• Oncology
  • Healthcare
  • Blog Post

Raising the bar to transform cancer care

Publish Date

06 NOV 2020


Luciano Rossetti


Navigating cancer biology is both challenging and exciting, but despite the great strides we’ve made, there is still more to be done.

Raising the bar in cancer biology
Cancer biology is complex, rife with biological redundancy and dramatically dynamic in nature. Navigating it is both challenging and exciting as the standard of care is improving at an exceptional pace. But despite the great strides the industry has made as evident in the large number of parallel clinical trials with registrational intent, there is still an unmet medical need for patients with cancer—we need to raise the bar. To meet this challenge, we’re strengthening our research and development (R&D) approaches in order to deepen our understanding of tumor biology and evolution. Through the use of artificial intelligence and computational testing of biological samples, we’re beginning to really understand the interconnections of different biological mechanisms, and gain an early understanding of treatment combinations and timing, as well as smart execution of clinical trial design. Today, we’re facing a much greater need than just new medicines, and in the great journey of innovation, this is only the beginning of what’s required to make an impact on a patient’s life.


There is more to explore
The traditional steps of innovation, of identifying fundamental biological underpinnings of cancer, and identifying its weaknesses and specific targets, have constructed a strong knowledge base. However, this field is advancing quickly, and agile methods of research and development are needed in order to truly transform care.

We as a research community need to deepen our understanding of tumor biology, its microenvironment and evolution; of targets and their molecular pathways; and of the multi-dimensional interactions between cancer cells and our immune system. But we also need to be able to predict what types of tumors will respond and how resistance develops, and we need to figure out how to start predicting which therapeutic combinations will be effective. We need to incorporate artificial intelligence and computational testing in order to understand the interconnections, combinations, timing and smart execution of clinical trial design.  


A heightened call to action
The COVID-19 crisis exemplifies how important it is that different areas of expertise work smoothly and quickly together. We’re at a new, unprecedented level of urgency, which has accelerated all aspects of drug discovery and development. Because of the pandemic, there’s an increased demand for precision medicine, safer treatments, wider safety windows and tailored approaches that are more convenient so that patients don’t need to necessarily visit a healthcare center.


It can be done
We’ve raised the bar before. For example, recent checkpoint inhibitors, CTLA-4, PD-1 and PD-L1, have transformed the immuno-oncology field, and have shown dramatic clinical benefit in several cancer types. Another example is the understanding that mutations in the epidermal growth factor receptor (EGFR) gene drive around 30% of all non-small cell lung cancers1,2, and in fact, EGFR is a common driver in other cancers. Sometimes, a patient’s own immune system, T cells in particular, isn’t strong enough to fight the cancer. Chimeric antigen receptor (CAR) T cells are genetically modified patient T cells that can scout out and attack cancer cells. Because CAR-T cells use a mechanism of action different from chemotherapy, they provide an alternative type of treatment, which also aims to spare healthy cells from being killed. These new approaches, together with the discovery of specific small molecule inhibitors, has definitely changed the landscape of targeted treatments. However, we will need to always address the evolution of disease and continue to improve treatment impact for each patient.


Unite expertise
To successfully meet the challenges of complex cancer biology or new emerging diseases, we need a critical mass of experts with profound knowledge in each aspect of the puzzle. The key is seamless integration of all pockets of innovation, technology and great talent at different stages of development across the entire company.


Complement externally
At the same time, there’s no question that small companies and startups often discover new technologies or mechanisms, and in order to have a bigger impact we must enable them to plug into our enterprises, which have the ability to develop new therapies. And in order to effectively execute sophisticated clinical trials, we need to stay very connected to the oncology field for back translation.


Circling back to human biology is critical
At Merck KGaA, Darmstadt, Germany, we’re focused on creating therapeutic areas of expertise that span end-to-end, and continue to emphasize looking beyond R&D. We’re working to break the silos within critical R&D functions that support the enterprise and recognize that back translation—or bedside-to-bench—where we work using real-time human experience and data from the clinic to directly inform new discoveries, is as important as working from the bench-to-bedside (traditional R&D), in optimizing treatment development

We have the opportunity to fully leverage information about human and cancer biology as treatments progress. Data needs to be confirmed from human information, for example, with patient samples from baseline and different stages of disease, treatment and response to treatment, to really drive the next steps of innovation. This is extremely difficult because of the multitude of factors converging on a patient: the complex biology underlying each type of cancer, the dynamic environment affected by particular stages of disease, use of a changing standard of care. But without real-time human information before and during intervention, it will be tough to make serious advances.

However, novel methods are offering new approaches for collecting this information. Take liquid biopsy as an example, which gives us more dynamic measurements that correlate with the clinical picture. One of our shorter-term gains is molecular drivers, where we see dramatic use of the tumor liquid biopsy approach. I expect that this will soon be used in practice and will grow explosively, and together with next-generation sequencing will give us the ability to look sequentially and to identify new molecular drivers that emerge during treatment.

What’s most important is to remember what we’re starting with. There is, in my view, no area of biology so rich with potential to address unmet medical needs as oncology. We should acknowledge the uniqueness of cancer biology—because despite the challenges we face, we’re also passionate about pursuing the science to raise the bar and make a greater difference.  


1 Zhang, YL. et al. 2016. The prevalence of EGFR mutation in patients with non-small cell lung cancer: a systematic review and meta-analysis. Oncotarget. https://doi.org/10.18632/oncotarget.12587
2 Harrison, P. et al. 2020. Rare epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer. Semin. Cancer Biol. https://doi.org/10.1016/j.semcancer.2019.09.015


  • US-NONO-00080