With new advancements in medicine come new advancements in technology. However, the ability for them to productively overlap is becoming an increasingly studied topic. While the thought of artificial intelligence (AI) in medical practice might be concerning to some, it is possible that implementing these systems may provide a pathway to knowledge that was previously unreachable.

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AI is a category of computer science that has the ability to efficiently and accurately analyze complex data. Applying this kind of data mining to healthcare could drastically change the landscape of the medical and pharmaceutical industries. Because of its ability to analyze unstructured data and successfully identify correlations, AI has been shown to be superior in accurately predicting previously unknowable outcomes. Some of the areas in which AI has demonstrated great promise are disease diagnosis and monitoring, drug development, and patient treatment (Bhattamisra et al., 2023).

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When considering the capabilities of AI in drug development, it is especially pertinent to discuss its potential in clinical trials. In a recent study, published in July 2023, it was found that AI could prospectively predict the outcome of Phase II to Phase III clinical trial outcomes with 79% accuracy. As a result, it was strongly suggested that pharmaceutical companies should incorporate predictive AI into their drug development efforts (Aliper et al., 2023). This would not only expedite the clinical research process by filtering out the majority of null-findings research, but it would also save billions of dollars in the pharmaceutical industry.

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Some of the limitations of AI in research include being able to synthesize understanding of more granular aspects of clinical trials and their protocols. Developing this component of AI learning would give it the ability to actually create a viable, exhaustive protocol that demonstrates comprehensive complexity in the design, population, procedures, and analysis. While this is still being studied and tested, it seems obvious that the utility of AI in clinical research still proves largely advantageous and desirable. 

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It seems inevitable that AI will continue to develop to play a pivotal role in clinical research. With its current ability to analyze complex data and successfully learn unstructured information, AI brings the potential for significantly improving medical knowledge and advancements. Although it is not perfect, it appears that it shows great promise to aid the field of medicine, and ultimately patient care.

References

Aliper, A., Kudrin, R., Polykovskiy, D., Kamya, P., Tutubalina, E., Chen, S., Ren, F., & Zhavoronkov, A. (2023). Prediction of Clinical Trials Outcomes Based on Target Choice and Clinical Trial Design with Multi‐Modal Artificial Intelligence. Clinical Pharmacology & Therapeutics, cpt.3008. https://doi.org/10.1002/cpt.3008

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Bhattamisra, S. K., Banerjee, P., Gupta, P., Mayuren, J., Patra, S., & Candasamy, M. (2023). Artificial Intelligence in Pharmaceutical and Healthcare Research. Big Data and Cognitive Computing, 7(1), 10.

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