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Pharmaceutics
Special Issues
Multicomponent Nanomedicines for Photodynamic Diagnosis and Photodynamic Therapy
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Multicomponent Nanomedicines for Photodynamic Diagnosis and Photodynamic Therapy

A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Nanomedicine and Nanotechnology".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 1792

Special Issue Editors

Prof. Dr. Heidi Abrahamse

E-Mail Website
Guest Editor
Laser Research Centre, Faculty of Health Sciences, University of Johannesburg, P.O. Box 17011, Johannesburg 2028, South Africa
Interests: PDT; laser; cancer therapy
Special Issues, Collections and Topics in MDPI journals
Dr. Hanieh Montaseri

E-Mail Website
Guest Editor
Department of Surgery and Cancer, Imperial College London, London W12 0NN, UK
Interests: nanomedicine; drug delivery; cancer treatment; photodynamic therapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Even though different drug discovery studies are composed of a single chemical entity, most analysts believe that “the one drug to fit all” approach will be unsustainable in the future as many diseases are multifactorial in nature and individual molecular targets cannot usually combat multifactorial diseases wherein multiple tissues or cell types are affected. Therefore, multi-drug or multi-target therapies are considered to be advantageous for multifactorial diseases. Our focus of this Special Issue is on multicomponent targeting drug delivery for photodynamic diagnosis (PDD) and photodynamic therapy (PDT) of oncological diseases. In addition, nanotechnology integrated with PDD and PDT strategies is a promising approach for the diagnosis and treatment of accurate lesions. In this regard, this Special Issue aims to publish high-quality research papers and reviews focusing on the design of smart nanomedicines in the PDD and PDT of various oncological tumors. Research topics include but are not limited to the following:

  • Photodynamic therapy;
  • Photodynamic diagnosis;
  • Oncological diseases;
  • Multicomponent nanomedicines;
  • Multi-target therapies;
  • Drug delivery;
  • Targeting antibodies/aptamers/peptides.

Prof. Dr. Heidi Abrahamse
Dr. Hanieh Montaseri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceutics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

17 pages, 6445 KiB  
Article
Self-Assembled Nanocomposite DOX/TPOR4@CB[7]4 for Enhanced Synergistic Photodynamic Therapy and Chemotherapy in Neuroblastoma
by Zhouxia Lu, Xu Chen, Conghui Wang, Xuelian Luo, Xiaohan Wu, Xing Zhao and Song Xiao
Pharmaceutics 2024, 16(6), 822; https://doi.org/10.3390/pharmaceutics16060822 - 18 Jun 2024
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Abstract
DOX/TPOR4@CB[7]4 was synthesized via self-assembly, and its physicochemical properties and ability to generate reactive oxygen species (ROS) were evaluated. The impact of photodynamic therapy on SH-SY5Y cells was assessed using the MTT assay, while flow cytometry analysis was employed to [...] Read more.
DOX/TPOR4@CB[7]4 was synthesized via self-assembly, and its physicochemical properties and ability to generate reactive oxygen species (ROS) were evaluated. The impact of photodynamic therapy on SH-SY5Y cells was assessed using the MTT assay, while flow cytometry analysis was employed to detect cell apoptosis. Confocal laser scanning microscopy was utilized to observe the intracellular distribution of DOX/TPOR4@CB[7]4 in SH-SY5Y cells. Additionally, fluorescence imaging of DOX/TPOR4@CB[7]4 in nude mice bearing SH-SY5Y tumors and examination of the combined effects of photodynamic and chemical therapies were conducted. The incorporation of CB[7] significantly enhanced the optical properties of DOX/TPOR4@CB[7]4, resulting in increased ROS production and pronounced toxicity towards SH-SY5Y cells. Moreover, both the apoptotic and mortality rates exhibited significant elevation. In vivo experiments demonstrated that tumor growth inhibition was most prominent in the DOX/TPOR4@CB[7]4 group. π–π interactions facilitated the binding between DOX and photosensitizer TPOR, with TPOR’s naphthalene hydrophilic groups encapsulated within CB[7]’s cavity through host–guest interactions with CB[7]. Therefore, CB[7] can serve as a nanocarrier to enhance the combined application of chemical therapy and photodynamic therapy, thereby significantly improving treatment efficacy against neuroblastoma tumors. Full article
(This article belongs to the Special Issue Multicomponent Nanomedicines for Photodynamic Diagnosis and Photodynamic Therapy)
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14 pages, 4408 KiB  
Article
Deep Learning Insights into the Dynamic Effects of Photodynamic Therapy on Cancer Cells
by Md. Atiqur Rahman, Feihong Yan, Ruiyuan Li, Yu Wang, Lu Huang, Rongcheng Han and Yuqiang Jiang
Pharmaceutics 2024, 16(5), 673; https://doi.org/10.3390/pharmaceutics16050673 - 16 May 2024
Viewed by 888
Abstract
Photodynamic therapy (PDT) shows promise in tumor treatment, particularly when combined with nanotechnology. This study examines the impact of deep learning, particularly the Cellpose algorithm, on the comprehension of cancer cell responses to PDT. The Cellpose algorithm enables robust morphological analysis of cancer [...] Read more.
Photodynamic therapy (PDT) shows promise in tumor treatment, particularly when combined with nanotechnology. This study examines the impact of deep learning, particularly the Cellpose algorithm, on the comprehension of cancer cell responses to PDT. The Cellpose algorithm enables robust morphological analysis of cancer cells, while logistic growth modelling predicts cellular behavior post-PDT. Rigorous model validation ensures the accuracy of the findings. Cellpose demonstrates significant morphological changes after PDT, affecting cellular proliferation and survival. The reliability of the findings is confirmed by model validation. This deep learning tool enhances our understanding of cancer cell dynamics after PDT. Advanced analytical techniques, such as morphological analysis and growth modeling, provide insights into the effects of PDT on hepatocellular carcinoma (HCC) cells, which could potentially improve cancer treatment efficacy. In summary, the research examines the role of deep learning in optimizing PDT parameters to personalize oncology treatment and improve efficacy. Full article
(This article belongs to the Special Issue Multicomponent Nanomedicines for Photodynamic Diagnosis and Photodynamic Therapy)
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