Name
Abstract | ||
|---|---|---|
Both society and industry are interested in increasing the safety of pharmaceuticals. Potentially dangerous compounds could be filtered out at early stages of R&D by computer prediction of biological activity and ADMET characteristics. Accuracy of such predictions strongly depends on the quality & quantity of information contained in a training set. Suggestion that some relevant chemical information can be added to such training sets without disclosing chemical structures was generated at the recent ACS Symposium. We presented arguments that such safety exchange of relevant chemical information is impossible. Any relevant information about chemical structures can be used for search of either a particular compound itself or its close analogues. Risk of identifying such structures is enough to prevent pharma industry from relevant chemical information exchange. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/s10822-005-9014-2 | Journal of computer-aided molecular design |
Keywords | Field | DocType |
biological activity spectra,computer prediction,PASS,relevant chemical information,reverse engineering,safety exchange,structure disclosing | Training set,Data science,Data mining,Reverse engineering,Computational chemistry,Information exchange,Chemistry | Journal |
Volume | Issue | ISSN |
19 | 9-10 | 0920-654X |
Citations | PageRank | References |
4 | 0.65 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dmitry Filimonov | 1 | 53 | 7.45 |
| Vladimir Poroikov | 2 | 128 | 17.98 |