Evolution underlies both the development of humankind as well as the greatest challenges to human health. Across the tree of life, cancer and infectious viruses, prokaryotes, and eukaryotes exist within complex competitive landscapes that can promote or inhibit disease progression and therapeutic resistance. The amazing diversity of heterogenous cell populations raises existential questions about how to combat drug resistance evolution. The convential approach to this problem is to attempt to reverse engineer evolving biological systems. I.e., after a selection has occurred, we isolate resistant cells, attempt to determine what caused drug resistance and treat the resistant state. This strategy results in a ?resistance treadmill? whereby resistance evolution occurs, new drugs combat drug resistance and then resistance re-emerges ? a process that occurs until we run out of effective agents. We believe that instead of combatting evolution, we should make use of it. We propose to employ a ?forward engineering? approach that seeks to create new paradigms to control and understand evolution. By creating a dual switch gene drive, we posit that we can use engineering design to build populations whose evolution can be guided by model driven therapeutic interventions. In essence, we will drive evolution in heterogenous cell populations towards eradicatable outcomes. This would be paradigm shifting in the clinic, but, by building these cellular systems, manipulating them with chemistry and biology, and quantiatively modeling their dynamics, we can also ?build to understand? evolution as we take giant strides towards controlling it.
Despite our best efforts, drug resistance evolution--from prokaryotes to cancers-- is one of the largest threats to public health. We propose that a novel paradigm to understand and fight drug resistance evolution is to use forward engineering design. Instead of simply describing the outcome of resistance evolution after it has occurred, we will use model-driven design to build dual-switch selection gene drives, and we will test their ability to control resistant populations which will enable a deeper understanding of biology and a shift in clinical paradigms.
