In order to provide better treatment for patients and more effective, targeted drugs, it is vital to understand disease mechanisms and to identify informative markers for patient susceptibility, disease progression, treatment response, and individual drug tolerance. The move to more stratified medicine is a key paradigm for global health care, but also an enormous challenge for biologists and data scientists. Technological developments are enabling larger studies that can rapidly deliver huge quantities of data—their translation into meaningful, actionable biological understanding is essential, but often difficult. Genomics and proteomics are increasingly combined to characterize the role of specific biomarkers in disease, uncover novel biological pathways, provide rationales for drug target selection, and develop new, more efficacious therapies. These large-scale, multiomics studies generate complex datasets that highlight an important example of the big-data problem. At the same time, the credibility of scientific research is facing challenges from the so-called “replication crisis,” raising questions about how we judge the significance of the data we obtain. Thus, biostatisticians play an increasingly critical role in interpreting and quality-assuring the outcome of such studies, throughout the process of biomarker discovery, validation, clinical implementation, and drug development. Our panelists will share their experiences in applying biostatistics to large datasets in order to facilitate more confident development of novel therapeutics, and to drive precision medicine.
During the webinar, the speakers will:
- Describe their biostatistical approaches to analyzing large, complex datasets
- Illustrate how biostatistical analysis can translate complex data into biological insights
- Discuss how biomarkers can be leveraged to identify unique underlying biological mechanisms and personalize patient treatment
- Answer your questions during the live broadcast!
This webinar will last for approximately 60 minutes.