ReviewPerspectives in clinical research
Applied intelligence in clinical drug development: Potential benefits and emerging concerns.
Review in Perspectives in clinical research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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1 author.
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Abstract
The use of artificial intelligence (AI) technology and machine learning (ML) is growing exponentially and is moving from AI to applied intelligence. Pharma industry is actively exploring the potential use of AI tools in new product discovery and clinical development. Some of the practical applications of AI in clinical development are for improving the efficiency of enrollment, selection and stratification of participants, optimizing study treatment, enhancing compliance, data analysis, and pharmacovigilance. AI applications have been used for outcome prediction; covariate selection/confounding adjustment; anomaly detection; real-world data phenotyping; imaging, video, and voice analysis; endpoint assessment; and pharmacometric modeling in regulatory submissions. However, widespread applications of novel yet difficult-to-understand AI technology in clinical development would need balancing the benefits and risks and resolving issues of scientific validity, technical quality, and ethics. The article discusses the potential benefits and emerging concerns of applying AI in clinical drug development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.