Introduction to In Silico Modeling and Simulation

Abstract

Computational advancement is the need of the present century and has played an important role in transforming the medical industry and health research. The application of engineering principles to biology using computational techniques has led to the development of in silico modeling and simulation. This chapter discusses the role of computational advancements in medical research and the importance of artificial intelligence and machine learning in modeling and simulation of diseases with personalized healthcare. In silico modeling and simulation provide precise predictions about the underlying signaling mechanisms involved in various diseases. This leads to early detection, as well as time-efficient and cost-effective solutions for healthcare practitioners. Computational techniques enhance targeted drug therapy in the pharmaceutical industry, facilitating drug design, development, and testing. Although in silico modeling and simulations are trending nowadays, challenges and limitations remain, such as the accuracy of the model, the depth of complex biological models, effective and efficient datasets, the lack of data availability, patient concerns, consent, and finally, the validation of the data as the model persists. Keeping the constraints in mind, the health informatics field has boosted the development and analysis of much more complex models like those related to cancer and diabetes. For advancing the medical industry, the impact of in silico models would bring a revolution in patient care. This chapter has attempted to cover everything, from significance to constraints and difficulties in in silico modeling.

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