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<p>Artificial intelligence (AI) has the potential to analyze existing data to innovate trial design and boost the success rates of clinical trials. This review aims to summarize the latest developments in how AI is revolutionizing dermatological clinical trials and randomized controlled trials (RCTs). AI enables the precise analysis of complex, large-scale datasets with speed and accuracy that were previously unattainable through traditional methods. AI-powered machine learning (ML) algorithms can identify subtle patterns in disease progression, treatment efficacy, and patient demographics from clinical trial data and electronic health records, facilitating the discovery of novel biomarkers and therapeutic targets for conditions like atopic dermatitis, psoriasis, and melanoma. By refining patient selection and predicting individualized treatment responses, AI optimizes trial design, reduces variability, and improves trial efficiency while increasing the likelihood of successful outcomes. AI’s predictive modeling can identify early indicators of success or failure, allowing for real-time adjustments in trial protocols, which accelerates the drug development process, reduces costs, and ensures more accurate, reproducible results. In addition to improving trial efficiency, AI enables researchers to uncover previously unknown associations between environmental, genetic, and clinical factors, fostering more inclusive and personalized treatment approaches across diverse populations. By analyzing these hidden correlations, AI can help target therapies to specific subgroups, improving both safety and efficacy. Its continuous learning capability supports adaptive trial designs, allowing treatment protocols to evolve based on interim findings, further enhancing the precision of clinical trials. However, AI hallucinations must be taken into account, as outputs can be fabricated and lead to flawed study designs. As AI evolves, it is poised to transform dermatology by enhancing trial precision, expediting treatment development, and advancing personalized care, ultimately paving the way for more effective, patient-centered therapies that meet the specific needs of individual patients.</p>

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Advancing dermatological clinical trials through artificial intelligence

  • 期刊论文

  • 发表日期：

    2026年2月7日

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  • Kelly Frasier,
  • Mary Grace Hash,
  • Brittani Reme,
  • Donna Pham

摘要

Artificial intelligence (AI) has the potential to analyze existing data to innovate trial design and boost the success rates of clinical trials. This review aims to summarize the latest developments in how AI is revolutionizing dermatological clinical trials and randomized controlled trials (RCTs). AI enables the precise analysis of complex, large-scale datasets with speed and accuracy that were previously unattainable through traditional methods. AI-powered machine learning (ML) algorithms can identify subtle patterns in disease progression, treatment efficacy, and patient demographics from clinical trial data and electronic health records, facilitating the discovery of novel biomarkers and therapeutic targets for conditions like atopic dermatitis, psoriasis, and melanoma. By refining patient selection and predicting individualized treatment responses, AI optimizes trial design, reduces variability, and improves trial efficiency while increasing the likelihood of successful outcomes. AI’s predictive modeling can identify early indicators of success or failure, allowing for real-time adjustments in trial protocols, which accelerates the drug development process, reduces costs, and ensures more accurate, reproducible results. In addition to improving trial efficiency, AI enables researchers to uncover previously unknown associations between environmental, genetic, and clinical factors, fostering more inclusive and personalized treatment approaches across diverse populations. By analyzing these hidden correlations, AI can help target therapies to specific subgroups, improving both safety and efficacy. Its continuous learning capability supports adaptive trial designs, allowing treatment protocols to evolve based on interim findings, further enhancing the precision of clinical trials. However, AI hallucinations must be taken into account, as outputs can be fabricated and lead to flawed study designs. As AI evolves, it is poised to transform dermatology by enhancing trial precision, expediting treatment development, and advancing personalized care, ultimately paving the way for more effective, patient-centered therapies that meet the specific needs of individual patients.