Abstract
Nanomedicine has emerged as a transformative strategy for precision-controlled drug delivery. It addresses key limitations of conventional therapeutics such as poor tissue selectivity, rapid degradation, and systemic toxicity. By employing nanoscale carriers (including lipid-based systems, polymeric nanoparticles, inorganic nanostructures, biomimetic vesicles, and hybrid platforms), researchers have developed multifunctional delivery systems capable of enhancing pharmacokinetics, biodistribution, and therapeutic index. Beyond passive accumulation through the enhanced permeability and retention (EPR) effect, modern nanocarriers integrate active ligand-mediated targeting, stimuli-responsive release mechanisms, and multilevel strategies that enable spatial, temporal, and cellular precision. Recent preclinical in vivo studies across oncology, central nervous system, and vascular disease models demonstrate significantly improved target-site accumulation, sustained drug release, and reduced off-target toxicity compared with free drug formulations. Advances in organelle-specific targeting, combination therapies, and theranostic platforms further highlight the expanding versatility of nanomedicine. However, translational barriers, including biological heterogeneity, limited predictive power of animal models, safety concerns, and manufacturing scalability, continue to challenge clinical implementation. Emerging solutions such as AI-guided nanoparticle design, humanized disease models, and organ-on-chip systems aim to bridge these gaps. Collectively, current preclinical evidence supports nanomedicine as a central pillar of precision drug delivery, with future progress expected to focus on adaptive, multifunctional, and patient-specific platforms that align with the principles of personalized medicine.
1 Introduction
Nanomedicine has gained traction as a transformative approach in targeted drug delivery as it offers the ability to improve therapeutic efficacy and reduce systemic toxicity, a major limitation of traditional therapies (Sabit et al., 2025; Tripathi et al., 2024). By utilizing nanoscale carriers such as liposomes, polymeric nanoparticles, and inorganic nanostructures, researchers build systems that shield active agents from rapid degradation, prolong circulation time, and exploit biological features, such as the enhanced permeability and retention (EPR) effect, to accumulate at disease sites (; ; Sreeharsha et al., 2021).
In addition to improving drug accumulation, current nanomedicine research has been focusing on achieving spatial, temporal, and cellular-level precision in therapeutic delivery (; Mitchell et al., 2021). Advances in stimuli-responsive materials, microenvironment-adaptive carrier design, and multistage targeting strategies now enable tighter control over the specifics of how therapeutic payloads are released in vivo (Rahim et al., 2021).
Although many recent reviews have analyzed nanocarrier materials, individual targeting mechanisms, or disease-specific applications, less attention has been given to targeted drug delivery as an integrated precision-controlled process operating across numerous biological scales. Particularly, previous reviews have often discussed stimuli-responsive release, ligand-mediated active targeting, passive targeting, and subcellular delivery as separate strategies rather than examining how these different methods can be combined to achieve coordinated cellular, temporal, spatial, and organelle-level control. In addition, the rapidly expanding preclinical literature requires critical evaluation of not only therapeutic efficacy but also of the translational limitations surrounding biological heterogeneity, pharmacokinetics, manufacturing reproducibility, and regulatory requirements. Therefore, this review synthesizes recent in vivo preclinical advances through the unifying framework of precision-controlled targeted delivery, compares the strengths and weaknesses of major nanocarrier platforms and targeting strategies, and identifies priorities necessary to improve their clinical translatability.
This review focuses on recent
in vivopreclinical studies and aims to:
highlight innovative nanocarrier platforms that allow precise drug delivery;
evaluate advanced targeting methods that enhance spatial and temporal control;
summarize recent preclinical outcomes across major disease models;
assess translational limitations in clinical adoption.
Preclinical studies have shown that nanoparticle delivery can enhance drug stability and uptake in target tissues across a variety of disease models. This delivery method shows improved outcomes when compared with free drugs. These investigations have explored both passive targeting mechanisms, which utilize specific vascular properties of tumors and inflamed tissues, and active targeting strategies that use surface ligands to bind specific cell receptors, therefore increasing cellular internalization (Yun et al., 2023).
Furthermore, the flexibility of nanocarriers allows tailored control over pharmacokinetics, biodistribution, and release profiles. This characteristic also supports multifunctional designs that combine stimuli-responsive behavior with therapy. Though there is promising preclinical performance, translating these innovations into clinical success remains a challenge due to the necessity to address issues such as off-target effects, scalability, and safety (Mitchell et al., 2021; Tripathi et al., 2024).
This review synthesizes recent preclinical progress in nanomedicine for targeted drug delivery by highlighting key advances in carrier design, targeting mechanisms, and in vivo outcomes, while also discussing the hindrances involved in translating this approach.
2 Literature search and study selection
This review was conducted using a structured narrative approach rather than a formal systematic-review methodology. Literature relevant to the topic was identified through searches of PubMed, Frontiers, Springer Nature, Science Direct, Nature, and Google Scholar. A combination of terms including “nanomedicine,” “nanoparticle drug delivery,” “targeted drug delivery,” “precision nanomedicine,” “active targeting,” “passive targeting,” “stimuli-responsive nanoparticles,” “preclinical,” and “in vivo” were used to help with the search. This review mainly focused on English-language articles published between 2020 and 2026, with additional earlier studies included when they provided important foundational or translational information. Priority was given to peer-reviewed studies that evaluated nanocarrier-based drug-delivery systems in animal disease models and included information on targeting mechanisms, pharmacokinetics, biodistribution, therapeutic efficacy, or safety. Recent review articles were used to provide broader background and identify relevant primary studies. However, quantitative preclinical findings were traced to the original research articles whenever possible. Studies limited to in vitro experiments, articles without a relevant drug-delivery component, unpublished data, and reports lacking sufficient information were excluded. Since this was a narrative review, study selection was intended to provide a representative overview of major developments rather than an exhaustive or formally risk-of-bias-assessed synthesis of all available studies.
3 Overview of nanocarrier platforms
3.1 Nanocarrier platforms in targeted drug delivery
Nanomedicine leverages a diverse range of carrier systems engineered at the nanoscale to deliver therapeutic agents in a way that is more effective than conventional methods. These platforms can be broadly grouped into organic, inorganic, and hybrid systems. Each system has distinct structural features, size ranges, drug loading/release profiles, and precision control capabilities. New engineering strategies, such as surface corona tuning, cell-membrane coating, and machine-learning-guided optimization, are improving targeting specificity and delivery in preclinical studies. Average carrier sizes range from ∼20 to 300 nm, allowing improved tissue penetration and enhanced cellular uptake. Release profiles can be tuned through material design and stimulus responsiveness to achieve temporal control over payload delivery ().
3.2 Lipid-based systems
Lipid systems are one of the oldest and most studied nanocarrier types, especially liposomes. They contain a phospholipid bilayer that can encapsulate both hydrophilic and hydrophobic drugs, protecting them from degradation and improving circulation time. Classic liposomes are ∼50–300 nm in diameter and have drug-loading efficiencies between 1% and 10% of their total mass. Liposomes can be modified with hydrophilic polymers (polyethylene glycol) to create “stealth” formations that avoid detection by the immune system and accumulate in target tissues through the enhanced permeability and retention (EPR) effect. Solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) are related systems that provide improved stability and regulated release while maintaining biocompatibility (). Ligand-targeted liposomes with surface peptides or antibodies have shown increased cellular uptake and reduced off-target toxicity compared with non-targeted versions ().
3.3 Polymeric nanoparticles
Polymeric carriers, including biodegradable ones like PLGA, chitosan, and PEGylated systems, provide highly flexible properties for drug loading and release. These nanoparticles can be engineered into micelles, dendrimers, and polymersomes, typically ∼100–1,000 nm. This allows encapsulation of small molecules, proteins, and genetic materials. When the degradation of polymer matrices is controlled, it allows sustained drug release. Similarly, surface modification with targeting ligands enhances active targeting to specific cells (). In addition, AI-designed tissue-targeting peptides have recently been used to enhance precision and personalized targeting in engineered exosome systems. This indicates a future of machine learning in nanocarrier design ().
3.4 Inorganic nanoparticles
Inorganic nanocarriers are made up of metals, metal oxides, mesoporous silica, and other mineral-based materials. These particles, such as gold, silica, and iron oxide, are often ∼10–100 nm (). They have high surface area and stability, which makes them a suitable tool for drug delivery and various applications such as imaging or stimuli-responsive release.
Mesoporous silica nanoparticles (MSNs) have a porous structure for high drug loading. Magnetic or plasmonic metal nanoparticles can be triggered externally for site-specific effects. However, there are concerns about long-term retention and potential toxicity that are influencing ongoing preclinical evaluation ().
3.5 Biomimetic nanocarriers
Engineered exosomes and cell-membrane-coated nanoparticles represent biomimetic platforms that integrate natural vesicle properties with engineered functionalities (Tikhonov et al., 2024). Exosomes are ∼30–150 nm extracellular vesicles that are capable of crossing biological barriers with low immunogenicity. Exosomes have been equipped with antibodies or peptides to enhance targeting specificity and cellular uptake for drug delivery. They also improve cargo encapsulation and decrease systemic side effects versus synthetic carriers (Rahgoshay et al., 2025). Similarly, cell membrane coated nanoparticles use membranes derived from red blood cells or cancer cells to enable immune escape and homotypic targeting. This enhances circulation and uptake by specific tissues (Yao and Zhang, 2023).
3.6 Hybrid and emerging systems
Hybrid platforms that combine organic and inorganic components to leverage complementary advantages are also being explored by researchers. This includes examples such as lipid-polymer hybrids and inorganic core-organic shell constructs. These improve stability, circulation, and targeting specificity. These systems’ main aim is to integrate the biocompatibility of organic carriers with the functional adaptability of inorganic materials. These hybrids often exhibit reduced immunogenicity, and improved precision in delivery compared with single-component carriers (). Ultimately, this approach will expand the toolkit for personalized and multifunctional therapeutic delivery (). Figure 1 illustrates how major nanocarrier platforms can be combined with passive, active, stimuli-responsive, and multilevel targeting approaches to achieve different levels of delivery precision while considering key translational factors.
FIGURE 1
Nanocarriers administered systemically utilize multiple target mechanisms to enhance spatial, temporal, and cellular precision of the drug delivery. Passive targeting relies on the enhanced permeability and retention (EPR) effect, enabling size-dependent accumulation at disease sites but with limited control due to biological heterogeneity. Active targeting enhances cellular specificity through ligand-receptor interactions that promote receptor-mediated endocytosis.
Stimuli-responsive targeting introduces temporal control by triggering drug release in response to cues such as pH, enzymes, or redox conditions. Hybrid and multilevel targeting strategies combine passive, active, and stimuli-responsive mechanisms to increase targeting accuracy, intracellular delivery, and therapeutic efficacy. Together, these approaches represent innovative paths toward precision-controlled nanomedicine.
When looking from a translational perspective, no single nanocarrier platform is superior, and the selection of a carrier should be based on the properties of the therapeutic payload, the biological target, the required release profile, and the intended route of administration. Lipid-based carriers offer high biocompatibility and encapsulate both hydrophilic and hydrophobic compounds, making them suitable for a broad range of therapeutic agents. On the other hand, their physical instability, premature drug leakage, and sensitivity to storage conditions may pose a limitation for long-term formulation stability. Polymeric nanoparticles provide greater control over degradation and sustained release, but their synthesis and purification can be complex, creating challenges in large-scale manufacturing. Inorganic nanoparticles provide high structural stability and distinctive imaging, magnetic, or photothermal functions, but limited biodegradability and possible long-term tissue retention raise greater safety concerns. Biomimetic carriers may improve immune evasion and biological targeting, but variability in their cellular source, isolation, purification, and cargo-loading efficiency complicates standardization. Hybrid systems can combine the strengths of multiple materials. However, each additional component makes manufacturing more complex and increases the number of variables requiring safety evaluation. Therefore, lipid-based and biodegradable polymeric systems may currently offer a more practical approach for clinical translation, whereas inorganic, biomimetic, and hybrid systems provide greater functional adaptability but require further improvements in reproducibility and safety.
4 Targeting strategies in nanomedicine
An essential goal in nanomedicine for drug delivery is to direct therapeutic agents to disease tissues and minimize systemic exposure. Passive targeting utilizes physiological features of pathological sites, mainly the enhanced permeability and retention (EPR) effect seen in many tumors. Due to leaky vasculature and impaired lymphatic drainage, nanoparticles of an optimal size range (∼10–200 nm) can preferentially target specific tissues and accumulate at these sites. This improves local drug concentration without modification of the active surface. However, the EPR effect is highly heterogeneous across tumor types and individual patients. Factors such as dense stromal barriers, elevated interstitial pressures, and variable vascular leakiness can limit passive accumulation to a few percent of the injected dose. As a result, strategies such as personalized EPR imaging and vessel priming are now being explored to adapt to this heterogeneity (Sun and Davis, 2021).
The clinical translatability of the EPR effect still remains controversial. Imaging studies have demonstrated that long-circulating liposomes can accumulate in some human solid tumors. However, the degree of accumulation varies significantly among patients, tumor types, and even lesions within the same patient (). In patients with metastatic HER2-positive breast cancer, the tumor accumulation of radiolabeled liposomal nanoparticles varied approximately 35-fold, while considerable uptake was also observed in clearance organs such as the liver and spleen, indicating that EPR-dependent delivery is not uniform or reliably predictable (). Furthermore, experimental data from multiple mouse models and human tumor samples have challenged the traditional view that nanoparticles enter tumors mainly through passive gaps between endothelial cells. This suggests that active transendothelial transport may contribute substantially to nanoparticle entry (Sindhwani et al., 2020). Active targeting does not necessarily overcome poor tissue accumulation: HER2-targeted immunoliposomes increased internalization by tumor cells but did not increase total tumor localization compared with otherwise similar nontargeted liposomes (). Therefore, EPR-based accumulation should not be considered a universal feature of all solid tumors. Future studies should distinguish total tumor accumulation from cellular uptake while researching imaging biomarkers for identifying patients whose tumors are suitable for nanoparticle delivery. Figure 2 shows how the EPR effect promotes nanoparticle accumulation in tumors while also highlighting important limitations such as dense stromal barriers, high interstitial pressure, and variable vascular permeability.
FIGURE 2
On the other hand, active targeting improves specificity by functionalizing nanocarriers with ligands (such as antibodies, peptides, or small molecules) that bind receptors overexpressed on target cells. This specific strategy promotes receptor-mediated endocytosis, which increases cellular internalization and improves therapeutic impact compared to passive accumulation alone. In preclinical cancer models, active targeting has been widely demonstrated, for example, by attaching nanoparticles with folate or integrin-binding ligands to recognize tumor cell surfaces (). The common ligands include folate receptors, transferrin receptors, integrin-binding peptides, and monoclonal antibodies. These can enhance intracellular drug concentrations significantly when matched to overexpressed receptors in tumors. The choice of ligand class, density, and binding kinetics influences targeting efficiency and intracellular uptake. Dynamic linkers or stimuli-cleavable tethers can unmask ligands only upon reaching the tumor microenvironment, thereby reducing peripheral off-target binding (Singh and Kumar, 2025).
Moreover, stimuli-responsive systems offer dynamic control over drug release. These types of nanocarriers are engineered to remain stable during circulation but respond to internal cues (like acidic pH, specific enzymes, elevated glutathione levels, or redox conditions) or external triggers (such as light, temperature, heat, ultrasound, or magnetic fields) (Mi, 2020). This enables controlled payload release at the target site and reduces off-target effects (Wang et al., 2016). Tumor microenvironment-responsive nanoparticles exploit acidic extracellular pH (∼6.5–6.9), redox gradients, and protease activity to trigger drug release. Meanwhile, multi-stimuli designs improve precision by integrating more than one internal cue and enabling on-demand sequential payload release ().
4.1 Multilevel targeting strategies
Multilevel targeting combines passive, active, and stimuli-responsive strategies to overcome delivery barriers and increase precision. These multistage systems can first accumulate in tumors due to the EPR effect, then engage active receptors for cellular entry, and finally release payloads in response to specific microenvironment cues. This results in higher target-to-off-target ratios than any single strategy. Multilevel nanoparticles have displayed improved tumor uptake and therapeutic efficiency in models of multidrug-resistant cancers and dense tumor microenvironment by coordinating size shifts, ligand exposure, and stimuli-based triggers (Singh and Kumar, 2025).
4.2 Organelle and subcellular targeting
Engineering nanoparticles for subcellular localization increases precision by directing therapeutics to specific intracellular locations such as mitochondria, the nucleus, or the Golgi apparatus. For example, nanoparticles with cell-penetrating or organelle-specific peptides can exploit intracellular pH differences or membrane potentials to achieve controlled release within these structures (Villaverde and Baeza, 2019). This maximizes the therapeutic effect while minimizing damage to non-target regions. Some studies have shown that dual organelle targeting (e.g., mitochondria and nucleus) can increase apoptosis in tumor cells by combining local damage and pathway disruption (). Figure 3 demonstrates how organelle-specific nanocarriers undergo cellular uptake and endosomal escape before targeting structures such as the mitochondria, nucleus, or Golgi apparatus to improve therapeutic effectiveness.
FIGURE 3
The relative value of these targeting strategies depends on the biological barrier being addressed, and increasing design complexity does not necessarily produce greater clinical benefit. Comparatively, passive targeting is simple and does not require ligand conjugation, but its effectiveness depends largely on vascular permeability, blood flow, stromal density, and other heterogeneous features of the disease microenvironment. Active targeting can improve receptor-mediated internalization and cellular specificity. However, it may not significantly increase the total amount of nanocarrier reaching a diseased tissue because the carrier must first accumulate near the target cell before ligand-receptor binding can happen. Its effectiveness may also decrease when receptor expression varies among patients or changes during disease progression. Stimuli-responsive systems provide greater temporal control over drug release, but differences in pH, enzyme activity, redox conditions, or external-stimulus penetration can result in inconsistent activation in vivo. Multilevel and organelle-specific systems offer the highest theoretical precision by integrating tissue accumulation, cellular entry, and intracellular release. However, their structural complexity may complicate characterization, manufacturing, and regulatory assessment. Accordingly, simpler systems that combine one validated targeting mechanism with controlled release may be more readily translatable than highly multi-functional platforms.
5 Recent preclinical applications
Recent preclinical research in nanomedicine shows diverse and impactful applications of targeted drug delivery systems across disease models, particularly in oncology, central nervous system disorders, and vascular/endothelial targeting. These investigations show how engineered nanocarriers can improve therapeutic efficacy, enhance biodistribution, and decrease systemic toxicity compared with conventional treatments.
5.1 Oncology applications
In the field of cancer therapy, various nanoparticle platforms have shown significant tumor inhibition in animal models by increasing drug accumulation at tumor sites through both passive and active mechanisms. For example, preclinical studies summarized in recent reviews suggest that folic acid-modified lipid nanovectors with doxorubicin showed improved tumor targeting and uptake in preclinical models, leading to enhanced antitumor effects and limited off-target toxicity. These findings highlight the ability of targeted nanocarriers to improve therapeutic indices in solid malignancies (Wei et al., 2020). Quantitative preclinical studies further demonstrate the impact of precision targeting. Reviews of preclinical studies demonstrate that ligand-functionalized nanoparticles can improve tumor accumulation and tumor-growth inhibition compared with free-drug formulations. However, the magnitude of these improvements varies greatly according to the nanocarrier, targeting ligand, tumor model, dose, and comparator formulation (; ). Preclinical nano-oncology research also underscores varied carrier types, such as PEGylated liposomes, micelles, and dendrimers, that facilitate efficient anticancer drug transport to tumor microenvironments, alongside ligand-mediated targeting strategies to further enhance specificity. Recently, reviews of preclinical combination delivery strategies suggest that nanocarriers co-delivering chemotherapeutics with RNA-based agents (such as siRNA targeting drug-resistance genes) or immunotherapies (such as immune checkpoint inhibitors) can enhance antitumor response in animal models. However, the degree of synergy and survival benefit depends on nanocarrier design, payload combination, tumor model, and dosing schedule ().
Despite these promising outcomes, the majority of oncology studies rely on murine tumor models with exaggerated EPR effects and limited immune complexity. This may overestimate nanocarrier accumulation and therapeutic efficacy compared with human tumors (Singh and Kumar, 2025).
5.2 Central nervous system (CNS) applications
In addition to oncology, CNS drug delivery has been a major focus due to the challenge of crossing the blood-brain barrier (BBB). Nanoparticles with engineered surface properties and sizes can cross the BBB, enabling targeted delivery of therapeutics for neurological diseases in preclinical settings. Precision CNS targeting using nanocarriers has shown promising results in models of neurodegenerative disorders, enhancing drug bioavailability within brain tissue and decreasing inflammation (). Figure 4 shows how targeted nanoparticles can cross the BBB through receptor binding, endocytosis, and transcytosis before releasing their therapeutic cargo into brain tissue.
FIGURE 4
Moreover, targeted polymeric nanocarriers have also been investigated for region-specific delivery within the brain, including delivery to the hypothalamus in preclinical disease models. These findings illustrate the potential of surface-functionalized nanoparticles to improve localized CNS drug delivery, although further validation in more representative models is needed. Across selected preclinical CNS models, targeted nanocarriers have been reported to increase brain exposure and reduce neuroinflammatory markers compared with nontargeted formulations. However, delivery efficiency varies according to the nanoparticle design, disease model, and condition of the blood–brain barrier (Saraswathi et al., 2025).
However, CNS studies are often constrained by short treatment durations and simplified BBB models that do not fully represent age-related, inflammatory, or disease-induced barrier heterogeneity that is observed in human neurological disorders.
5.3 Vascular and endothelial applications
Preclinical studies also cover vascular and endothelial targeting. In this context, nanocarriers are optimized to interact with vascular cells to modulate pathological processes such as atherosclerosis or thrombosis. These systems can improve the delivery of therapeutics to dysfunctional endothelial sites and enable controlled release profiles that are tailored to vascular microenvironments (). Reviews of vascular-targeting studies report that functionalized nanoparticles can enhance localization at inflamed endothelium and reduce plaque-associated disease measures compared with control formulations. However, the reported targeting efficiency and therapeutic response vary greatly among animal models and nanoparticle systems ().
Comparison across these disease areas shows that each application presents a different balance between therapeutic opportunity and translational difficulty. Oncology has produced the largest body of preclinical evidence and provides accessible measures such as tumor accumulation, growth inhibition, and survival. However, many tumor studies rely on xenograft or murine models that may exaggerate the EPR effect and fail to reproduce the stromal architecture, vascular heterogeneity, and immune complexity of cancers in humans. CNS nanomedicine addresses a major unfulfilled need because conventional therapeutics often show limited penetration across the blood-brain barrier. However, successful delivery must achieve sufficient brain exposure without interrupting barrier function or producing neurotoxicity. Results from healthy or simplified BBB models may not accurately predict delivery in aged or diseased patients. Vascular targeting may have an advantage because endothelial targets are accessible directly from the circulation and do not always require deep tissue penetration. On the other hand, blood flow, immune recognition, shear stress, and rapid clearance can reduce nanoparticle adhesion and retention at vascular lesions. Therefore, apparent efficacy should not be compared solely through fold increases in drug accumulation. In the future, preclinical studies should also consider the biological relevance of the model, immune competence, treatment duration, and long-term safety.
Altogether, these applications portray the versatility of nanomedicine in addressing disease-specific delivery obstacles. Nanoparticles enhance the localized concentration of active agents and also enable multi-modal strategies combining therapy with imaging or external trigger responsiveness. Although many of the advances are still in the preclinical stages, they offer compelling evidence that targeted nanocarrier systems have the potential to outperform traditional therapies in animal models, laying the groundwork for future translational work.
Studies were selected for Table 1 based on their relevance to precision-controlled targeted drug delivery and the availability of sufficient in vivo preclinical data. Eligible studies were mainly research articles published between 2021 and 2025 that evaluated a nanocarrier in an animal disease model and utilized at least one precision-delivery mechanism. These included ligand-mediated active targeting, biomimetic targeting, stimuli-responsive release, blood–brain barrier transport, or multistage delivery. Studies were prioritized when they reported detailed quantitative information on nanoparticle size, target mechanism, therapeutic payload, administration route, biodistribution, target-site accumulation, therapeutic efficacy, or safety. The studies that were selected also represent different nanocarrier classes and disease applications, including oncology, central nervous system disorders, and vascular disease. Studies that were excluded from the table include review articles, studies limited to in vitro experiments, studies without a disease model, and experiments that lacked sufficient quantitative information. The table is intended to provide representative examples rather than a systematic assessment of all available preclinical studies.
TABLE 1
| Nanocarrier platform | Nanoparticle size | Therapeutic payload | Targeting ligand or precision mechanism | Administration route | In vivo model | Major efficacy outcomes | Study design and key limitation | References |
|---|---|---|---|---|---|---|---|---|
| Inorganic theranostic nanoparticle: AGuIX-Bi-cRGD | 8.1 ± 5.5 nm | Gadolinium and bismuth theranostic metal chelates; radiosensitizing and MRI functions | cRGD peptide targeting RGD-binding integrins overexpressed on lung cancer cells; combined active targeting and radiation-responsive therapy | Retro-orbital intravenous injection, 300 mg/kg, followed by three daily 6 Gy radiation fractions | Subcutaneous Lewis lung carcinoma tumors in C57BL/6 mice | Increased tumor accumulation and retention; delayed tumor growth; complete tumor regression in some treated mice; prolonged median survival; increased CD3+ and CD8+ T-cell infiltration; no evident systemic toxicity | Targeted and untargeted nanoparticles were compared with and without radiation in groups of 8–9 mice. The study used one subcutaneous lung-cancer model and provided limited long-term safety data | Muradova et al., 2025 |
| Carrier-free peptide–drug nanoparticle: DPA NP | 163.2 ± 1.9 nm | Doxorubicin and monophosphoryl lipid A | iRGD tumor-homing peptide combined with an MMP-2-responsive peptide; enables tumor penetration, microenvironment-responsive release, and simultaneous tumor-cell and dendritic-cell targeting | Intravenous administration on days 7, 12, and 17 after tumor implantation | B16 melanoma model in mice | Significantly inhibited primary tumor growth and reduced tumor burden; nearly eliminated visible lung metastases; stimulated antitumor immune responses; further enhanced tumor suppression and recurrence prevention when combined with immune-checkpoint inhibition | Treatment groups generally included 5 mice, while metastasis and recurrence studies included 3. Small sample sizes, one melanoma model, and formulation complexity limit translation | |
| Platelet-hitchhiking polymer–drug conjugate: P@NPP | NPPD: 174 ± 62.5 nm; platelet-conjugated P@NPPD: 600.9 ± 60.7 nm | DMXAA vascular-disrupting and STING-activating agent | Natural platelet adhesion to exposed collagen within tumor vasculature; coagulation-cascade-mediated self-amplification and esterase-responsive drug release | Intravenous administration | Subcutaneous CT26 colorectal tumors in mice | Produced 2.61-fold greater tumor accumulation than non-platelet NPPD after 24 h; achieved an 89.1% tumor-suppression rate; prolonged survival and reduced systemic toxicity | The platelet-targeted formulation was compared with PBS, free drug, and non-platelet nanoparticles. Some experiments used only 3 mice, and the main efficacy-group size was not clearly reported | |
| ITP-modified lipid nanoparticle: ITP-LNP/siBACE1 | Size of the therapeutic ITP-LNP was not stated numerically in the main article text; a related PEG-ITP-modified liposome formulation measured 87.40 ± 9.81 nm | siRNA targeting β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) | ITP peptide binds the transmembrane domain of the insulin receptor, enabling allosteric receptor targeting and BBB penetration without competing with endogenous insulin | Tail-vein injection, 1 mg/kg siRNA every 2 days for seven injections | Eight-month-old APP/PS1 double-transgenic Alzheimer’s disease mice | Enhanced delivery and stability of siBACE1 in the brain; improved novel-object-recognition and Morris-water-maze performance; inhibited BACE1 expression in the hippocampus and cortex to levels similar to wild-type controls; no evident organ toxicity or inflammatory cytokine response | Behavioral outcomes used 6 mice per group, while protein analyses used 3. The study used one Alzheimer’s disease model with limited treatment duration and long-term safety assessment | Tang et al., 2025 |
| Monocyte-membrane-coated PLGA nanoghost | 292 nm by hydrodynamic measurement; approximately 62.5 nm by TEM with a 5 nm membrane coating | Gliclazide; approximately 4.68% drug loading | Biomimetic monocyte membrane promotes immune compatibility and homing to inflamed endothelium and atherosclerotic plaques | Intravenous administration | Experimentally induced atherosclerosis in rabbits | Reduced CD14+ macrophage abundance in aortic plaques from 46.98% in untreated animals to 7.7%; decreased plaque lesions, foam cells, and lipid-laden macrophages; promoted anti-inflammatory M2 macrophage polarization | Approximately 8 rabbits were included per treatment group, with 3 used for pharmacokinetics. No free-drug control was included, and mortality occurred during disease induction | |
| Platelet-anchored, ROS-responsive protein nanoassembly: P-Mn/TI@mHSA | Protein nanoassembly: approximately 144.37 nm before platelet anchoring; disassembles into approximately 12–15 nm protein blocks in a ROS-rich environment | Mn3O4 antioxidant nanozyme and a TRAF6-signaling inhibitor | Natural platelet binding to injured endothelium and exposed plaque matrix; mannose-mediated macrophage targeting; ROS-cleavable linkers produce size transformation and deeper plaque penetration | Intravenous administration | High-fat-diet-induced atherosclerosis in ApoE−/− mice | Produced an aortic plaque area 5.82-fold smaller than that of the PBS group; reduced necrotic-core and inflammatory-cytokine levels; improved intraplaque delivery and macrophage uptake; enabled MRI visualization of atherosclerotic lesions | Five treatment groups containing 5 mice each were used to examine targeting and therapeutic effects. The study used one mouse model, short safety follow-up, and a complex platelet-based formulation |
Preclinical nanomedicine studies demonstrating precision-controlled targeted delivery (2023–2025).
Particle sizes are in hydrodynamic diameters unless specified otherwise. MMP-2, matrix metalloproteinase-2; MPLA, monophosphoryl lipid A; MRI, magnetic resonance imaging; BBB, blood–brain barrier; BACE1, β-site amyloid precursor protein-cleaving enzyme 1; ROS, reactive oxygen species; TRAF6, tumor necrosis factor receptor-associated factor 6.
Study designs and limitations were narratively assessed from the original articles. Direct comparison should be made cautiously because the studies varied in animal model, sample size, control groups, treatment duration, and outcome measure.
6 Pharmacokinetics, biodistribution, and safety
Effective nanomedicine requires careful consideration of in vivo behavior and safety. Preclinical studies show that engineered nanoparticles can improve circulation time, enhance target tissue accumulation, and reduce off-target toxicity compared with free drugs. Surface modification (such as PEGylation) helps evade immune clearance, and ligand-mediated targeting enhances cellular uptake. From a pharmacokinetic view, nanoparticle size, shape, and surface corona composition strongly influence circulation half-life and systemic exposure. Optimized formulations demonstrate increased area under the curve (AUC) and improved target-to-nontarget exposure ratios relative to free drugs ().
In animal models, biodistribution studies reveal preferential accumulation in diseased tissues, but variability exists due to tumor heterogeneity and organ-specific clearance. Targeting efficiency is often measured using indices such as tumor-to-organ accumulation ratios. These highlight how precise control over nanoparticle physicochemical properties improves tissue selectivity and limits unintended disposition in clearance organs (e.g., the liver and spleen) (). Immunological interactions represent an additional layer of control. Surface chemistry and protein corona formation can modulate opsonization, macrophage uptake, and complement activation, directly shaping biodistribution and immunotoxicity.
Assessments of toxicity indicate that biocompatible carriers usually minimize adverse effects, but long-term retention and immune responses are still critical challenges for translation (Sreeharsha et al., 2021). Most importantly, preclinical evidence suggests that enhanced spatial and temporal control over drug release (achieved through controlled degradation or stimuli-responsive mechanisms) can significantly reduce systemic toxicity while maintaining therapeutic efficacy ().
Optimization of pharmacokinetics and biodistribution requires balancing competing physicochemical properties rather than maximizing circulation time or cellular uptake alone. Smaller nanoparticles may penetrate tissues more effectively but can undergo rapid renal elimination, whereas larger particles tend to circulate differently and are more likely to be captured by macrophages in the liver and spleen. A positively charged surface can enhance interaction with cellular membranes, but it may also increase nonspecific protein binding, immune recognition, and toxicity. Similarly, PEGylation and other hydrophilic coatings can extend circulation by reducing immediate clearance, yet long-lasting systemic exposure may increase the duration of contact with healthy organs and does not guarantee effective delivery into diseased tissue. Increasing ligand density might strengthen receptor binding, but excessive surface functionalization can change protein-corona formation, particle stability, and uptake by clearance organs. Consequently, high blood exposure should not automatically be interpreted as favorable pharmacokinetics. High target accumulation should be evaluated relative to accumulation in the liver, spleen, kidneys, and other organs. Therefore, safety evaluation should include repeated-dose studies, long-term clearance, immunological responses, biodegradation, and quantitative recovery of the administered nanoparticle. Formulations that achieve a moderate improvement in targeting with predictable clearance and reproducible manufacturing may ultimately be more valuable clinically than systems that show exceptional short-term efficacy but uncertain long-term performance.
7 Key challenges in preclinical translation
Although there is significant preclinical progress, several obstacles continue to hinder the translation of nanomedicine-based drug delivery systems. A major barrier is biological heterogeneity, as variability in disease microenvironments can significantly affect nanoparticle accumulation and therapeutic efficacy, reducing the reliability of passive targeting strategies. Moreover, scale-up and reproducibility remain difficult, since nanoparticle synthesis methods optimized at the laboratory level often fail to maintain consistency in size, surface chemistry, and drug loading during large-scale production. Safety concerns also persist. These include long-term biodistribution, immune responses, and potential organ accumulation, which may not always be fully captured in short-term animal studies. Furthermore, preclinical models may not accurately predict human responses, which complicates regulatory evaluation and clinical translation.
Regulatory translation of nanomedicine is complicated by the structural complexity of nanoscale delivery systems and the need to evaluate product characteristics that potentially differ from those of conventional drug formulations. Successful clinical development requires rigorous control of critical quality attributes, including surface charge, particle size distribution, morphology, drug-loading efficiency, release kinetics, stability, sterility, purity, and batch-to-batch reproducibility. Even small differences in material properties can alter the pharmacokinetics, biodistribution, cellular uptake, and safety of nanocarrier formulations (U.S. Food and Drug Administration, 2022). Consequently, scalable production processes should be developed under Good Manufacturing Practice conditions using validated analytical methods and clearly defined acceptance criteria (). During early formulation and process development, incorporating quality-by-design principles may help identify critical material attributes and manufacturing parameters, improve reproducibility, and reduce the gap between laboratory-scale innovation and clinical translation ().
Clinically approved nanomedicines provide important benchmarks for evaluating the translational significance of recent preclinical findings. Liposomal doxorubicin (Doxil), albumin-bound paclitaxel nanoparticles (Abraxane), and the lipid-nanoparticle-formulated siRNA therapy patisiran (Onpattro) show that nanocarriers can achieve clinical value by altering drug disposition, supporting delivery of otherwise difficult therapeutic payloads, and producing reproducible formulations suitable for regulatory approval (U.S. Food and Drug Administration, 1999; U.S. Food and Drug Administration, 2013; U.S. Food and Drug Administration, 2018). However, these successes should not be misinterpreted as evidence that increasing targeting complexity will improve clinical outcomes. For example, MM-302, a HER2-targeted liposomal doxorubicin formulation, advanced from promising preclinical investigations to early clinical evaluation. On the other hand, the randomized HERMIONE trial was terminated after a futility analysis indicated that the treatment was unlikely to provide a benefit over the control therapy (Munster et al., 2018; ). This contrast highlights how improved target recognition, pharmacokinetics, or tumor accumulation in preclinical studies does not necessarily translate into superior clinical efficacy. Therefore, preclinical fold improvements should be interpreted relative to clinically established formulations and validated through comparative studies that assess meaningful therapeutic benefit, manufacturing reproducibility, patient heterogeneity, and safety.
Emerging solutions to these limitations include the use of humanized and patient-derived animal models. This better recapitulates human immune responses, vascular architecture, and disease heterogeneity, thereby improving the predictive power of preclinical nanomedicine studies. At the same time, artificial intelligence (AI) and machine-learning-based optimization frameworks are increasingly being applied to nanoparticle design. This approach enables data-driven tuning of size, composition, and surface chemistry to maximize targeting precision and minimize off-target accumulation (Ros et al., 2026). Another solution includes utilizing microfluidic and organ-on-chip platforms. These offer scalable and reproducible systems for evaluating nanoparticle transport, cellular uptake, and toxicity under physiologically relevant flow conditions. Ultimately, they bridge the gap between conventional in vitro assays and in vivo models ().
To address these challenges, standardized characterization methods, improved disease models, and closer integration of engineering, biology, and regulatory science will be required.
This review has several limitations. Since it was conducted as a structured narrative review rather than a systematic review, the literature search was intended to provide a representative overview and may not have identified every single relevant study. The selection of studies with detailed preclinical and quantitative findings may have also introduced selection bias. This may be because studies reporting positive outcomes are more likely to be published and discussed. Additionally, significant variation in nanocarrier composition, dosing schedules, animal models, control groups, and outcome measures prevented direct quantitative comparison across studies. A formal risk-of-bias assessment or meta-analysis was not conducted. Therefore, the comparisons and findings presented in this review should be interpreted as a critical narrative synthesis rather than an exhaustive evaluation of all available evidence.
8 Future directions
Future progress in targeted nanomedicine will be centered on smart and multifunctional platforms that combine therapy, diagnostics, and real-time responsiveness. Advances in stimuli-responsive nanocarriers are expected to improve spatial and temporal control of drug release by allowing therapeutic payloads to respond to disease-associated signals. There is also increasing attention on personalized medicine, where carrier design will be tailored to patient-specific disease characteristics. In addition, blending nanocarriers with gene therapy and immunotherapy holds promise for synergistic treatment effects. Further refinement of material design and improvement of preclinical models will be critical for enhancing translational success (Wang et al., 2016). Stimuli-responsive nanomaterials can improve controlled release, but their future development will require attention to safety, manufacturing scalability, delivery efficiency, and long-term evaluation.
A vital future research priority is the development of preclinical models that more accurately reproduce human physiological conditions and disease heterogeneity. Microfluidic and organ-on-chip platforms may help address this need because they can reproduce biological gradients, dynamic fluid flow, tissue-specific microenvironments, and interactions among numerous cell types. These systems may provide more physiologically relevant evaluation of nanoparticle transport, therapeutic performance, cellular uptake, and toxicity than conventional static cell-culture models. However, organ-on-chip findings should be combined with appropriate in vivo models rather than treated as total replacements for animal studies ().
The standardization of nanocarrier characterization and experimental reporting should also be treated as a major research priority. Future studies should consistently report important physicochemical and biological characteristics such as particle size distribution, morphology, drug-loading behavior, surface properties, stability, biological interactions, and descriptions of the experimental methods used. When there is inconsistent characterization and reporting, it makes it difficult to compare results across studies and determine why seemingly similar nanocarriers are producing different outcomes. Minimum reporting standards covering material characterization, biological characterization, and experimental procedures have therefore been proposed to improve reproducibility and allow valid quantitative comparisons among nanomedicine systems ().
Future studies should also establish clearer quantitative criteria for deciding whether a targeted nanocarrier is actually more effective than a simpler one. Studies should distinguish improvements caused by nanoparticle encapsulation from those caused solely by active targeting or stimuli-responsive release. Therefore, targeted formulations should be compared with appropriate controls, including the free drug and a comparable nontargeted nanocarrier. Researchers should also determine whether improvements in target-site accumulation are accompanied by reduced exposure in clearance organs and significant improvements in therapeutic efficacy and safety. In addition, standardized quantitative comparisons would make it much easier to identify which features produce reproducible advantages and which add complexity without substantial therapeutic benefit ().
Smart nanocarriers capable of adaptive behavior (such as responding to stimuli) are expected to play a pivotal role in achieving precision-controlled drug delivery across heterogeneous disease environments (Srivastava, 2025). The integration of nanocarriers with gene-editing tools, RNA therapeutics, and immunomodulatory agents represents a key future direction. This will allow multi-layered therapeutic control and personalized interventions. Future studies should also demonstrate that each targeting ligand, responsive element, or therapeutic payload provides a measurable advantage over a simpler delivery system. For RNA-based therapies in particular, continued optimization of safety, large-scale manufacturing, delivery efficiency, and long-term biological responses will be necessary for successful translation.
Artificial intelligence and computational modeling may further support the development of personalized nanomedicine by identifying relationships among physicochemical characteristics, biodistribution, nanocarrier composition, toxicity, and therapeutic response. Computational models that integrate patient-specific factors with predicted nanocarrier behavior may eventually help simulate nanoparticle distribution and guide the selection of delivery strategies. However, these models should be supported by standardized experimental datasets and validated through in vivo studies before being used to guide decisions in the clinic (; ).
Finally, manufacturing and regulatory considerations should be incorporated during the beginning stages of nanocarrier design. Future platforms should use reproducible production methods that can maintain consistent particle characteristics, drug loading, stability, and biological outcomes between batches. The FDA states that nanomaterial-containing drug products may have attributes that differ from conventional products and may therefore require close examination of pharmaceutical quality and chemistry, manufacturing, and controls. Designing nanocarriers with these requirements in mind may help reduce the gap between promising preclinical outcomes and clinical development (U.S. Food and Drug Administration, 2022).
Overall, the future of targeted nanomedicine will depend largely on balancing functional innovation with clinical practicality. Most importantly, increasing complexity should be justified by clear improvements in efficacy, safety, or target precision. Progress towards clinical application will require more predictive disease models, quantitative evaluation of targeting performance, standardized characterization, long-term safety studies, and scalable manufacturing. Addressing these priorities will help align nanomedicine development with the principles of precision and personalized medicine.
9 Conclusion
Recent preclinical research demonstrates that nanomedicine can improve drug stability, tissue accumulation, pharmacokinetics, controlled release, and therapeutic efficacy across oncology, central nervous system, and vascular disease models (Mitchell et al., 2021; Tripathi et al., 2024). Lipid-based, inorganic, biomimetic, polymeric, and hybrid platforms each offer distinct benefits, but no single nanocarrier is universally suitable for every therapeutic payload or disease environment. Therefore, carrier selection must account for the biological target, required release profile, administration route, biodegradability, safety, and feasibility of large-scale manufacturing.
The evidence reviewed also demonstrates that greater targeting complexity does not necessarily produce better translational value. Passive targeting remains heavily influenced by vascular and disease heterogeneity, while active targeting may enhance receptor-mediated cellular uptake without consistently increasing the total number of nanocarriers reaching the target tissue (; ; Sindhwani et al., 2020). Stimuli-responsive, multilevel, and organelle-specific systems can improve spatial and temporal control, but their additional components may make characterization, safety assessment, reproducibility, and regulatory approval complicated. Consequently, simpler biodegradable formulations that offer measurable therapeutic benefits, predictable clearance, and reproducible manufacturing may sometimes provide a more practical translational pathway than highly multifunctional systems.
The large gap between preclinical promise and clinical application is therefore not limited to delivery efficiency alone. More standardized nanoparticle characterization, predictive disease models, quantitative biodistribution measurements, appropriate free-drug and nontargeted controls, long-term safety evaluation, and scalable manufacturing are also required (; U.S. Food and Drug Administration, 2022). Caution is necessary when interpreting large fold improvements gained from small animal studies because differences in tumor vascularity, immune responses, blood-brain barrier properties, dosing schedules, and experimental durations limit direct comparison and may tend to overestimate performance in humans.
Overall, current evidence supports the preclinical feasibility of precision-controlled nanomedicine but does not yet establish the clinical superiority of increasingly complex targeted systems. Future progress will depend on balancing functional innovation with clinical practicality and biological relevance. Nanocarriers that show reproducible benefits in representative models, meaningful improvements over simpler formulations, acceptable long-term safety, and compatibility with regulatory requirements will have the strongest potential to reach clinical use. Continued integration of materials science, disease biology, pharmacology, and regulatory science will be essential for translating precision-controlled nanomedicine into effective and safe therapies.
Statements
Author contributions
AS: Conceptualization, Validation, Software, Writing – review and editing, Writing – original draft. PB: Supervision, Writing – review and editing.
Funding
The author(s) declared that financial support was not received for this work and/or its publication.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
biomedical applications (E), nanomedicine, preclinical applications, targeted drug therapy, theranostic platforms
Citation
Sureshkumar A and Balu P (2026) Innovative nanomedicine strategies for precision-controlled targeted drug delivery: recent preclinical progress. Front. Biomater. Sci. 5:1916503. doi: 10.3389/fbiom.2026.1916503
Received
22 June 2026
Revised
07 August 2026
Accepted
11 August 2026
Published
07 September 2026
Volume
5 - 2026
Edited by
Raj Kumar, University of Petroleum and Energy Studies, India
Reviewed by
Amin Orash Mahmoudsalehi, Monterrey Institute of Technology and Higher Education (ITESM), Mexico
Sarhan Rashid, Wasit University, Iraq
Updates
Copyright
© 2026 Sureshkumar and Balu.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Prakash Balu, prakazbt@gmail.com, prakashb.sls@vistas.ac.in
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.