
The need to early predict the possible failure of a drug candidate is becoming an absolute requirement in the drug discovery process. For this reason, from the initial phases of lead development, great attention is paid to the ADMET characteristics of the compounds. In this context, the recent discovery that hitting some well-identified macromolecular targets can induce undesired side effects has led drug designers to apply some classical in silico technologies to the goal of avoiding the interaction of lead candidates with such antitargets.:
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
