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AI comes to lead optimization: medicinal chemistry in all disease areas can be accelerated by exploiting our pre-competitive knowledge in an unbiased way.

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We have applied the two most commonly used methods for automatic matched pair identification, obtained the optimum settings, and discovered that the two methods are synergistic. A turbocharging approach to matched pair analysis is advocated in which a first round (a conservative categorical approach that uses an analogy with coin flips, heads corresponding to an increase in a measured property, tails to a decrease, and a biased coin to a structural change that reliably causes a change in that property) provides the settings for a second round (which uses the magnitude of the change in properties). Increased chemical specificity allows reliable knowledge to be extracted from smaller sets of pairs, and an assay-specific upper limit can be placed on the number of pairs required before adequate sampling of variability has been achieved.