Figure : Human-in-the-loop de novo molecular design: an AI-assistant helps a chemist to decide parameters of an MPO objective function 𝑆 𝑟,𝑡 (𝑥) iteratively at round 𝑟 and iteration 𝑡, where 𝑟 are rounds of goal-directed molecule generation with a de novo design tool, and 𝑡 are online interactions with a chemist. The objective consists of K molecular properties 𝑐 𝑘 (𝑥) with relative weights 𝑤 𝑘 . The utility of the 𝑘:th property is measured using a desirability function 𝜙 𝑟,𝑡,𝑘 that defines the range of good property values. At each iteration, the method selects a molecule 𝑥 𝑟,𝑡 to query, which the chemist evaluates with feedback 𝑦. The method then adapts 𝑆 𝑟,𝑡 (𝑥) based on the feedback by estimating the parameters of 𝜙 𝑟,𝑡,𝑘 to match the chemist's underlying goal.