Overcoming these challenges is a requirement to bring AI-boosted nano diagnostics into stable, ethical, and clinically viable forms that can enable early cancer diagnosis and precision medicine.

Nanocarriers like lipid nanoparticles, polymeric particles, protein-based carriers, and hybrid nanosystems are under active development to improve targeted delivery of immune checkpoint inhibitors like anti-PD-1, PD-L1, and CTLA-4 antibodies, siRNA, and mRNA constructs directly to the TME (Guo L. et al., 2025). Targeted delivery significantly increases therapeutic efficacy while reducing systemic toxicity and immune related adverse events typically encountered with traditional checkpoint blockade treatments. By encapsulating these checkpoint blocking agents, nanocarriers maintain protection against enzymatic degradation, improve localized drug accumulation in tumors, and allow for controlled or stimulus sensitive release mechanisms induced by conditions like pH, enzymatic activity, or exposure to light (Hu J. et al., 2025). This control of space-time delivers sustained therapeutic concentrations and also targeted immune modulation within the TME. Furthermore, co-delivery strategies where checkpoint inhibitors are mixed with immunostimulatory cytokines, adjuvants, or tumor antigens in a single nanoplatform have reported synergistic enhancement of innate and also adaptive immunity, leading to enhanced rates of response in cancer models preclinically (Tian et al., 2024). While these encouraging results hold much promise, various challenges must yet be overcome before clinical translation can be successful, such as large-scale and reproducible production of nanoparticles, long-term stability upon storage and in circulation, possible immunogenicity, and the development of standardized test protocols. Ongoing formulation design optimization as well as regulatory validation will be critical to achieve the full clinical value of nanocarrier based immune checkpoint delivery systems.

Nanovaccines take advantage of advanced carrier systems such as liposomes, polymeric nanoparticles, virus-like particles, and self-assembling protein constructs to co-deliver tumor antigens in association with immunostimulatory adjuvants to improve antigen presentation and elicit potent T-cell activation (Zhang et al., 2019). These nanocarriers ensure the efficient engulfment by antigen presenting cells (APCs) and provide sustained, controlled antigenic material release, ensuring extended immune stimulation. Current advances in nanotechnology have provided new vaccine platforms, such as lipid nanoparticle (LNP)-based mRNA vaccines, peptide polymer conjugates, and dendritic cell-targeted nanoparticles, enabling targeted delivery to lymph nodes and effective induction of cytotoxic T-lymphocyte responses for powerful antitumor immunity (Tian et al., 2024). Moreover, cutting-edge studies identify the modular and tunable nanovaccine architectures for use in personal neoantigen immunotherapy to provide scalable and tunable manufacturing to cover unique tumor patterns. These developments altogether are a significant step ahead towards the next-generation of cancer vaccination approaches (Zhang et al., 2019; Saleh et al., 2025).

TAMs are among the most common immune cells of the TME and are a major regulator of immunosuppression, tumor growth, angiogenesis, and metastasis (Li et al., 2024a). TAMs have a tendency to acquire an M2 like phenotype that supports tumor cell proliferation, suppresses cytotoxic T-cell functions, and facilitates immune evasion. As a result, TAMs have emerged as a valuable target for cancer immunotherapy. Nanotechnology brings novel and targeted ways to control TAM activity by using three broad strategies: (i) blocking circulating monocyte recruitment that gets differentiated into TAMs, (ii) targeted elimination of the pro-tumoral M2 subset macrophages, and (iii) reprogramming the M2 macrophages into anti-tumoral M1 phenotypes with the ability to secrete pro-inflammatory cytokines and restore antitumor immunity (Kim et al., 2024). Macroscopic effects to be brought about by them have led to the development of macrophage receptor ligand-functionalized nanocarriers that deliver therapeutic molecules like CSF-1R inhibitors, siRNA, or TLR agonists to TAMs selectively and thereby modulate the immune system effectively (Li et al., 2024b; Xu et al., 2025). n recent times, lipid nanoparticles (LNPs) loaded with RNA have also been identified as a highly promising delivery strategy for in vivo reprogramming of macrophages due to their biocompatibility, efficient cell uptake, and ability to protect against RNA cargo degradation [30]. The LNPs have the properties to efficiently modulate gene expression in macrophages, changing TME from immunosuppressive to immunostimulatory states. Additionally, nanoparticle platforms can co-deliver cytokines or co-stimulatory molecules to trigger T-cells simultaneously, thus integrating innate and adaptive immunity. Such combinational macrophage–T-cell targeting approaches bear significant potential for the next-generation of immuno-oncology treatments, as shown in Figure 4 (Gül et al., 2025; Xu et al., 2025).

Nanoplatforms are areas of research that offer scope to combine various therapeutic modalities chemotherapy, radiotherapy, photothermal therapy (PTT), photodynamic therapy (PDT), and immunotherapy, on a single scaffold (Naik et al., 2025). These multifunctional systems allow for concurrent tumor killing and immune stimulation. For instance, drug carrier nanoparticles or photosensitizer-loaded nanoparticles can induce tumor cell death as well as induce in situ release of tumor-associated antigens. When used in combination with immune checkpoint blockade, the process augments systemic antitumor immunity, creating an in situ vaccine effect that enhances the body’s immune response against metastatic or remaining cancer cells (Sun et al., 2024; Naik et al., 2025). Additionally, photothermal and radiotherapy derived nanoplatforms have shown striking synergistic effects by recording more effective tumor regression and greater abscopal responses when combined with immune adjuvants or checkpoint inhibitors. Rational and spatiotemporal design of these multimodal nanotherapies is fundamental to providing clinical efficacy, reducing toxicity, and maximizing therapeutic safety and translation toward next-generation cancer treatment strategies (Pan et al., 2024; Sun et al., 2024; Naik et al., 2025).

Nanomedicine focuses on multifunctional theranostic nanoplatforms that both possess therapeutic and diagnostic functions and are highly biocompatible and pharmacokinetically predictable. These smart nanoplatforms deliver drugs, genes, or immunomodulators in combination with imaging modalities, including MRI, PET, fluorescence, or ultrasound, enabling real-time monitoring of biodistribution, therapeutic efficacy, and early therapeutic response expressed in Figure 5 (Yasir et al., 2024; Salgueiro and Zubillaga, 2025).

Further hybrid inorganic-organic and polymeric architectures combine photothermal or photodynamic modules with targeting ligands and contrast agents, enabling precision-guided therapy and simultaneous visualization at the molecular level (Salgueiro and Zubillaga, 2025). Moreover, the clinical success of such advanced systems depends on safe material composition and controlled in vivo behavior. Important physicochemical characteristics, particle size, charge, hydrophilicity, and degradability dictate circulation half-life, reticuloendothelial system clearance, and tissue uptake (Kyriakides et al., 2021; Saker et al., 2024). Rational design, therefore, requires the careful balance of multifunctionality with biological safety. Emerging methods utilize biodegradable polymers and environmentally friendly nanomaterials to minimize chronic toxicity and immune stimulation without sacrificing efficacy (Kyriakides et al., 2021; Parra-Nieto et al., 2024). In the future, pharmacokinetic and immunotoxicity assessment frameworks are necessary to provide reproducibility and regulatory acceptability and make them scalable and safe theranostic nanomedicine (Saker et al., 2024; Sabit et al., 2025).

Selective and targeted delivery of intelligent nanomedicines to the lung is associated directly with anatomical and biological barriers that restrict therapeutic effectiveness. The respiratory tract is shielded by a cascade of defense barriers, such as mucus, pulmonary surfactants, and epithelial cell barriers, which all retard nanoparticle adhesion, deposition, and penetration in target tissue (Cojocaru et al., 2024). Nanoparticles must counteract mucociliary clearance mechanisms that rapidly remove foreign particles from airways, as well as evade phagocytic uptake by alveolar macrophages that can greatly cut short their sojourn time and reduce drug bioavailability in the target site (Fernández-García and Fraguas-Sánchez, 2024; Wang et al., 2024c). In addition, pathological alterations like inflammation, fibrosis, and tumor-induced airway architecture remodeling change permeability of the tissue and establish heterogeneous microenvironments that impede nanoparticle diffusion and uniform distribution in sites of tumors (Deng et al., 2021; Sanati et al., 2025). All these barriers individually highlight the need to develop lung-specific nanocarriers with well-designed aerodynamic properties, surface modifications, and targeting strategies to maximize pulmonary delivery and therapeutic effects.

Recent studies have shown that surface engineering, such as PEGylation or charge modulation, improves mucosal diffusion and minimizes immune clearance (Deng et al., 2021; Fernández-García and Fraguas-Sánchez, 2024). Current advances in inhalable nanocarriers, such as lipid-based aerosols and polymeric micelles, show enhanced delivery efficiency and tumor penetration when aerodynamically optimized for size and surface properties (Jin et al., 2023; Chen R.-K. et al., 2025). Yet, with good preclinical performances, scaling up nanotherapeutics into large scale manufacturing continues to be an unprecedented challenge. Laboratory synthesis pathways, emulsification, nanoprecipitation, and microfluidics do not readily scale up to replicate consistent particle size, surface charge, and encapsulation efficiency (Operti et al., 2021). Continuous manufacturing and microfluidic-based platforms are becoming the solutions to obtain consistent particle batches and minimize process variability (Feng et al., 2019; Abdelmonem et al., 2025). In addition to that, ensuring their regulatory approval and batch-to-batch reproducibility demands sophisticated analytical characterization equipment and rigorous quality control, which considerably escalates production costs (Operti et al., 2022; Khopade and Shah, 2025).

Safety and biocompatibility of nanocarriers are the key issues for clinical translation. Biodegradable polymers, such as polyethylene glycol-poly(lactic-co-glycolic acid (PEG-PLGA), chitosan, and lipid-based nanocarriers, represent a widely used family of materials owing to their relatively low immunogenicity and favorable clearance profile (Wu et al., 2024). The PEGylation indeed reduces opsonization and prolongs the circulation time by minimizing off-target accumulation within the liver and spleen (Zhang et al., 2022; Kesharwani et al., 2025). Nevertheless, the main problem of nanoparticle accumulation in the reticuloendothelial system cannot be completely ignored. Long-term exposure to non-degradable nanoparticles results in oxidative stress, inflammation, and organ-specific toxicity. Recently reported surface modification strategies, including zwitterionic coating or HA-decoration, may markedly minimize the uptake of macrophages and systemic toxicity while maintaining therapeutic efficacy (Li et al., 2022; Skorzynski et al., 2025). Moreover, poorly soluble nanocarriers and inhalable nanocarriers targeting lung tissue are designed for maximal local deposition and minimal systemic exposure, offering further advances in improving the safety profile in preclinical models (Anderson et al., 2020; Feng X. et al., 2024). Therefore, safety is balanced against therapeutic benefit by rational design, optimization of drug dose, and careful monitoring of the biodistribution of nanoparticles.

Smart Nanomedicines also have different regulatory problems because of their physicochemical and biological dual hybrid nature. Agencies such as the FDA and EMA stress thorough physicochemical characterization, particle stability testing, and immunotoxicology profiling prior to approval (Soares et al., 2018; de Vlieger et al., 2019). Even harmonized international guidelines only slow down global harmonization and product approval. Ethical issues also come from the unresolved long-term biodistribution and possible unforeseen immune or genetic effects. Moreover, the high development and production costs are concerns regarding accessibility, especially in low- and middle-income economies. Open risk benefit evaluation, patient consent measures, and open data sharing are necessary to enhance clinical trust and provide an equal access approach to nano therapies (Wang L. et al., 2024; Khopade and Shah, 2025). Long-term safety is a gigantic concern while translating nanomedicine. Long-term accumulation of inorganic nanoparticles in organs like the liver, spleen, and kidneys is known to cause chronic inflammation, fibrosis, or oxidative stress. Research has shown that gold and silica nanoparticles cause mild but persistent tissue alterations months after they have been administered (Paranjpe and Müller-Goymann, 2014; Abdelmonem et al., 2025; Chen L et al., 2025). Moreover, nanoparticle interactions with the immune system can lead to complement activation, imbalance of cytokines, or even a change in microbiota composition (Soares et al., 2018; Garcés et al., 2021; Sanati et al., 2025). Per current research, biodegradable polymers like PLGA or lipid-based systems present with better clearance profiles, but stringent long-term monitoring must be maintained to establish metabolic safety. The integration of advanced in vitro organ-on-chip models and longitudinal in vivo imaging is increasingly proposed to predict and mitigate chronic nanotoxicity (Soares et al., 2018; de Vlieger et al., 2019).

The combined system of personalized medicine and nanotechnology is an efficient step forward in precision medicine, which makes it possible for individual diagnosis, of multiple targeted treatments, and therapy outcome monitoring in real-time. Collectively, these nanocarriers can also be formulated with real-time or “intelligent” features in combination with imaging probes including near-infrared dyes, magnetic nanoparticles, and photoacoustic reporters for simultaneous therapy and monitoring. For instance, ROS-responsive polymeric nanocarriers encapsulating fluorescent reporters enable real-time tracing of drug release in tumor therapy (Zhang et al., 2021; Li X. et al., 2023). While magnetic-response nanoplatforms have been developed to deliver immune modulators and allow MRI-guided monitoring of treatment response (Yang et al., 2022; Wei et al., 2026). Overall, all these recent designs underline the importance of smart nanocarriers in establishing targeted, efficient, and responsive immunotherapy in lung cancer (Zhou L. et al., 2022; Feng J. et al., 2024). Nanotechnology is concerned with the manipulation and engineering of materials at the nanoscale (1–100 nm), a scale that is similar to biomolecules, so as to achieve very specific interaction with cellular and molecular targets (Salata, 2004; Wagner et al., 2006). In personalized medicine, different nanomaterials like liposomes, dendrimers, polymeric nanoparticles, metal nanoparticles, carbon nanotubes, and quantum dots are utilized for the delivery of drugs and genes as per the individual’s molecular profile (Mura et al., 2013; Zhou Y. et al., 2022). Such nano-systems are feasible to be engineered using ligands, antibodies, or aptamers in order to selectively target tumor-specific biomarkers and thus escape the redundant toxicity and enhance treatment specificity and overall efficacy (Ventola, 2017). Moreover, nanotechnology has revolutionized molecular characterization and biorecognition element design used in biosensing platforms. The novel immobilization techniques, nanoscale sequencing and biosensing devices enable the facilitation of accurate pharmacogenetic analysis using the identification of genetic polymorphisms and mutations that influence personalized therapy outcomes. These advances in technologies allow dynamic adjustment of treatment regimens and real-time patient stratification. In total, the interaction between personalized medicine and nanotechnology provides an unparalleled platform for delivering ultra-specific, effective, and adaptive personalized healthcare solutions. Such paradigmatic shift not only enhances diagnostic precision and therapeutic benefits but also enables the formation of predictive, preventive, and participatory medicine by filling the gap from molecular to clinical translation as depicted in Figure 6 (Jain, 2019; Akhlaghi et al., 2024).

The advanced innovations in nano-diagnostics and theranostics have also coupled therapy and imaging in one nanoplatform, permitting real-time monitoring of drug release and disease progress.

The use of nanomedicine is aggressively growing and will see tremendous growth in the healthcare industry. Nanomedicines involve a broad spectrum of formulations, such as liposomes, lipid nanoparticles (LNPs), antibody drug conjugates ADCs, polymeric nanoparticles, viral vectors, cell-derived nanoparticles, inorganic nanoparticles, nanocrystals, protein-based nanoparticles, and nano-micelles (Thapa and Kim, 2023). As a result, they have been extensively used to treat cancer, infectious diseases, and neurological disorders. But clinical applications of nanomedicines on a larger scale are hindered, mainly because of limitations such as poor in vitro-in vivo correlation, off-target-derived toxicity, intricate processes of manufacture, and product instability (Agrahari and Agrahari, 2018). The current advancements in AI and Machine Learning (ML) have provided promising solutions to overcome the current challenges in nanomedicine development. AI/ML tools can predict, analyze, and optimize complex systems based on large sets of data, thus aiding multiple steps in the design, production, and clinical testing of nanomedicine (Kolluri et al., 2022).

Nanotechnology is the most revolutionary science of the 21st century, encompassing nanometer-scale engineering and production of materials (1–1000 nm), at which most biological processes naturally take place (Surendiran et al., 2009). Use of nanotechnology in medicine, known as nanomedicine, aims to create nanoscale therapeutic systems for better patient outcomes. Among them, nanoparticles (NPs), particularly those with a size of 10–100 nm, are highly useful owing to their capability to bypass the reticuloendothelial system (RES) and remain in circulation time in the blood. Small size, large surface area-to-volume ratio, and molecular encapsulation capacity, along with surface functionalization, render them the most sought-after candidates for drug delivery, imaging, and therapeutic purposes (Fang et al., 2013; Steichen et al., 2013). Various types of nanoparticles have been made for biomedical applications, such as lipid-based NPs, polymeric NPs, silica NPs, and metal NPs. Lipid nanoparticles, such as liposomes, are very biocompatible and can also encapsulate hydrophilic as well as hydrophobic molecules, though they generally suffer from issues such as leakage of the content and instability, and toxicity (Sharma and Sharma, 1997; Maurer et al., 2001). To overcome these problems of immune rejection, toxicity, and biodistribution, scientists have resorted to biomimetic nanotechnology. This method applies cell membrane-coated nanoparticles (CMCNPs) that can replicate the surface characteristics of native cells. By membrane coating of nanoparticle cores from erythrocytes, leukocytes, platelets, stem cells, cancer cells, or bacteria, these devices can avoid immune detection and preserve the biological behavior of native cell membranes (Gupta et al., 2014; Zhang, 2016). CMCNPs therefore present a two-in-one platform, unifying the therapeutic adaptability of nanoparticles with the biological camouflage and targeting property of natural cells. Effective lung cancer screening following clinical trials necessitates excellent institutional support, collaboration, and multidisciplinary coordination. Administrators, radiologists, oncologists, pulmonologists, and surgeons should be engaged in program planning under a medical director who coordinates clinical, administrative, and marketing staff. Patient recruitment, supported by educational materials and outreach through print, broadcast, and electronic media to reach target smokers, is what will sustain success. Effective workflows in eligibility screening, shared decision documentation, scheduling, and billing are necessary. In the United States, USPSTF certification and CMS approval have facilitated program implementation (Moyer and Force, 2014; Richards et al., 2019). Technical characteristics involve a CT scanner of at least 16-channel and/or higher that is able to complete low-dose single-breath-hold scans and must be run by qualified CT technologists to maintain consistency and image quality. Image interpretation should ideally be conducted by thoracic radiologists or those who have experience with chest CT, and results are stored via a Picture Archiving and Communication System for use and long-term record keeping (Wolf et al., 2024).