cytotoxicity indices, cardiac liability reflected through adrenoreceptor or ion channel activity, etc. In Fig. 2.15, a whole matrix of data is supplied to help drive the decision-making process.

• Target potency (juM): activity from the HTS assay

• Target selectivity: search of all the screening databases, both against other targets HTS and lower-throughput screening, to check whether the compound was found to be active against other targets. The number indicates the number of positive results found.

• Human liver enzyme inhibition (fjM): the activity in a standard cell-based toxicity model.

• Mutagenesis (juM): the activity in an in vitro model of mutagenesis

• Cardiac Liability: activity in essential cardiac ion channels that would cause an adverse side effect in humans.

• Drug-like properties: assessing the compound in a range of drug-like in silico models.

• Chemical tractability: a more subjective flag that is based on a medicinal chemist's view on whether this is a good start for a medicinal chemistry program.

• Liability or disadvantage: this is color coded, red = high, yellow = medium, and green = low.

In this example, if the only datum available to the medicinal chemist was the potency of a compound, BMS1 would be the highest priority. BMS5 has the cleanest profile, and this chemical series was the preferred candidate for progression, although it was 10-fold less potent than BMS1. Activity in these liability assays will not stop the progression of a compound, but it helps in understanding how to drive the medicinal chemistry forward. This is the point at which the initial HTS process has ended. The decisions from this point are around compound optimization and continued target validation. HTS approaches and technology are back into play if the project requires further chemotypes.

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