Virtual twinning for intelligent, personalized transdermal drug delivery
Type. FreeNovation project
Funding. This PhD project is funded by the Novartis Research Foundation under the FreeNovation program and Empa (internal).
Duration. 4 years (2018-2022).
Collaborations. This project is a collaboration between different Empa labs of the Department of Materials Meet Life.
Contact. Thijs Defraeye (principal investigator).
Staff. Flora Bahrami (PhD student), Lu Ding (Master student EPFL, 2019)
Transdermal drug delivery (TDD) is a non-invasive technology that is currently used to (self-) administer drugs in lower doses. A main hurdle with TDD is controlling the percutaneous drug absorption since the delivery pathway – the human skin – is very patient specific. The absorption kinetics depend on the patient’s skin composition, metabolism and lifestyle. Instead of “one-size-fits-all”, we aim at designing future TDD devices that deal with specific patients (genotypes and phenotypes). We propose an innovative way to make TDD device control more intelligent by creating a virtual twin of the TDD patch and patient’s skin. This virtual twin predicts the physical processes occurring during drug release and absorption. This information is used to steer the TDD process and to tailor it to the patient.
Defraeye T., Bahrami F., Ding L., Malini R.I., Terrier A., Rossi R.M. (2020), Predicting transdermal fentanyl delivery using mechanistic simulations for tailored therapy, Frontiers in Pharmacology (11) 585393. DOI
Defraeye T., Bahrami F., Rossi R.M. (2021), Inverse mechanistic modeling of transdermal drug delivery for fast identification of optimal model parameters, Frontiers in Pharmacology 12, 1-15, 641111 DOI
Bahrami, F., Rossi, R.M. and Defraeye, T., (2022). Predicting transdermal fentanyl delivery using physics-based simulations for tailored therapy based on the age. Drug Delivery, 29(1), pp.950-969. DOI