TRANSFORMING CLINICAL TRIAL MANAGEMENT WITH SALESFORCE AI: A TECHNICAL OVERVIEW
DOI:
https://doi.org/10.34218/IJCET_16_01_195Keywords:
Artificial Intelligence In Healthcare, Clinical Trial Management, Data Security And Compliance, Patient Recruitment Optimization, Supply Chain AnalyticsAbstract
This comprehensive article explores the transformative impact of Salesforce AI on clinical trial management in the life sciences industry. The article examines how artificial intelligence is revolutionizing various aspects of clinical trials, from patient recruitment and supply chain optimization to data management and healthcare professional integration. The article highlights significant improvements in operational efficiency, patient matching accuracy, and regulatory compliance through AI-driven solutions. The integration of advanced machine learning algorithms, natural language processing, and predictive analytics has fundamentally changed how trials are designed, executed, and monitored. The article demonstrates how Salesforce's AI capabilities address critical challenges in trial management while enhancing patient engagement, reducing operational costs, and maintaining rigorous quality standards across different therapeutic areas.
References
Rizwan Qureshi, et al., "Artificial Intelligence and Biosensors in Healthcare and Its Clinical Relevance: A Review," IEEE Access ( Volume: 11), 2023. Available: https://ieeexplore.ieee.org/abstract/document/10149321
Imad Faghmous, et al., "Why We Fail: An Analysis of Terminated Interventional Clinical Trials in Lymphoma," Clinical Research and Regulatory Affairs, Volume 40, Issue 4, 2023, Pages 100032, https://doi.org/10.1016/j.clitra.2023.100032. Available: https://www.sciencedirect.com/science/article/pii/S0006497123083465
Stefan Harrer, et al., "Artificial Intelligence for Clinical Trial Design," Trends in Pharmacological Sciences, Volume 40, Issue 8, August 2019, Pages 577-591. Available: https://www.sciencedirect.com/science/article/pii/S0165614719301300
Abdalah Ismail, et al., "The role of artificial intelligence in hastening time to recruitment in clinical trials," BJR Open. 2023 May. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC10636341/
Tapan Senapati, et al., "Enhancing healthcare supply chain management through artificial intelligence-driven group decision-making with Sugeno–Weber triangular norms in a dual hesitant q-rung orthopair fuzzy context," Engineering Applications of Artificial Intelligence, Volume 135, September 2024, 108794. Available:
https://www.sciencedirect.com/science/article/abs/pii/S0952197624009527#
Matthew I Miller, et al., "Machine Learning in Clinical Trials: A Primer with Applications to Neurology," Neurotherapeutics. 2023 May 30. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC10228463/
Scott Askin, et al., "Artificial Intelligence Applied to clinical trials: opportunities and challenges," Health Technol (Berl). 2023 Feb 28. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC9974218/
Suman Deep, et al., "AI-Driven Data Security in Healthcare: Safeguarding Data and Financial Transactions," International Journal Of Novel Research And Development, 2024. Available: https://www.researchgate.net/publication/384438304_AI-Driven_Data_Security_in_Healthcare_Safeguarding_Data_and_Financial_Transactions
Vangelis D. Karalis, "The Integration of Artificial Intelligence into Clinical Practice," Appl. Biosci. 2024. Available: https://www.mdpi.com/2813-0464/3/1/2
Robert A. Greenes, et al., "Clinical decision support models and frameworks: Seeking to address research issues underlying implementation successes and failures," Journal of Biomedical Informatics, Volume 78, February 2018, Pages 134-143. Available: https://www.sciencedirect.com/science/article/pii/S1532046417302757
Panagiota Galetsi, et al., "The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19," Soc Sci Med. 2022 Apr 12. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC9001170/
Lucas Glass, et al., "Ai In Clinical Development Improving safety and accelerating results ," IQVIA Institute for Human Data Science, White Paper, pp. 1-42, 2023. Available: https://www.iqvia.com/-/media/iqvia/pdfs/library/white-papers/ai-in-clinical-development.pdf
Yizhuo Wang, et al., "Application of machine learning methods in clinical trials for precision medicine," Jamia Open 5(1), 2022. Available: https://www.researchgate.net/publication/358479573_Application_of_machine_learning_methods_in_clinical_trials_for_precision_medicine
Varun H Buch, et al., "Artificial intelligence in medicine: current trends and future possibilities," Br J Gen Pract. 2018 Mar. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC5819974/
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