The TITAN-X Platform Integrates Big Data, Artificial Intelligence, Bioinformatics, and Advanced Computational Modeling to Understand Immune Responses and Develop the Next Wave of Precision Medicines.

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Annual Review of Biomedical Data Science Pub Date : 2025-04-16 DOI:10.1146/annurev-biodatasci-103123-094804

Ryan Baker, Josep Bassaganya-Riera, Nuria Tubau-Juni, Andrew J Leber, Raquel Hontecillas

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Abstract

The TITAN-X Precision Medicine Platform was engineered to rapidly, fully, and efficiently utilize large-scale immunology datasets, including public data, in drug discovery and development. TITAN-X integrates big data with artificial intelligence (AI), bioinformatics, and advanced computational modeling to seamlessly transition from early target discovery to clinical testing of new therapeutics, developing biomarker-driven precision medicines tailored to specific patient populations. We illustrate the capabilities of TITAN-X through four case studies, demonstrating its use in computationally driven target discovery; characterization of novel immunometabolic mechanisms in infectious, inflammatory, and autoimmune diseases; and identification of biomarker signatures for patient stratification in clinical trials designed to maximize therapeutic efficacy and safety. Data-driven and AI-powered approaches like TITAN-X are enhancing the pace of drug development, reducing costs, tailoring treatments, and increasing the probability of success in clinical trials.

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TITAN-X平台集成了大数据、人工智能、生物信息学和先进的计算建模，以了解免疫反应并开发下一波精准医疗。

TITAN-X精密医学平台旨在快速、全面、高效地利用大规模免疫学数据集，包括公共数据，用于药物发现和开发。TITAN-X将大数据与人工智能（AI）、生物信息学和先进的计算建模相结合，从早期靶点发现无缝过渡到新疗法的临床测试，开发针对特定患者群体的生物标志物驱动的精准药物。我们通过四个案例研究说明TITAN-X的能力，展示其在计算驱动的目标发现中的使用；传染病、炎症和自身免疫性疾病中新的免疫代谢机制的表征在临床试验中识别患者分层的生物标志物特征，以最大限度地提高治疗效果和安全性。像TITAN-X这样的数据驱动和人工智能驱动的方法正在加快药物开发的步伐，降低成本，定制治疗方法，并增加临床试验成功的可能性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Annual Review of Biomedical Data Science

CiteScore

11.10

自引率

1.70%

发文量

期刊介绍： The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.