Dataset for Hollow-fiber membrane technology: Characterization and proposed use as a potential mimic of skin vascularization towards the development of a novel skin absorption in vitro model
Historically, animal testing has been used to support risk assessment for a variety of toxicological endpoints related to cosmetic ingredients, including the local lymph node assay (LLNA) to assess the sensitization potential and potency of a chemical. However, in recent years, there has been a continuous drive to reduce the level of animal testing undertaken to support risk assessments for new cosmetic products, and a move towards a mechanistic understanding of human exposure. Consequently, the development of mechanistic/biologically relevant in vitro, in chemico or in silico models for predicting the sensitising potential and/or potency of new chemicals is necessary to generate data leading to increased confidence in predictions of in vivo scenarios. The chemical and biological events driving the induction of human skin sensitisation are now well understood and companies such as Unilever use this information in non-animal models to test the safety of new compounds. Discs of ex vivo skin (from cosmetic surgery procedures) are mounted in diffusion cells and the permeation of a test item through the skin is monitored over time. While this has proved to be an adequate model, it does not truly represent living skin. At present, little is known regarding chemical clearance via dermal capillaries, and this is a gap in our mechanistic understanding of the bioavailability of a topically applied chemical in the elicitation of skin sensitisation. The proposed capillary bed bioreactor (CBB) better replicates the in vivo environment of the skin and its blood supply by providing a bed of pseudovascularisation in the form of hollow fibre membranes. Therefore it should more accurately predict permeation of chemicals through the skin, and provide data that more closely resembles that of the in vivo scenario. The new bioreactor will be more physiologically accurate than the current model and can therefore potentially refine inputs to our mechanistic models for skin sensitisation, to give us more accurate predictions of adverse outcomes. This in turn will give greater confidence in our ability to risk assess new ingredients in the future without the requirement for animal testing.
This dataset contains data collected using capillary bed bioreactor (CBB), a new method for pseudovascularisation of skin models. The data was collected by sampling the permeate that exited the fibres, and the amount of caffeine in the samples was measured using HPLC for the purpose of assessing permeability. By observing and analyzing the data we can conclude that the new bioreactor will be more physiologically accurate than the current model and can therefore potentially refine inputs to our mechanistic models for skin sensitisation, to give us more accurate predictions of adverse outcomes. The data is organised in an Excel spreadsheet with each tab relating to a specific figure in the paper.
Cite this dataset as:
Ellis, M.,
2019.
Dataset for Hollow-fiber membrane technology: Characterization and proposed use as a potential mimic of skin vascularization towards the development of a novel skin absorption in vitro model.
Bath: University of Bath Research Data Archive.
Available from: https://doi.org/10.15125/BATH-00579.
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Raw data_Biochem … 2019.xlsx
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Creative Commons: Attribution 4.0
Creators
Marianne Ellis
University of Bath
Contributors
University of Bath
Rights Holder
Coverage
Collection date(s):
From 1 October 2014 to 30 June 2016
Documentation
Data collection method:
Samples were taken every ten minutes for two hours, and in a second experiment every hour for 24 hours, and the concentration of caffeine was analyzed via HPLC (Agilent Technologies, 1260 Infinity Series). The concentration of caffeine was calculated directly comparing the area of the peaks measured via HPLC with the calibration curve obtained with caffeine standards of known concentration. The integration of the peaks was performed manually. A C18 column was used (Poroshell 120 EC-C18, 2.7 mm, 4.6 x 50 mm), and isocratic elution was chosen. The mobile phase was 75:25 acetonitrile: deionized water, and a UV-visible detector was employed (DAD Detector Signal (mAU) = 273/4 nm, Reference 360/80 nm). A calibration using caffeine solutions of known concentration was performed. The retention time of caffeine in the column used for this study was approximately 0.54 minutes.
Data processing and preparation activities:
Three independent experiments were conducted and and mean calculated in excel. Data presented with error bars representing the standard deviation
Technical details and requirements:
The equipment used for the collection of these data was a HPLC Agilent Technologies 1260 Infinity, with DAD Detector Signal (mAU) = 273 / 4 nm, Reference 360 / 80 nm. 1 ml of total sample was measured in HPLC. The residence time for caffeine was 0.54 min, and the eluent was 75:25 MeCN:DI water. The injections were 10 microlitres at a flow rate of 1.000ml/min.
Funders
Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266
Capillary Bed Bioreactor: Improved Estimation of Dermal Bioavailability
EP/M506850/1
Publication details
Publication date: 30 January 2019
by: University of Bath
Version: 1
DOI: https://doi.org/10.15125/BATH-00579
URL for this record: https://researchdata.bath.ac.uk/id/eprint/579
Related papers and books
Perez Esteban, P., Pickles, J., Scott, A. D., and Ellis, M. J., 2019. Hollow-fiber membrane technology: Characterization and proposed use as a potential mimic of skin vascularization towards the development of a novel skin absorption in vitro model. Biochemical Engineering Journal, 145, 90-97. Available from: https://doi.org/10.1016/j.bej.2019.01.025.
Contact information
Please contact the Research Data Service in the first instance for all matters concerning this item.
Contact person: Marianne Ellis
Faculty of Engineering & Design
Chemical Engineering
Research Centres & Institutes
Bioprocessing Research Unit (BRU)