Enhanced skin retention and permeation of a novel peptide via structural modification, chemical enhancement, and microneedles

Chen, Jungen; Bian, Junxing; Hantash, Basil M.; Albakr, Lamyaa; Hibbs, David E.; Xiang, Xiaoqiang; Xie, Peng; Wu, Chunyong; Kang, Lifeng

doi:10.1016/j.ijpharm.2021.120868

Cited by 14 publications

(8 citation statements)

References 34 publications

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“…For the plastic MN, each MN is in the shape of a regular square pyramid. So, the surface area is calculated using Equation (10), where a is the length of the bottom square edge, and h is the height of a single MN from the apex of the pyramid to the base plane.…”

Section: Machine Learningmentioning

confidence: 99%

“…These MNs can enhance drug permeation into the skin and/or main circulation, by creating multiple micron‐sized passages through skin, a formidable biological barrier preventing external substances from entering human body 2–5 . Owing to the simple concept of MN and technological feasibility of MN fabrication, MN has been extensively studied as a device to deliver into human a variety of therapeutic agents, for example, small‐molecule compounds, 6,7 peptides, 8–10 mRNA, 11 proteins, 12 and extracellular vesicles 13 …”

Section: Introductionmentioning

confidence: 99%

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Prediction of drug permeation through microneedled skin by machine learning

Yuan

Han

Yap³

et al. 2023

Bioengineering & Transla Med

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Stratum corneum is the outermost layer of the skin preventing external substances from entering human body. Microneedles (MNs) are sharp protrusions of a few hundred microns in length, which can penetrate the stratum corneum to facilitate drug permeation through skin. To determine the amount of drug delivered through skin, in vitro drug permeation testing is commonly used, but the testing is costly and time‐consuming. To address this issue, machine learning methods were employed to predict drug permeation through the skin, circumventing the need of conducting skin permeation experiments. By comparing the experimental data and simulated results, it was found extreme gradient boosting (XGBoost) was the best among the four simulation methods. It was also found that drug loading, permeation time, and MN surface area were critical parameters in the models. In conclusion, machine learning is useful to predict drug permeation profiles for MN‐facilitated transdermal drug delivery.

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Section: Machine Learningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of drug permeation through microneedled skin by machine learning

Yuan

Han

Yap³

et al. 2023

Bioengineering & Transla Med

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“…Another chemical strategy, known as prodrug modification, entails the chemical alteration of the parent drug molecule to enhance its lipophilic characteristics, thereby facilitating greater penetration through the lipid‐rich outermost layer of the skin called the SC. [ 9 ] Examples include modification to corticosteroids like triamcinolone and betamethasone, which resulted in marked improvements in their topical efficacy. Likewise, chemical enhancers like fatty acids, alcohols, [ 10 ] and terpenes, [ 11 ] can be included in a formulation to lower the skin's barrier function.…”

Section: Introductionmentioning

confidence: 99%

Progress in Lipid and Inorganic Nanocarriers for Enhanced Skin Drug Delivery

Albakr,

Du,

Zhang

et al. 2024

Advanced NanoBiomed Research

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New advancements in nanocarrier technologies are revolutionizing the delivery of drugs through the skin, allowing for precise treatment with better absorption, stability, and bioavailability. This review investigates lipid and inorganic nanocarriers like liposomes, ethosomes, and inorganic nanoparticles and assesses their potential for delivering drugs through the skin. It emphasizes the mechanisms that enable controlled release and deeper skin penetration, which are crucial for ensuring effectiveness in clinical applications. The review synthesizes existing research, acknowledging that only few nanocarriers are successfully deployed in clinical settings. By offering a comprehensive overview, it sheds light on the progress and future obstacles to using nanocarriers for drug delivery through the skin.

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“…Those two efforts are specifically important in the early stages of topical drug and cosmetic product development since an AI can be economically screened to optimize AI selection, concentration, and formula before significant investigation for clinical and marketing progresses [9]. The transdermal delivery systems have been intensively studied to overcome the skin barrier for more effective application of pharmaceutical and cosmetic products [10,11]. Although the cosmeceutical industry has made substantial progress in the development and incorporation of new and effective AI in their products, the barrier function of the skin remains a limiting factor in the penetration and absorption of these actives.…”

Section: Introductionmentioning

confidence: 99%

Mini Review: Mass Spectrometry Technology for Molecule Distribution inside Skin

Hao¹

2022

Adv Res Dermatol Cosmetics

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The functional ingredients for skin-related products have been highly recognized accompanied by the consumers’ curiosity and instrumental improvement. The targeted location of a functional active ingredient in the skin organelle could be very critical information for its product development, safety evaluation, and benefit claims. Due to those factors, mass spectrometry technology exhibited rapid growth in those research areas because it can accurately and sensitively determine the ingredient molecular weights and locations. In this min review, a summarized figure was created for mass spectrometry technology applications in skin research in the last two decades or so. Compared to other related technologies, the uniqueness and advantage of chromatographic-mass spectrometry and mass spectrometry imaging were also emphasized. Several typical examples from separation, isotopic labeling, and combination with Franz cell were discussed.

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Enhanced skin retention and permeation of a novel peptide via structural modification, chemical enhancement, and microneedles

Cited by 14 publications

References 34 publications

Prediction of drug permeation through microneedled skin by machine learning

Prediction of drug permeation through microneedled skin by machine learning

Progress in Lipid and Inorganic Nanocarriers for Enhanced Skin Drug Delivery

Mini Review: Mass Spectrometry Technology for Molecule Distribution inside Skin

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