Winslow leaned back and drummed the fingers of his right hand on the desk. “I don’t understand. So you sequenced some DNA and retroactively predicted evolutionary patterns that we can already measure anyway. Why should we care? Where are you going with this? And more to the point: How can AgriMed use this to further our drug research? How can this be monetized? I supported this research in the hope that you would find a genetic root for cancer. Or better yet, a genetic root for fighting cancer.”

A tingle raced up Juan’s spine as he nodded enthusiastically. “Yes. Exactly. I did. That’s why I started with the mammoth. As you probably know, modern elephants are highly resistant to tumors. They have many extra copies of TP53, a known tumor-suppressor gene. So I wanted to see how that evolved. Then I stumbled onto the pattern I told you about, and it suddenly dawned on me that if I could predictably follow the pattern of all of these different extinct animals and study how various parts of their genetic code evolved, couldn’t I, using the same algorithm, simulate how our genes will evolve in the future?

“Imagine it. What will our genetics look like in a thousand generations? Ten thousand generations? What will we be able to discover? We’ve mapped our genes, but we’ve barely scratched the surface of truly understanding them. We hunt and peck like blind chickens searching for a kernel of corn, just hoping that the genetic modifications we experiment with do something useful. But with this predictive algorithm, we could model in months what nature would take tens or hundreds of thousands of years to do.”

Juan leaned over and flipped to the summary page of his most recent simulation. “In that simulation run, I applied my algorithm against the genome for the common laboratory rat. I simulated the evolution of the rat’s DNA across the next two hundred thousand generations. That’s about four to five thousand years of future evolution.”

Winslow leaned closer to the printout on his desk, his finger tracing across the page. Was that a flicker of interest? Juan waited uneasily, shifting his weight from one foot to the other.

Suddenly, Winslow looked up. “If I’m reading this right, you believe that, given a few thousand years of evolution, the common rat will begin to show multiple copies of the TP53 tumor-suppressing gene.”

Juan nodded. “That’s what the simulations are showing. It’s much more complicated than that—the entire genome has all sorts of changes that need to be studied—but it was easy for me to pick up that anomaly since it was something the computers were already flagging. And if I can continue my work, see what triggered that change, and better yet, actually see this in a live specimen…”