ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY: A PROMISING FRONTIER
International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)
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Abstract
The degradation of the environment is one of the most pressing challenges of the 21st century. Climate change, deforestation, loss of biodiversity, and pollution threaten ecosystems and human livelihoods. In response, scientists and conservationists are increasingly turning to AI as a powerful tool to aid in conservation efforts. By leveraging AI's capabilities in data analysis, predictive modeling, and automation, stakeholders can improve their understanding of complex ecological systems, streamline conservation efforts, and enhance resource management. The intersection of technology and pharmaceuticals heralds a new era in drug discovery, where Artificial Intelligence (AI) emerges as a transformative force. By leveraging vast datasets and advanced algorithms, AI not only accelerates the identification of potential drug candidates but also refines the processes involved in their development. The drug discovery landscape is replete with challenges such as high costs and lengthy timelines, making traditional methods increasingly inadequate. Incorporating AI into this domain has shown remarkable potential in enhancing efficiency and effectiveness, as illustrated in frameworks that detail various stages of drug discovery (see). Each phase, from target identification to clinical trials, benefits from AIs capability to analyze complex data patterns, thus improving the likelihood of successful outcomes. As we delve deeper into AIs applications, it becomes evident that this technology is not just an adjunct but also a critical partner in forging the future of pharmaceuticals.
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