A robust preclinical disease model is a primary requirement
to
understand the underlying mechanisms, signaling pathways, and drug
screening for human diseases. Although various preclinical models
are available for several diseases, clinical models for Alzheimer’s
disease (AD) remain underdeveloped and inaccurate. The pathophysiology
of AD mainly includes the presence of amyloid plaques and neurofibrillary
tangles (NFT). Furthermore, neuroinflammation and free radical generation
also contribute to AD. Currently, there is a wide gap in scientific
approaches to preventing AD progression. Most of the available drugs
are limited to symptomatic relief and improve deteriorating cognitive
functions. To mimic the pathogenesis of human AD, animal models like
3XTg-AD and 5XFAD are the primarily used mice models in AD therapeutics.
Animal models for AD include intracerebroventricular-streptozotocin
(ICV-STZ), amyloid beta-induced, colchicine-induced, etc., focusing
on parameters such as cognitive decline and dementia. Unfortunately,
the translational rate of the potential drug candidates in clinical
trials is poor due to limitations in imitating human AD pathology
in animal models. Therefore, the available preclinical models possess
a gap in AD modeling. This paper presents an outline that critically
assesses the applicability and limitations of the current approaches
in disease modeling for AD. Also, we attempted to provide key suggestions
for the best-fit model to evaluate potential therapies, which might
improve therapy translation from preclinical studies to patients with
AD.