Recent Developments in Layer-by-Layer Assembly for Drug Delivery and Tissue Engineering Applications.
João BorgesJinfeng ZengXi Qiu LiuHao ChangClaire MongeCharlotte GarotKe-Feng RenPaul MachillotNihal Engin VranaPhilippe LavalleTakami AkagiMichiya MatsusakiJian JiMitsuru AkashiJoao F ManoVarvara GribovaCatherine PicartPublished in: Advanced healthcare materials (2024)
Surfaces with biological functionalities are of great interest for biomaterials, tissue engineering, biophysics, and for controlling biological processes. The layer-by-layer (LbL) assembly is a highly versatile methodology introduced 30 years ago, which consists of assembling complementary polyelectrolytes or biomolecules in a stepwise manner to form thin self-assembled films. In view of its simplicity, compatibility with biological molecules, and adaptability to any kind of supporting material carrier, this technology has undergone major developments over the past decades. Specific applications have emerged in different biomedical fields owing to the possibility to load or immobilize biomolecules with preserved bioactivity, to use an extremely broad range of biomolecules and supporting carriers, and to modify the film's mechanical properties via crosslinking. In this review, the focus is on the recent developments regarding LbL films formed as 2D or 3D objects for applications in drug delivery and tissue engineering. Possible applications in the fields of vaccinology, 3D biomimetic tissue models, as well as bone and cardiovascular tissue engineering are highlighted. In addition, the most recent technological developments in the field of film construction, such as high-content liquid handling or machine learning, which are expected to open new perspectives in the future developments of LbL, are presented.
Keyphrases
- tissue engineering
- drug delivery
- room temperature
- machine learning
- cancer therapy
- minimally invasive
- bone mineral density
- reduced graphene oxide
- drug release
- escherichia coli
- soft tissue
- gold nanoparticles
- big data
- body composition
- biofilm formation
- staphylococcus aureus
- postmenopausal women
- deep learning
- bone regeneration