Organ-on-a-Chip: Novel In Vitro Model

for Drug Discovery

6

Geeta Aggarwal, Gaurav Kaithwas, Manjari Singh,

and Ramesh K. Goyal

Abstract

In conventional drug discovery process, the attrition in clinical development as a

consequence of late clinical trial failure has been very high. One of the main

reasons for high attrition rate during clinical trials is the limitation of animal

models used for preclinical testing of drugs, which are not able to clearly predict

drug response in patients. In spite of advancements in use of preclinical and

in vitro models, viz., cell cultures, computational models, animals, and

humanized animals during drug discovery process, there is a need to develop a

human-specific model to bridge this gap between animal-based models and

human clinical trials.

In vitro disease models can provide an excellent alternative to the animal

models as they minimize the use of animals and understand the cellular and

molecular aspects of various diseases. One of the important techniques for

development of three-dimensional (3D) in vitro model is 3D bioprinting, which

makes realistic in vitro disease models and mimics the actual cellular arrangement

of any human tissue or organ. Organ-on-a-chip as 3D in vitro model has shown its

potential to understand the disease mechanism along with evaluation of new

therapeutic compounds. Further, multiple organs on a chip are utilized to under-

stand drug–drug interactions and pharmacokinetic profile of new drugs and thus

show potential to predict safety and efficacy of drug in patients in a more realistic

G. Aggarwal · R. K. Goyal (*)

Delhi Pharmaceutical Sciences and Research University, New Delhi, India

e-mail: goyalrk@gmail.com

G. Kaithwas

Babasahem Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India

M. Singh

Department of Pharmaceutical Sciences, Assam University, Silchar, Assam, India

# The Author(s), under exclusive license to Springer Nature Singapore Pte

Ltd. 2022

R. C. Sobti, N. S. Dhalla (eds.), Biomedical Translational Research,

https://doi.org/10.1007/978-981-16-9232-1_6

73