Preclinical in vitro evaluation of implantable materials: conventional approaches, new models and future directions

Abstract

Nowadays, implants and prostheses are widely used to repair damaged tissues or to treat different diseases, but their use is associated with the risk of infection, inflammation and finally rejection. To address these issues, new antimicrobial and anti-inflammatory materials are being developed. Aforementioned materials require their thorough preclinical testing before clinical applications can be envisaged. Although many researchers are currently working on new in vitro tissues for drug screening and tissue replacement, in vitro models for evaluation of new biomaterials are just emerging and are extremely rare. In this context, there is an increased need for advanced in vitro models, which would best recapitulate the in vivo environment, limiting animal experimentation and adapted to the multitude of these materials. Here, we overview currently available preclinical methods and models for biological in vitro evaluation of new biomaterials. We describe several biological tests used in biocompatibility assessment, which is a primordial step in new material's development, and discuss existing challenges in this field. In the second part, the emphasis is made on the development of new 3D models and approaches for preclinical evaluation of biomaterials. The third part focuses on the main parameters to consider to achieve the optimal conditions for evaluating biocompatibility; we also overview differences in regulations across different geographical regions and regulatory systems. Finally, we discuss future directions for the development of innovative biomaterial-related assays: in silico models, dynamic testing models, complex multicellular and multiple organ systems, as well as patient-specific personalized testing approaches.

Keywords: 3D models; biocompatibility; biomaterials; implants; organoids.

FIGURE 1

Evolution of biocompatibility testing: from classic monolayer culture to personalized testing approaches.

FIGURE 2

Foreign body reaction to biomaterial implantation and respective evaluation. Quickly after the implantation of the biomaterial, blood plasma proteins are adsorbed on the surface of the material. Their presence on the implant allows recruitment of leukocytes, including neutrophils and followed by monocytes. Differentiation of monocytes into macrophages and then their fusion into foreign body giant cells (FBGC) finally lead to recruitment of fibroblasts and to formation of a fibrous capsule around the implant, leading to chronic inflammation. Each of the foreign body reaction steps can be assessed through more or less specific assays. Enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), microscopy or flow cytometry are common methods to study biocompatibility. In addition to these, there are more specific tests such as Griess assay for nitric oxide secretion, Cytoselect™ 96-well phagocytosis assay to study the activation of macrophages, or Epithelial to Mesenchymal Transition (EMT) and Fibroblast to Myofibroblast Transition (FMT) to study the fibrotic tissue formation.

FIGURE 3

Evaluation of materials cytotoxicity (A) and cell adhesion (B) in 2D and 3D environment. In 2D, only one cell layer is in contact with the material, which may lead to an overestimation of its toxicity, as compared with 3D model. In a similar way, material interaction with the surrounding tissues is more complex in 3D, with the cells surrounding the implant from all the sides.

FIGURE 4

Engineered oral mucosal models with inserted implant materials (A) and histological views of oral mucosal models (B). Adapted from (Barker et al., 2020). Copyright 2020, the Authors. Published by MDPI, Basel, Switzerland.

FIGURE 5

Schematics showing the experimental steps for construction of in vitro 3D skin model using gelatin methacrylate (GelMA) scaffold Adapted from (Kwak et al., 2018). Copyright 2018, Elsevier.

FIGURE 6

Parameters to consider for medical device testing biocompatibility. Main parameters have been classified into 4 categories related to the sample selection, testing methods, their applications and standardization.