This year’s 2024 Precision Medicine World Conference (PMWC)
This years 2024 Precision Medicine World Conference (PMWC) was held from January 24-26th at the Santa Clara Convention Center in Silicon Valley, California. Like previous years, the conference was a pivotal gathering of experts at the forefront of healthcare and genomics and brought together thought leaders, innovators, and professionals to delve into precision medicine and health.
Starting with the end in sight: incorporating a multi-omic workflow in your research
At PMWC, DNA Genotek was pleased to speak about the importance of incorporating a multi-omic workflow into research studies. Presented by one of the authors of this blog post, Dr. Tara Crawford Parks emphasized the importance of incorporating multi-omics, specifically genomic and transcriptomic datasets, in study workflows.
A multi-omic approach can generate more robust datasets that give broader insights for the system being investigated and enable researchers to go beyond the genome, to accelerate biological discovery. However, there are key considerations to keep in mind when designing multi-omics studies, and the focus of the presentation was on the considerations specific for the biological sampling methodology used.
Choosing an efficient and cost-effective sampling methodology becomes even more critical when incorporating multi-omics into a study due to the challenges associated with collecting multiple independent samples to capture various analytes of interest. Some of these challenges include:
Sampling variability
The chosen methodology for sample collection can increase the variability between or within samples and this variability can be carried throughout a workflow, ultimately impacting downstream data analysis and producing unnecessary noise in datasets.
Logistics
Collecting multiple samples creates additional logistical challenges related to sample traceability, storage space requirements, and often is associated with increased costs. Finding a solution that captures and stabilizes multiple analytes of interest in a single tube can reduce or eliminate these challenges.
Sample type
The type of sample utilized and included in a multi-omic study can also have an impact on the overall success of the study.
Current progress on multi-omic research workflows
Taking a multi-omics approach can facilitate both translational outcomes and provide the foundation for precision medicine. However, there is a need for appropriate computational analysis workflows to integrate molecular signatures, such as genomics and transcriptomics, together while also including the relevant pathophysiological model. For example, in oncology, it is necessary to consider these molecular signatures with respect to the tumor microenvironment in order to create models that can inform clinical decision-making. In the oncology drug development process, genomics (DNA) data alone is often not sufficient to measure clinical outcomes; incorporating transcriptomic (RNA) data, in addition to genomic data, can provide greater biological insight to demonstrate that a drug is working as expected.