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Cancer Precision Drug Discovery Using Big Data and Artificial Intelligence Technologies
Abstract
Improved cancer treatments are widely cited as a significant unmet medical need. Recent technological developments and the increasing availability of biological “big data” provide an unprecedented opportunity to systematically classify the primary genes and pathways involved in tumorigenesis. Artificial intelligence (AI) has shown great promise in many healthcare fields, including science and chemical discovery. The AI will explore and learn more using vast volumes of aggregated data, converting this data into “usable” information. The aim is to use current computational biology and machine learning systems to predict molecular behaviour and the probability of receiving a helpful medication, thus saving time and money on unnecessary tests. Clinical trials, electronic medical records, high-resolution medical images, and genomic profiles can all be used to help with drug growth. The discoveries made with these emerging technologies have the potential to lead to innovative therapeutic approaches.
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