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May 8, 2026Chemical Biology & Drug Design0 citations

Smart Immunoliposome‐Based Targeted Drug Delivery for Cancer: A Comprehensive Systematic Review

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GGGandhali GhaisasVLVaishali Y. Londhe

Key Points

  • This review aims to summarize recent advancements in immunoliposome technology for targeted cancer therapy.
  • Conducted systematic review following PRISMA guidelines
  • Evaluated engineering strategies for antibody-modified liposomes
  • Assessed performance across various cancer cell models
  • Immunoliposomes demonstrated enhanced targeting efficiency compared to conventional methods
  • Stimuli-responsive designs improved site-selective drug delivery
  • Overall, findings indicate significant potential for transforming targeted cancer therapy

Abstract

Cancer remains one of the leading causes of mortality worldwide, and although conventional chemotherapy has demonstrated therapeutic benefits, its clinical utility is often limited by severe systemic adverse effects. Advances in targeted drug delivery, particularly through monoclonal antibody-based therapies, have significantly improved treatment specificity and patient outcomes. Among nanocarrier systems, liposomes have emerged as highly effective platforms capable of encapsulating both hydrophilic and lipophilic drugs, thereby enhancing therapeutic index, improving pharmacokinetics and enabling controlled drug release. To further refine tumour targeting efficiency, antibody-modified liposomes, immunoliposomes, have been developed as the next generation of liposomal therapeutics. Diverse strategies for conjugating monoclonal antibodies to liposomal surfaces have been established, along with the development of intrinsic and extrinsic stimuli-responsive designs capable of site-selective drug delivery. This systematic review, conducted in accordance with PRISMA guidelines, summarises recent advances in immunoliposome engineering and evaluates their performance across various cancer cell models, highlighting their potential to transform targeted cancer therapy.

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Cite This Study

Ghaisas et al. (2026) studied this question.

synapsesocial.com/papers/69fd7f65bfa21ec5bbf07e40https://doi.org/10.1111/cbdd.70295
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