Roy Rosman Nathanson

Using Long-read Sequencing to Advance Personalised Decision Making in Multiple Myeloma

The work in Cribbs lab focus on developing novel technology and computational analysis frameworks that empower new modes of treatment for disease. Recent technology developed in the lab allows for the measurement of translocations, variant calling, and alternative splicing in unprecedented detail.

In collaboration with Oxford Translational Myeloma Centre, we propose that leveraging LR sequencing's multi-modal data can unlock a deeper grasp of functional genomics, refining our diagnosis and prediction of MM with greater precision. Thus, we will employ state-of-the-art machine learning methodologies to identify and integrate the modalities which best predict outcomes. By doing so, we aspire to unearth not only novel diagnostic methods but also discover potential therapeutic targets, thus propelling us further towards our goal of personalised MM patient care.

How could your research ultimately benefit patients?

With the goal of uncovering unique insights into myeloma biology and pinpointing potential therapeutic targets, we will leverage LR sequencing data to understanding the intricacies of the disease, illuminating novel hallmarks, and thus empowering us to target myeloma more effectively and precisely.

About Adam

Coming from a background in medicine and biomedical engineering, I have had the opportunity to gain experience in diverse settings, including clinical environments, scientific research, and computational teams. This blend of experiences sparked my interest in translational research, where science and technology converge to address clinical challenges. My passion for advancing cancer diagnosis and treatment through integration of cutting-edge technology and science, along with the field's potential to make a significant clinical impact, led me to pursue a DPhil in Cancer Science.