Increasingly, data are transforming our understanding of diseases. This is especially true in cancer.

We have invested in robust data science capabilities to enable rapid data-driven decision making as we advance our products through all stages of development. Integration of disparate data sets from clinical and pre-clinical studies is a major guiding principle that is allowing us to extract novel insights regarding targets, investigational products, indications and patient biomarkers.

Data science is tightly embedded in the Genmab community to help:

• Democratize access to integrated data across the organization by providing stakeholders such as laboratory researchers and clinicians with intuitive views to complex data sets and analytics
• Identify novel disease targets by canvassing private and public clinical and pre-clinical data
• Identify clinical biomarker candidates and biological insights in real time during the conduct of clinical trials
• Scale and automate the derivation of novel discoveries by leveraging advancements in machine learning and artificial intelligence