Systems Biology at Merrimack integrates the fields of biology, computing and engineering. We use these tools to gain a more comprehensive understanding of the dynamics of cancer. Rather than focus on individual molecules, our discovery efforts seek to encompass the complexity of entire biological networks. Our foundation is data-driven. We build predictive computational models of tumor biology and using simulation to drive the productivity and precision of our research. Our systems research is comprehensive to all levels of tumor biology, spanning the biochemical interactions of intracellular signaling networks to systems pharmacology.
Cancer is difficult to treat because it is dynamic on multiple dimensions. Our research focuses on three biological characteristics of tumors that we have found critical to engineering and selecting the best treatments: the signaling network addictions that drive tumor growth; the signaling adaptations that occur as tumors become resistant to treatment; and the influence of the micro-anatomy of tumor physiology and its micro-environment on growth and treatment. Learn more about the biological states of addiction, adaptation, and micro-anatomy.
Select a dimension to learn more.
The signaling dependencies that drive
tumor growth have the potential to evolve with the growth and development of the tumor or as a response to treatment. Anticipating the potential paths of resistance is critical to delivering the most effective therapy.
Example: MM-111 >
Compensatory activation of HER3 is believed to be a central mechanism by which cancer cells develop resistance to targeted therapies as well as many chemotherapies. MM-111 is an investigational product designed to inhibit ligand-induced HER3 signaling in HER2-expressing cancer cells. Therefore, the combination of MM-111 with other cytotoxic agents may prevent the development of resistance by proactively blocking potential adaptive mechanisms.
In response to genomic stress, cancer cells develop addictions to specific signaling events that continually transmit a message of growth, overriding the regulatory balance of healthy cell development. These dependencies take root in the redundant signaling networks resident to normal cells and are the key to precise diagnosis and treatment.
Example: MM-151 >
Overexpression and/or constitutive activation of the EGFR receptor is a driving force for multiple types of cancer. These classes of cancers are effectively addicted to EGFR signaling for their continuous growth and proliferation. MM-151 is an investigational product consisting of three monoclonal antibodies that bind to EGFR and inhibit both ligand dependent and independent signaling. The result is a near complete inhibition of the addictive signals driving these cancers.
The tumor micro-anatomy describes the physiology of the tumor itself as well as the environment outside of a cancer cell and its role in the production of tumors. The micro-anatomy includes the involvement of the vasculature, immune system, extracellular factors, interaction with non-cancer cell types and neighboring tissues. Understanding how their collective role affects tumor development can help optimize drug delivery and potential efficacy.
Example: MM-398 >
For a cancer therapy to be effective, it must have adequate access to the tumor. MM-398 is an investigational liposome encapsulated irinotecan designed to accumulate in tumors, while simultaneously minimizing exposure to healthy non-target tissues. We believe that this ability to deposit directly in the tumor environment could result in a higher therapeutic window and the delivery of greater levels of irinotecan than can be achieved with conventional administration.