Healthcare generates an unprecedented amount of data from electronic health records, medical imaging, genomics, and more. This data, when effectively harnessed, is proving to be key to unlocking innovative treatments and accelerating the drug development process.

However, transforming this complex process into a data-driven endeavor requires a special blend of technology, talent, and execution. The organizations that can effectively employ data stand to drive health innovations that will help shape the future of disease management.

Unlocking the power of data requires organizations to build a workforce that is ready for the future. This is especially crucial in the era of proliferating artificial intelligence tools such as large language models (LLMs) which are democratizing data analysis and enabling insights that were once buried in the institutional memory of companies and only available to the “coding” community.

At Genmab, we champion “algorithmic leadership,” ensuring that our team, from research to patient support, is accustomed to the use of data, algorithms, and artificial intelligence to make decisions, improve efficiency, and solve complex problems. It’s about leveraging technology to enhance decision-making processes, predict future trends, and automate tasks that can free up human leaders to focus on more strategic and creative aspects of their roles.

This doesn’t mean replacing human judgment with AI; rather, it’s about augmenting human capabilities with technological tools to make better-informed decisions and providing all employees, regardless of role, with the data literacy tools and training they need to feel confident to take smarter, more data-driven actions.

Translating data into impact

Data science serves as a robust tool for healthcare innovators, offering the capacity to analyze and discern patterns in voluminous information, guiding researchers towards novel insights and discoveries. We harness the power of data to enable our teams to expedite the discovery, development, and commercialization of medicines and experiences rooted in a profound understanding of patients and their caregivers.

And, instead of siloing data scientists into their own division, they are fully embedded across the company and connect the right data and analytics tools with each team’s unique need to make more informed decisions.

Hisham Hamadeh, PhD
Hisham Hamadeh, PhD [Genmab]
For instance, data scientists in our discovery team use their expertise in data and AI to incorporate some form of algorithmic work and take advantage of large amounts of data at their fingertips to help identify the most promising targets and the antibodies to make. This is done side by side with wet-lab biologists.

Acknowledging our interconnectivity and interdependence, we have consciously invested in integrating AI and digital capabilities throughout our organization from its inception. The advantage of commencing our journey in the “digital era” allowed us to foresee the pivotal role that data and AI would play.

Today, we are integrating and analyzing complex data from different stages of the drug development process to transform our understanding of cancer and other serious diseases, inform the development of novel therapies, and equip us with the insight into how to match the right treatment to the right patient at the right time and at the right dose.

For instance, we’re currently identifying novel disease targets by canvassing private and public preclinical and clinical data. We’re also leveraging data on the historical relationship between cancer genetics and response to treatment to help us build the next generation of antibody medicines.

Beyond the lab, data can help us understand how patients progress on their care journey and anticipate what they or their caregivers might need. This can enable us to direct resources like personalized disease education toward patients and inform their healthcare providers where additional engagement might be helpful.

Democratizing data across the healthcare ecosystem

To unlock the full potential of data, collaboration is key. We must work in unison with industry, regulatory agencies, health care systems, patient advocacy organizations, policy makers, and academia to make healthcare data more accessible and actionable in a responsible and ethical fashion. We all share the collective goal of improving patient outcomes, and safe, secure data sharing is paramount to achieving this.

The good news is progress to open the healthcare ecosystem is already underway. For example, as part of the Cancer Moonshot initiative, the White House has recommended creating a National Cancer Data Ecosystem for sharing and analyzing cancer data so that researchers, clinicians, and patients can contribute and access data to better understand these complex diseases and advance important research. There have also been improvements in how patient data is stored and shared, including new federal regulations requiring health care organizations to provide patients with access to their full health records in a digital format, which is critical to empowering patients and improving care.

To maximize the benefit to patients, we must continue to focus on developing policies and practices that allow data to flow more freely, while ensuring robust privacy and security.

The biotech industry is at an exciting crossroads where data and technology, such as generative AI, are converging to unlock new opportunities from discovery through development and commercialization. We eagerly anticipate the road ahead as we further integrate AI and digital into our operations. We believe data science will continue to enhance the development of our antibody therapies to treat cancer and other serious diseases, ultimately touching as many lives as possible.


Hisham Hamadeh, PhD, is senior SVP, Global Head of Data Science & AI, Genmab.

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