The Integration of Nanotechnology, Artificial Intelligence (AI), Machine Learning (ML) and 3D-Bioprinting Approaches for Personalized COVID-19 Treatment

Abstract

The COVID-19 pandemic has thrusted the world into a public health crisis, necessitating a relentless pursuit of effective nanotechnological treatments alongside vaccination efforts. Coronavirus 2 (SARS-CoV-2, the virus that causes COVID-19) can persist in the blood and tissue for over a year, causing long COVID-19 and associated risks. As COVID continues to harm people worldwide, it is clear that there are numerous vastly different ways in which patients respond to the same SARS-CoV-2 virus, requiring a personalized nanotechnological drug approach. In the repurposing of drugs for COVID-19, in silico methods, driven by computational simulations, have proven instrumental. In harnessing the power of machine learning (ML), a subset of artificial intelligence (AI) tools, vast datasets of existing drugs and diseases can be efficiently analyzed to choose the right datasets for personalized COVID-19 treatment. Significantly, this approach is not only cost-effective but also expeditious, offering a quicker and more economical avenue than traditional drug discovery processes. In the study of SARS-CoV-2, ML has proven to be an effective approach, especially for identifying targets for potential therapeutic development and personalized treatment. Because ML models can handle large, complex datasets with ease, they are powerful tools for studying proteomic and genetic data of viruses. By discovering relationships in the data, ML models can help prioritize proteomic or genomic areas that are crucial for viral replication, entry, or evasion of host barricades. This process can lead to the identification of possible personalized therapeutic targets. This literature review article delves into the innovative approach of using AI, ML and nanotechnological 3D bioprinting (3DBP) for in silico drug repurposing to battle COVID-19. The article provides a detailed investigation of SARS-CoV-2 targets, the role of AI and ML in various aspects of COVID-19 management, and the integration of nanotechnological 3DBP in creating in vitro tissue models and therapeutic agents to precisely fabricate structures at the nanoscale. In doing so, this study highlights an important personalized and more effective approach to treat patients today for COVID-19 and any virus in the future.

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