Two thousand questions

Late at night Arjun sits at a monitor in his lab, a glowing model turning above him. “Most candidate molecules fail,” he says. “Usually we learn that after months in the lab.” He wants to learn it earlier, on the screen, before anyone spends a month at the bench.

From the story: Two thousand questions

Morning light fills the same lab. On the screen, twelve candidates stand highlighted out of the long list from the night. Arjun smiles, but only a little. “Twelve. Only twelve go to the lab,” he says. “A simulation is a question, not an answer.”

From the story: Two thousand questions

In a glass meeting room Arjun shows the investors one simple chart: two thousand simulated candidates on the left, twelve on the right. Someone asks about results. He answers calmly: “I don't promise results. I promise we stop spending months on the wrong ones.”

From the story: Two thousand questions

In a corridor by the lab doors Arjun shakes hands with a scientist from a partner lab. Her team runs the real tests next week. Until then the twelve are only well asked questions. “Follow the experiment,” he says.

From the story: Two thousand questions

Standing in the lab corridor next to a colleague, Arjun says what the whole floor already knows: “Nobody on this floor trusts a simulation alone. We test the twelve, and we write down every result.” The candidates that fail are written down too.

From the story: Two thousand questions