Gelatin methacryloyl (GelMA) hydrogels
are promising
materials
for tissue engineering applications due to their biocompatibility
and tunable properties. However, the time-consuming process of preparing
GelMA hydrogels with desirable properties for specific biomedical
applications limits their clinical use. Visible-light-induced cross-linking
is a well-known method for the preparation of GelMA hydrogels; however,
a comprehensive investigation on the influence of critical parameters
such as Eosin Y (EY), triethanolamine (TEA), and N-vinyl-2-pyrrolidone (NVP) concentrations on the stiffness and gelation
time has yet to be performed. In this study, we systematically investigated
the effect of these critical parameters on the stiffness and gelation
time of GelMA hydrogels. We developed an artificial neural network
(ANN) model with three input variables, EY, TEA, and NVP concentrations,
and two output variables, Young’s modulus and gelation time,
derived from our experimental design. Through the alteration of individual
chemical concentrations, [EY] between 0.005 and 0.5 mM and [TEA] and
[NVP] between 10 and 1000 mM, we studied the impact of these alterations
on the real-time values of stiffness and gelation time. Furthermore,
we demonstrated the validity of the ANN model in predicting the properties
of GelMA hydrogels. We also studied cell survival to establish nontoxic
concentration ranges for each component, enabling safer use of GelMA
hydrogels in relevant biomedical applications. Our results showed
that the ANN model can accurately predict the properties of GelMA
hydrogels, allowing for the synthesis of hydrogels with desirable
stiffness for various biomedical applications. In conclusion, our
study provides a comprehensive library that characterizes the stiffness
and gelation time and demonstrates the potential of the ANN model
to predict these properties of GelMA hydrogels depending on the critical
parameters. The ANN models developed here can facilitate the optimization
of GelMA hydrogels with the most efficient mechanical properties that
resemble a native extracellular matrix and better address the need
in the in vivo microenvironment. The approach of
this study is to bring research about the synthesis of GelMA hydrogels
to a new level where the synthesis of these hydrogels can be standardized
with minimum cost and effort.