AI in Genomic Data Analysis for Drug Development

Abstract: The drug development industry has greatly benefitted from the application of artificial intelligence (AI) in genomic data analysis. Genomic data is useful in understanding diseases genetics as well as in making drugs to counter the diseases. However, this process is quite challenging as it requires a lot of data and analysis which makes the process complex. This aspect of the study made the process to be time-consuming and quite resource intensive which necessitated a better and more efficient tool for analysis. AI has advanced machine learning and deep learning algorithms that enable it to be an effective option in the process. AI offers great solutions for processing large sets of data with efficient and accurate outcomes. As such, the drug development industry has benefited from reduced costs, saving time, and accurate and more effective research data. It has also ensured that therapies are tailor-made for the patients, including making appropriate treatments for the specific genetic profile, ensuring better treatment outcomes. It is therefore without doubt that artificial intelligence has been a great transformative force in the industry and continues to facilitate innovation and advancement in the process.

Keywords: Genomic data, drug discovery, genetics, machine learning.