Title : Artificial Intelligence advancing dermatological research through enhanced clinical trial precision and accelerated treatment discovery
Abstract:
Recent studies have shown how artificial intelligence (AI) has the potential to analyze existing data to innovate trial design and boost the success rates of clinical trials. AI enables the precise analysis of complex, large-scale datasets with speed and accuracy previously unattainable through traditional methods. This review aims to summarize the latest developments in how artificial intelligence is revolutionizing dermatological clinical trials and randomized controlled trials. Additionally, this review explores how AI-powered machine learning 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 eczema, psoriasis, and melanoma. By refining patient selection and predicting individualized treatment responses, AI optimizes trial design, reducing variability and improving trial efficiency while also increasing the likelihood of successful outcomes. 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.
Future research should investigate how bias and hallucination can be mitigated in AI models to optimize trial outcomes. 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.
