Artificial Intelligence In Clinical Research

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Artificial intelligence (AI), also known as machine intelligence, is a branch of computer science that focuses on building and managing technology. They are capable of learning to freely make decisions and carry out actions on behalf of a human being – Techopedia. Huge impacts have been seen in different attempts by Nigerians in software development and devices that positively improve healthcare outcomes. But why AI in clinical research?

While being key to improving healthcare and outcomes, clinical research as currently practiced is complex, labor-intensive, and expensive. It could also be prone to unexpected errors which can, at times, threaten its successful application, and acceptance.AI, however, has been proven fit to deliver authentic results. Wearable gadgets and apps have made it easier for researchers to provide real-time data. Copied from AI and clinical trials

It is important to know that successful clinical trials require exceptional preclinical investigation and planning. During which promising candidate particles and targets are identified and the investigational strategy to achieve regulatory approval is defined. Perhaps any error that occurs in this phase can delay the discovery of promising drugs or doom clinical trials to eventual failure.  

Impact of AI in clinical research;

• AI can help researchers take advantage of previous and ongoing research to decrease the inefficiencies of the preclinical process. https://pubmed.ncbi.nlm.nih.gov/34399832/

• It also helps to trim the process and increase the success of drug target identification and candidate molecule generation. This can be achieved through synthesis of massive amounts of existing research, elucidation of drug mechanisms, and predictive modelling of protein structures and future drug target interactions. Culled from The role of machine learning in clinical research: transforming the future of evidence generation | Trials | Full Text

• Maxing out the success and efficiency of trials during the planning phase through application of simulation techniques to facilitate trial protocol development. Excerpt from The role of machine learning in clinical research: transforming the future of evidence generation | Trials | Full Text

Xcene Research believes that with the use of Artificial intelligence, there are clear opportunities to improve the efficiency and yield of clinical research. Exceptional clinical solutions will also be provided to biopharmaceutical companies and medical institutions which will aid medical breakthroughs.