The identification and utilization of safety biomarkers plays a key role in mitigating toxicity risks and reducing costs in drug development, thereby accelerating the delivery of safe and effective drugs to patients. AI can streamline the identification of relevant biomarkers from the ever-growing biomedical literature, offering insights into drug resistance and toxicity.

Traditional keyword searching is highly inefficient, subject to bias and is not always comprehensive, providing limited potential for knowledge discovery and hypothesis generation. This selective approach introduces a bias towards familiar areas of expertise, which can lead to missed opportunities for novel insights and innovations. This is where AI comes in.

Biomarkers serve as objective measures of treatment response to guide patients towards the most appropriate therapies. Yet, in the era of big data, pinpointing promising biomarkers remains a challenging endeavor. AI is revolutionizing translational medicine by improving the efficiency and accuracy of biomarker identification. Here, we used Causaly to identify and prioritize biomarkers of sorafenib […]

Biomarkers are pivotal throughout drug development, from discovery to market, playing key roles in unravelling drug mechanisms, providing prognostic insights and assessing treatment efficacy. Despite the clinical promise, biomarker development is challenging. There are substantial obstacles, from disease heterogeneity and rigorous validation requirements to the inability to extract meaningful biomarker insights from extensive biological data.

With oncology pivotal trials averaging $32 million and a 95% drug failure rate, there is a growing interest in leveraging biomarkers for treatment optimization. Notably, drug resistance biomarkers are key in identifying treatment sensitivity, adjusting treatment protocols, and improving survival rates.

Pancreatic cancer is one of the most aggressive and fatal cancers worldwide. Treatment efficacy is a major concern, and there is a pressing need for reliable prognostic biomarkers to improve patient outcomes. Here, we used Causaly to uncover potential biomarkers for this disease.

In the evolving landscape of modern medicine, biomarkers are at the forefront of clinical research. Biomarkers can serve as objective measures of treatment response, guiding patients towards the most suitable therapies and reducing the risk of unnecessary and potentially harmful treatments.

Biomarkers 2023 was held in Manchester, UK on the 27th and 28th of February. The event brought together a diverse group of experts, across pharma, biotech, and academic institutions.