Sensitivity analysis and other improvements to tailored combinatorial library design

'Tailoring" combinatorial libraries was developed several years ago as a ve ry general and intuitive method to design diverse compound collections whil e controlling the profile of other pharmaceutically relevant properties. Th e candidate substituents were assigned to "categorical bins" according to t heir properties, and successive steps of D-optimal design were performed to generate diverse substituent sets consistent with required membership quot as from each bin. This serial algorithm was expedient to implement from exi sting D-optimal design codes, but was order-dependent and did not generally locate the very best possible design. A new "parallel" Fedorov search algo rithm has now been implemented that can find the most diverse property-tail ored design. An ambiguous mass penalty has been added, whereby most duplica te masses can be eliminated with little loss of library diversity. Sensitiv ity analysis has also been added to quantitatively explore the diversity tr ade-offs due to increasing or decreasing each specific kind of bias.