In silico ADME in drug design – enhancing the impact

Each year the pharmaceutical industry makes thousands of compounds, many of which do not meet the desired efficacy or pharmacokinetic properties, describing the absorption, distribution, metabolism and excretion ( ADME) behavior. Parameters such as lipophilicity, solubility and metabolic stability can be measured in high throughput in vitro assays. However, a compound needs to be synthesized in order to be tested. In silicomodels for these endpoints exist, although with varying quality. Such models can be used before synthesis and, together with a potencyestimation, influence the decision to make a compound. In practice, it appears that often only one or two predicted properties are considered prior to synthesis, usually including a prediction of lipophilicity. While it is important to use all information when deciding which compound to make, it is somewhat challenging to combine multiple predictions unambiguously. This work investigates the possibility of combining in silico ADMEpredictions to define the minimum required potencyfor a specified human dose with sufficient confidence. Using a set of drug discovery compounds,in silicopredictions were utilized to compare the relative ranking based on minimum potencycalculation with the outcomes from the selection of lead compounds. The approach was also tested on a set of marketed drugs and the influence of the input parameters investigated.