Advancing Nanotechnology in Targeted Cancer Therapy: From Passive Targeting to Smart Delivery Systems

Azza Moustafa Fahmy
Parasitology Department, Theodore Bilharz Research Institute, Cairo, Egypt
Correspondence to: azzafhmy@gmail.com

DOI: https://doi.org/10.70389/PJS.100052

Additional information

• Ethical approval: N/a
• Consent: N/a
• Funding: No industry funding
• Conflicts of interest: N/a
• Author contribution: Azza Moustafa Fahmy – Conceptualization, Writing – original draft, review and editing
• Guarantor: Azza Moustafa Fahmy
• Provenance and peer-review:
  Commissioned and externally peer-reviewed
• Data availability statement: N/a

Keywords: Nanocarriers, Liposomal formulations, Enhanced permeability and Retention (epr), Stimuli-responsive systems, Blood-brain barrier.

Peer-review
Received: 18 December 2024
Revised: 19 January 2025
Accepted: 19 January 2025
Published: 31 January 2025

Introduction

One out of six fatalities is attributed to cancer, which is a substantial global health burden. In 2020, there were an estimated 10.3 million deaths and 19.3 million new cases of cancer worldwide; 70% of the deaths occurred in low- and middle-income countries.¹ The major factors contributing to this dismal outcome are a lack of early diagnosis methods and a shortage of therapies.²

Current Therapeutic Limitations

Traditional cancer treatments, including radiation and chemotherapy, provide numerous clinical challenges. Neuropathy, myelosuppression, alopecia, nephrotoxicity, and cardiotoxicity are dose-limiting adverse effects stemming from the drugs’ insufficient selectivity for neoplastic cells and the necessity for elevated dosages to attain therapeutic efficacy.³ The inadequate water solubility of numerous chemotherapeutic agents results in formulation challenges and adverse pharmacokinetic properties.^4,5

Nanotechnology: An Innovative Approach

By improving therapeutic efficacy and minimizing side effects, nanotechnology has completely changed the way that cancer is treated.⁶ Various biological interactions are facilitated by the unique physicochemical properties that are imparted by manipulating materials at the nanoscale (1–100 nm).⁷ Nanocarriers’ substantial surface-area-to-volume ratios and nanoscale dimensions (less than 500 nm) enhance tumor targeting and drug pharmacokinetics.⁸

Targeting Mechanisms and Advanced Systems

There are two main active methods of focus in the field of cancer nanomedicine. According to Yao et al.,⁹ passive targeting depends on the enhanced permeability and retention (EPR), which is when nanoparticles accumulate in the tumor tissue because of compromised vasculature and poor lymphatic drainage. Chehelgerdi et al.⁷ define active targeting as a modification of nanocarrier surfaces through the use of certain ligands that attach to the receptors of cancer cells.

Hybrid Nanocarriers Integrating Passive and Active Targeting Mechanisms

Novel hybrid nanocarriers are suggested as a way to get around the drawbacks of individual targeting techniques. These nanocarriers combine passive targeting through the EPR effect with active targeting through surface modifications. These systems exploit the unique features of tumors, such as leaky vasculature combined with receptor-ligand interactions to improve specificity. For example, dual functional nanoparticles may be constructed with PEGylation to prolong circulation time and folate or peptide ligands for specific attachment to overexpressed tumor receptors.^10,11 In addition, pH sensitive coatings or thermoresponsive liposomes such as ThermoDox are also stimuli-responsive materials for controlled drug release, where systemic toxicity is reduced through the release of drugs into cancer tumor sites.^12,13 These hybrid approaches represent a hopeful strategy for improving therapeutic efficacy while reducing off-target effects (Figure 1).

The Scope of Review: This paper presents an important review of nanotechnology in targeted cancer therapy. It focuses on current targeting mechanisms, clinical outcomes, and nanocarrier systems. Some elements that the current approach to cancer therapy was addressing, but which nanotechnology does also, are drug resistance, systemic toxicity, and therapeutic efficiency.

Nanocarrier Systems: An effective and successful nanocarrier must (1) avoid the premature leak of therapeutic agents during circulation in the blood under physiological conditions; (2) possess targeting ability to accumulate at the tumor sites to provide a sufficient dose of therapeutic agents and reduce the severe side effects of therapeutic agents on healthy tissues; (3) show biocompatibility and exhibit biodegradability.¹⁴

Liposomal Formulations: Recently reported studies have identified that drug delivery is effectively achieved through lipid-bilayer liposomes. Due to their amphiphilic structure, they have the ability to conceal drugs inside them and carry them to the site of need while allowing controlled release.¹⁵ By 2023, liposomes were used in 15 FDA-approved medicines, making them the most successful nanocarrier system for treatment.16 They are widely used because of their high flexibility, low immunogenicity, and established efficacy.¹⁷ The liposomal formulations authorized by the FDA include Doxil C-130 (non-PEGylated liposomal daunorubicin) for multiple myeloid leukemia and ovarian cancer. These preparations have enhanced pharmacokinetics and reduced cardiotoxicity. They have also improved tumor targeting by the EPR effect. Their design in a lipid bilayer permits controlled drug release at tumor sites while protecting drugs from degradation during circulation.

Limitations:

1. Low EPR Efficiency: The average size of liposomes of ~100 nm leads to liposomes being susceptible to hepatic and renal metabolism to excretion outside the body, leading to poor drug delivery efficiency with a total utilization rate of less than 0.7%, resulting in unfavorable treatment outcomes.¹⁸
2. Limited Tumor Penetration: According to Sharifi et al., liposomes have been found to achieve only partial penetration into tumor cores. Such shallow penetration compromises their therapeutic efficiency.¹⁹
3. Immunogenicity Risks: After a couple of uses, little to no bio-agents have an effect on the body; this is a side effect of accelerated blood clearance (ABC). A ligand that was once effective has now lost its potency due to ABC. This is an effectiveness risk caused by immunogenicity.²⁰

Proposed Solutions:

• EPR Optimization: Passive targeting combined with nonoperation is one of the CNS treatment techniques. Anti-angiogenic agents are also used to passively target tumor sites and aid in the enhancement of EPR.^19,21
• Active Targeting: Functionalize liposomes with ligands for receptor-mediated endocytosis to enhance selective uptake by cancer cells.²²
• Stimuli-Responsive Systems: Stimuli-responsive drug delivery systems have been created so as to reduce the negative effects produced by lossy conventional chemotherapy, targeting over a specific range of times or spaces such as the tumor, but there are exogenous and endogenous stimuli used. The responsive nanocarrier utilizes internal biological stimuli such as pH, redox, and enzyme and external stimuli like temperature and ultrasound, to modulate drug release systems and deliver imaging and chemotherapeutic agents to help fight cancer.¹³ For example, develop thermoresponsive liposomes like ThermoDox that release drugs at specific temperatures to target tumors more precisely while minimizing systemic toxicity.¹⁴

Polymeric Nanoparticles

Active substances can be encapsulated within or on the surface of polymeric nanoparticles, which have a diameter ranging from 1 to 1000 nm. They have considerable promise for precise drug delivery in many disorders.²³

Types and Characteristics: According to Thepa and Kim (2023), polymeric nanoparticles improve cancer therapy by facilitating regulated release, shielding medications from environmental influences, and increasing bioavailability.²⁴ PEG-poly (lactic acid) formulations like Genexol PM, PEG-poly (aspartic acid) systems like NK105 and NK911, and albumin-based particles like Abraxane²⁵ are the main polymeric nanocarrier systems.²⁶

Clinical Progress: NK105 shows a 90-fold increase in plasma concentration over free paclitaxel. Genexol PM is approved for breast, lung, and ovarian cancers. CRLX101 is in Phase II trials for non-small-cell lung cancer.²⁵ These carriers improve cancer treatment by offering adaptable structures, controlled release, and enhanced targeting while reducing systemic toxicity.

Limitations:

1. Biocompatibility Issues: Some of the polymers are capable of inducing immunogenic responses or can exhibit chronic toxic effects, which can be a security problem in the long run.²³
2. Manufacturing Scalability: Batch reproducibility is often hard to sustain in these types of goods as the synthesis processes get quite complicated.²⁷
3. Restricted Tumor Infiltration: Physiological barriers present in the tumor microenvironment (TME) induce limited tumor infiltration similar to liposomes.²⁶

Proposed Solutions:

• Biocompatible Polymers: Biodegradable polymers such as poly (lactic-co-glycolic acid) PLGA should be used to decrease toxicity, but not at the cost of effectiveness.^23,28
• Scalable Manufacturing: Micromanufacturing explores the use of microfluidics technology to improve batch consistency on a larger scale.²³
• Multifunctional Nanoparticles: Nanoparticles that are multifunctional: Combine nanoparticle-mediated drug delivery with imaging agents in polymeric nanoparticles to monitor the delivery of the drug through the tumor and its response.²⁶

Smart Nanoparticles

Stimuli-Responsive Systems: Smart nanoparticles accurately distribute medications by responding to biological signals or environmental stimuli. By integrating many functionalities, they can enhance therapeutic efficacy while minimizing adverse effects.²⁹

Multifunctional Capabilities: These designs combine diagnostic imaging with therapeutic functions for real-time monitoring and improved targeting mechanisms.³⁰

Advanced Formulations of the Stimuli-Responsive Systems: Stimuli-responsive systems like ThermoDox release drugs at specific temperatures or pH levels to target tumors accurately while minimizing systemic toxicity.^16,25 This revised section consolidates overlapping content on FDA approvals and clinical efficacy while maintaining a clear focus on the unique advantages of each nanocarrier system type.

Limitations:

1. Complex Design Requirements: The formation of multifunctional smart nanoparticles with exact responsiveness is both expensive and technically demanding.^13,29
2. Challenges of the TME: The heterogeneous characteristics of the TME hinder activation at the specific site.^13,29
3. Obstacles to Regulation: The design of smart nanoparticles is more complex than that of simpler systems, complicating the regulatory approval process.³¹

Proposed Solutions:

• Artificial Intelligence (AI) Integration: AI can optimize nanoparticle design by predicting drug release patterns and improving targeting efficiency, achieving a prediction accuracy of 92%.³²
• Microenvironment-Specific Triggers: Enhance targeted delivery by developing nanoparticles that respond to specific tumor characteristics like hypoxia or particular enzymes.²²
• Standardized Protocols: Establishing uniform characterization processes for smart nanoparticles can facilitate regulatory pathways (Table 1).³³

Table 1: Comparative analysis of nanocarrier systems in cancer therapy.
Feature	Liposomes	Polymeric Nanoparticles	Smart Nanoparticles
Clinical Approvals	Doxil, Vyxeos	Genexol PM, NK105	Limited clinical trials
Drug Release Mechanism	Passive (EPR effect)	Controlled release	Stimuli-responsive
Targeting Capability	Enhanced with PEGylation	Active targeting possible	High precision via stimuli
Challenges	Low EPR efficiency; ABC effect	Biocompatibility; scalability	Complex design; regulatory issues

Fundamental Targeting Mechanisms

Cancer nanomedicine employs two primary targeting approaches: passive and active targeting, each exploiting distinct mechanisms for therapeutic delivery.

Passive Targeting

The EPR impact increases nanoparticle accumulation in tumor tissues by impairing lymphatic outflow and vasculature.¹⁰ The distinctive characteristics of tumor vasculature promoted nanoparticle extravasation, including compromised basement membranes and enlarged endothelial gaps (~1 μm).²² Rapid tumor proliferation induces vascular hyperpermeability by the overproduction of mediators, including bradykinin, nitric oxide, and VEGF (Figure 2).³⁴

Clinical Translation and Enhancement

Despite its theoretical potential, EPR-mediated transport yields an accumulation in tumors that is less than double that of normal tissues.³⁵ Tumor heterogeneity and high interstitial fluid pressure prevent core tumor penetration.¹⁰ A variety of enhancement strategies have emerged to optimize EPR-based delivery, including pharmacological therapies using vascular modulators, physical enhancement techniques such as heat and sonoporation, and methods for vascular normalization.²²

Active Targeting

Active targeting improves passive systems via molecular recognition. Surface-modified nanocarriers with specific targeting moieties are employed to facilitate selective tumor cell adhesion.¹¹ Targeting proteins, peptides, and antibodies against tumor-specific antigens by receptor-mediated endocytosis provides exact cellular interaction (Figure 3).²²

Advanced Design Parameters

According to Suk et al.,³⁶ surface engineering standards call for PEGylation for prolonged circulation, neutral surface charge to reduce nonspecific interactions, and exact control of nanocarrier size (10–100 nm) for maximum tumor penetration. Current developments comprise stimuli-responsive drug release procedures and multifunctional stages that participate in imaging and therapeutic functions. AI-driven design optimization has boosted targeting effectiveness through unconventional computational techniques.³⁷ While additional optimization is essential to get past present restrictions, the blend of passive and active targeting mechanisms, assisted by new technology, offers a strategy for refining therapeutic effectiveness in the management of cancer.²²

Biological Barriers in Cancer Nanomedicine

The successful delivery of nanotherapeutics encounters multiple physiological obstacles that significantly impact therapeutic efficacy.

Blood-Brain Barrier (BBB)

The delivery of nanotherapeutics for brain malignancies is considerably obstructed by the blood-brain barrier, which inhibits around 98% of small-molecule medications and practically all macromolecular therapies.³⁸ Endothelial cells, active efflux transporters, and transport proteins that govern molecular access from this selective barrier. Brain tumors can compromise the integrity of the BBB, leading to a heterogeneous blood-tumor barrier with variable permeability; yet, substantial delivery problems persist because of nonuniform distribution and elevated interstitial pressure (Figure 4).²⁴

TME

The TME is an intricate and dynamic unit, including stromal cells, immune cells, blood vessels, and extracellular matrix, which is closely related to the incidence and progress of cancers, as well as their treatment.³⁹ The intricate and diverse characteristics of the cancer cell microenvironment present substantial challenges for nanoparticle-mediated drug delivery.⁴⁰ Because of the uneven patterns of the vascular structure and the permeability of the arteries, the delivery of medication varies across different tumor sites. Within the tumor mass, various forms of extracellular matrix create physical barriers that hinder effective medication delivery.⁴¹ Tumor cells in various locations respond biologically to treatment differently due to their distinct microenvironmental contexts.⁴²

Immune System Synergy

Substantial interactions between nanocarriers and the immune system profoundly influence their therapeutic efficacy. According to La-Beck et al.,⁴³ these interactions cause the initiation of complement and the opportunity for false-allergic reactions. While interactions with immune cells in the TME can either enhance or decline therapeutic efficiency, the mononuclear phagocyte system quickly removes nanoparticles from the bloodstream. These immune interactions have an extensive influence on pharmacokinetics, biodistribution, and finally therapeutic benefits.⁴⁴ These biological difficulties may be overcome thanks to recent improvements in surface modification techniques and nanocarrier design. To recover barrier diffusion while conserving therapeutic efficiency, surface engineering methods make use of specific targeted ligands and stealth features.⁴⁵ The improvement of these delivery mechanisms requires a comprehensive examination of nanocarrier characteristics and a methodical measurement of their efficacy in biological systems.

Clinical Translation in Cancer Nanomedicine

There are a number of complex problems that must be fixed logically as cancer nanomedicine transfers from lab research to clinical use.

Regulatory Framework

Regulatory challenges stem from the unique physicochemical characteristics of nanomedicine formulations. As per Đorđević et al.,⁴⁶ the FDA and EMA have stringent regulations for assessing nanoformulations, which include comprehensive physicochemical characterization and expert safety assessments. The frequent failure of appealing laboratory results to yield similar therapeutic efficacy in human subjects exacerbates the gap between preclinical and clinical outcomes, complicating the licensing procedure.⁴⁷

Patient Selection and Stratification

Advanced methods of patient selection are required since the effectiveness of nanomedicine varies greatly depending on physiological and malignant parameters. Improving patient products now depends on the detection of certain biomarkers for forecasting treatment response.⁷ This modified approach requires the use of sophisticated analytical tools and a close inspection of the unique patient features that impact the efficiency of treatment.

Considerations in Manufacturing

Development costs can surpass $2.5 billion, and scale-up issues mostly impact complicated formulations that require numerous synthesis processes.⁴⁸ Maintaining quality consistency in large-scale production is an ongoing challenge, and stability issues across the product lifecycle can undermine both physical integrity and therapeutic efficacy.⁷

Establishing Alternatives

Recent technological advancements suggest that these translation issues may be resolved. Innovative manufacturing methods and microfluidic technology are anticipated to resolve issues related to scalability and repeatability.⁷ AI has been integrated into design optimization and quality control measures to transcend the limitations of traditional inventions.³⁰ These are several interrelated issues that will eventually connect lab successes with clinical efficacy if they are resolved by methodical approaches and continuous improvements in the clinical translation of cancer nanomedicine.

Current Challenges in Cancer Nanomedicine

The outcome of treatment is greatly impacted by a number of interrelated obstacles that must be overcome throughout the shift from laboratory development to clinical use.

Manufacturing Complexities

Scalability difficulties and strict chemistry manufacturing and controls supplies are the chief reasons for obstacles related to manufacturing.⁴⁹ Large-scale manufacturing offerings face repeatability issues between batches, especially for complex structures that need several manufacturing procedures.⁵⁰ Physical integrity and therapeutic efficiency are both wedged by product stability during the course of its lifecycle.⁷

Biological and Physiological Barriers

In clinical settings, there are major biological barriers to therapeutic efficacy. Suboptimal tumor penetration is caused by heterogeneous distribution within tumors and increased interstitial pressure.⁴⁷ The effectiveness of the EPR effect varies depending on the type of cancer; studies show that drug delivery is less than twice as high in these organs as in normal ones.⁷

Long-Term Biocompatibility of Advanced Nanocarriers

Thorough review protocols on immunogenicity, bioaccumulation, and chronic toxicity should be conducted to ensure that future safety studies can ascertain the long-term safety of advanced nanocarriers. The efficiency of extending circulation time is ascertained by PEGylated nanoparticles, but these nanoparticles have disadvantages like ABC phenomena.^7,38 Biodegradable coatings and extended biodistribution research are crucial to address oxidative stress and bioaccumulation in organs such as the liver and spleen, which are caused by metallic nanoparticles, including gold and iron oxide.^6,51 Despite being programmable, DNA nanostructures entail chemical alterations to improve stability and reduce immunogenicity.^52,53 Preclinical testing approaches, including prolonged in vitro cytotoxicity assays, in vivo biodistribution investigations, and advanced organ-on-a-chip models, are essential for evaluating long-term safety and efficacy. Tang et al. in 2021 and Meng et al. in 2024 demonstrated that researchers can alleviate potential adverse effects and improve the clinical use of nanomedicine by employing these strategies.^38,51

Technical and Economic Restraints

Precise regulation of drug release kinetics in vivo is a significant technical challenge.⁷ The average tumor accumulation of only 0.7% nanoparticles indicates a markedly low targeting efficacy.⁴⁷ Development costs frequently surpass $2.5 billion due to complex synthesizers, specialized supply requirements, and extensive characterization analysis.⁴⁸

Scale-up Deliberations

The transition from laboratory to commercial production introduces additional complexities, including:⁵⁴

• Implementation of GMP-compliant manufacturing methods
• Specialized facility requirements for nanomaterial handling
• Maintenance of consistent quality throughout scale-up.

Because of the need for small-batch production, specific customization, and complex characterization procedures, personalized nanomedicines put additional financial strain on the economy.46 Systematized approaches are vital to addressing these combined issues while preserving treatment success and financial sustainability if cancer nanomedicine is to continue effectively.

Future Perspectives

Incorporating AI and nanotechnology has the perspective of renovating cancer treatment by providing those new ways to adapt treatments.

Advanced Nanocarrier Systems

New designs for nanocarriers are redefining the possibilities of targeted medicine delivery. DNA nanostructures and quantum dots are promising platforms for cancers of the future.⁵² These new paradigms reduce the adverse effects on surrounding tissue while enhancing the delivery of water-insoluble drugs through programmable construction and precise control over the geometric scale and morphology of the drug complex. It has been largely documented that DNA nanostructures, when conjugated with functional entities such as proteins, peptides, and aptamers that are functional, are less sensitive to dipeptidase and have a longer circulation time in vivo (Figure 5).

Smart Nanoparticles and Stimuli-Responsive Systems

Cancers are being targeted with smart nanoparticles that can respond to the microenvironment, a new avenue in cancer nanomedicine.²⁹ Such intelligent systems achieve spatial and temporal control over the site and time of drug delivery through a variety of stimuli, including pH, temperature, enzymes, magnetic fields, and other factors. For instance, ThermoDox and other thermoresponsive liposomes offer stimulated drug release at certain temperature ranges, which have been designed for the treatment of cancerous sites.¹²

AI-Enhanced Design and Optimization

Introducing AI informs a revolution in nanoparticle design and effectiveness projection. Targeting efficiency, physicochemical characteristics, and drug interactions with the nanoparticle can all be improved by machine learning flood of big data.⁴⁴ Aided by AI analysis, the development pipeline is fast, as many disease-specific nanoparticle types are synthesized in a fraction of the time. Remarkably, some models have predicted up to 92% delivery efficiency for predicting models.⁷

Personalized Nanomedicine

Anyone may now obtain personalized cancer therapies thanks to the merging of AI and nanomedicine research. When applied to patient data, such as genetic information or tumor features, machine learning algorithms can assist in the creation of nanocarriers that are distinct to each individual.⁵⁵ Overall, this strategy has a good chance of increasing treatment efficacy while decreasing adverse effects and enhancing medication effectiveness.

Multimodal Theranostic Platforms

The notion of advanced nanomedicine that integrates all traditional functions, including diagnosis, imaging, and therapy, into a single entity, is plausible. Nanoparticles engineered with theranostic properties will provide real-time modifications of pharmaceutical protocols and assessments of treatment efficacy.⁵³ These pathways will provide the early detection of cancer biomarkers and the real-time evaluation of therapy efficacy by imaging agents and sensors integrated within nanocarriers.

Concrete Examples and Case Studies in Future Directions

A multitude of case studies illustrates the effective implementation of proposed solutions in both preclinical and clinical environments, hence confirming their practical efficacy. Microfluidic platforms have been employed to tackle manufacturing scale challenges by generating homogeneous, uniformly high-quality PLGA-based nanoparticles.⁵⁴ Modular manufacturing techniques that combine synthesis purification and quality control have reduced expenses and improved rigidity.⁵⁶ AI-driven predictive models have expedited regulatory approval processes by simplifying nanoparticle characterization and simulating drug release properties.⁵⁷ Despite the promising imaging and therapeutic applications of quantum dots in cancer models, new technologies like DNA nanostructures show that tumor-bearing animals have longer circulation durations and less enzymatic breakdown.⁵⁸ These cases show how cutting-edge methods can improve clinical translation while addressing major obstacles to nanomedicine’s progress.

Challenges and Future Directions

Before these technologies may be used in clinical situations, several problems still need to be fixed, despite the hopeful expansions. Manufacturing scalability, regulatory hurdles, cost reduction, emerging technologies, and multimodal theranostic platforms are important issues that necessitate care.⁴⁸ Improved nanocarriers’ long-term safety and biocompatibility entail extensive study and clinical testing. Upcoming research endeavors should focus on:

Manufacturing Scalability

The production of nanocarriers for cancer nanomedicine is challenging to scale up while maintaining consistency and quality due to the complexity of formulations like liposomes and polymeric nanoparticles. This aids in waste minimization and enhances overall performance, which are major problems in scaling up.^59,60 Furthermore, it has been indicated that modular production systems reduce the complexity of manufacturing liposomal formulations such as Doxil, hence cutting costs by up to 30% in comparison to normal batch production.^56,59 Other authors suggested that microfluidics could enhance the percentage of PLGA nanoparticles with the aim of reducing the processing time by 20%.⁵⁴ Also, modular production systems have been manifested to reduce the total time of liposomal Doxil experiments by nearly 40%.⁵⁶ As we can see, the aforementioned advancements indicate the pursuit of advanced manufacturing systems for the rapid clinical translation of cancer nanomedicine while being cost- and scale-efficient.

Regulatory Hurdles

Regulatory frameworks for nanomedicine remain complex due to the unique physicochemical properties of nanoparticles and the lack of conventional characterization techniques, which often delay clinical translation. To get around these issues, it has been proposed that standardized methods for describing nanoparticles—such as size distribution, surface charge effect, drug-loading efficiency, and release kinetics—be created. This new guide will speed up the regulatory approval process and ensure consistency across investigations.⁴⁶ Additionally, AI-driven predictive models may be integrated by modeling nanoparticle activity under various conditions, generating trustworthy data to support regulatory filings. For example, AI models have been used to predict medication release profiles and interactions of nanoparticles with biological systems to expedite the approval process.^57,58

Cost and Proposed Solutions for Medical Nanomedicine in the Context of Emerging Healthcare Systems

Because of the complicated synthesis procedures and long clinical trials involved in developing nanomedicine, each formulation might cost over $2.5 billion. One solution that has been suggested is an AI-enhanced quality control system to maximize production by detecting flaws in real time, cutting waste, and guaranteeing constant quality throughout batches. Furthermore, by facilitating the manufacture of nanoparticles on a broad scale with little human involvement, automated manufacturing processes have shown the potential to reduce labor costs and increase efficiency. Microfluidics, for example, are perfect for scalable production because they reduce batch-to-batch variability and provide fine control over nanoparticle size and characteristics.^56,59 These advances offer inexpensive ways to get past the financial hindrances that come with developing nanomedicine.

Emerging Technologies in Cancer Treatment

Thanks to their improved targeting capabilities and programmable designs, cutting-edge technologies like DNA nanostructures and quantum dots are completely changing the way that cancer is treated. By improving circulation times and reducing enzymatic degradation, DNA nanostructures with programmable forms, biocompatibility, and functionalization provide for precise control over drug delivery.61 Real-time monitoring of therapy effectiveness and improved treatment accuracy are made possible by the use of quantum dots in improved medication delivery.^58,62

Multimodal Theranostic Platforms

The forthcoming individualized cancer treatment lies in the combination of imaging, treatments, and diagnostics on a single platform. Real-time treatment efficacy monitoring is made possible by theranostic nanoparticles, which combine therapeutic and imaging properties. For example, DNA nanostructures and quantum dots are being created for both therapeutic and dual imaging applications, providing improved treatment outcomes and precise tumor targeting.^58,63 Furthermore, ThermoDox and other stimuli-responsive systems release medications in reaction to environmental cues like temperature or pH, guaranteeing accurate administration while reducing systemic toxicity.^12,64 These developments demonstrate how multimodal theranostic platforms have the potential to transform cancer therapy and diagnosis by facilitating individualized and flexible treatment plans.

Ethical Considerations in AI-Driven Medicine

From predictive diagnosis and treatment plans to individualized care, AI is revolutionizing medicine. Given the significant ethical issues raised by the application of AI in healthcare, the technology must be implemented fairly and responsibly. These include, among other things, responsibility, model interpretability, and data privacy.⁶⁵

Data Privacy

The dependency on AI systems with vast amounts of sensitive patient data, such as genetic data, imaging tests, and electronic health records, raises concerns over confidentiality violation and illegal access.⁶⁶ Tang et al.³⁸ found that these dangers may be reduced by using secure storage protocols, multifactor authentication, role-based access restrictions, and advanced encryption techniques. These measures preserve data both during transmission and storage. To this end, federated learning approaches have been developed to train AI systems on distributed datasets without sending sensitive data, hence reducing privacy concerns while keeping performance stable.⁷ Moreover, for ensuring compliance and protecting patient rights, privacy regulations such as HIPAA (USA) and GDPR (EU) must be followed. Transparency regarding the use of personal information in AI applications forms the very foundation of trust and patient autonomy.⁶⁷

Model Explainability

Most algorithms in AI applications are “black boxes” that generate results without giving any explanations behind the decisions reached.⁶⁸ Besides inhibiting the process of regulatory clearance, this lack of transparency erodes trust among patients and practitioners. With the incorporation of XAI frameworks that provide interpretable results using simple decision trees or visualizations, clinicians will have a better understanding of how specific features contribute to a prediction.⁶⁹ The collaboration of medical experts, ethicists, and AI developers has resolved the challenges in a successful manner. For compliance with GDPR using different datasets, Google Health collaborated with radiologists on the development of an AI model for breast cancer detection that reduced false positives by 5.7% and false negatives by 9.4%.⁷⁰ To address sections of HIPAA, a collaboration by Mayo Clinic and NVIDIA resorted to federated learning while maintaining patient privacy for medical imaging analysis.⁷¹ Continuous auditing of the AI models, which becomes necessary for interpretability and to remove bias, becomes difficult as the datasets evolve.⁷²

Accountability

It is challenging to establish accountability in AI-driven healthcare because so many parties are engaged, including developers, clinicians, and institutions. According to Morley et al., errors in AI recommendations may cause substantial patient harm.⁷³ Legal frameworks need to specify responsibilities to address this issue: developers should stringently test algorithms before their use; physicians must have the final say in decisions; and organizations should ensure that staff working with AI systems are adequately trained. Multidisciplinary experts on ethical oversight committees can review the implications of AI initiatives before deployment.⁷³ In addition, liability insurance for developers and organizations using AI systems may cover anticipated damages due to failure or malfunction.⁷⁴ Anomaly detection in AI recommendations requires real-time monitoring systems that will aid in taking corrective measures with speed.⁷⁵

Ethical Challenges and Lessons from AI in Healthcare

The use of AI in health training has brought up several ethical issues despite the great potential for transformation. For example, a widely used algorithm employed by a major US healthcare system systematically overestimated how sick Black patients were compared to White patients with similar conditions because of biased training data, as reported by Obermeyer et al. in 2019.⁷⁶ Such a case points to the need for interdisciplinary oversight from ethicists and medical experts in creating algorithms. A 2020 partnership between a digital enterprise and a healthcare organization was criticized for poor anonymization of patient data. The partnership brought into focus the need for transparency in the light of legislation on privacy.⁷⁷ A different incident where an AI system used “irrelevant parts of the image,” such as ruler marks, to diagnose skin lesions in clinical trials provided incorrect diagnoses and, hence, incorrect treatment recommendations in the process.⁶⁹ These examples further outline that, to do no harm, explainable AI frameworks are a necessity, together with continuous audits by interdisciplinary teams and strong ethical oversight (Figure 6).

Conclusion

Medication delivery methods based on nanoparticles have demonstrated the ability to overcome tumor disease-related medication resistance. The production of stimulus-responsive multifunctional nanocarriers, which may react to biological signals and other environmental stimuli, is what distinguishes this development and enables highly accurate spatiotemporal management of medicine delivery. Basic research into the discovery and clinical translation of nanomedicine has brought significant therapeutic benefits. Economically successful, clinically approved formulations, such as polymeric nanocarriers and liposomal doxorubicin, address some of the major shortcomings of classic chemotherapy. In comparison with conventional drug delivery, these nanoformulations generally show improved accumulation in tumors, reduced toxicity, and improved pharmacokinetics. Despite these successes, several key issues remain unaddressed:

• A very important problem that remains is the scalability of manufacturing at large-scale production while keeping quality consistent, especially for complex nanoformulations.
• The median accumulation of the administered nanoparticles in tumors is approximately 0.7%, which signals continuous failure in targeting efficiency. This, therefore, calls for more targeted surgery and also increased knowledge of tumor biology.
• With innovating nanomedicine technologies surrounded by complex regulatory frameworks that limit their clinical translational possibilities, there is a need for standardized nanoparticle characterization and quality assurance processes.
• Tailored techniques nevertheless raise questions about cost-effectiveness, particularly for bespoke nanomedicines that need complex manufacturing.

The combination of AI, novel delivery methods, and customized treatments can help overcome these obstacles. Some models can now administer essential medications with a 92% probability thanks to AI-optimized design. Advances in the areas of microfluidics and other manufacturing processes ease scalability and reproducibility concerns. Such techniques, when put together with AI-mediated tumor feature analysis, open new avenues toward very personalized cancer treatments. For instance, nanotechnology, in amalgamation with material science, biotechnology, and AI, could bring in new forms of cancer treatment in the future. Efficiency in overcoming the challenges of modernity and using technology for better and more affordable healthcare solutions is of pivotal essence. Patient-centered methodology, real-time monitoring, and versatile theranostic system development are crucial in realizing all the potentials of nanomedicine during its current development.

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Fahmy AM. Advancing Nanotechnology in Targeted Cancer Therapy: From Passive Targeting to Smart Delivery Systems. Premier Journal of Science 2025;6:100052

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