Title |
Drug design for ever, from hype to hope
|
---|---|
Published in |
Perspectives in Drug Discovery and Design, January 2012
|
DOI | 10.1007/s10822-011-9519-9 |
Pubmed ID | |
Authors |
G. Seddon, V. Lounnas, R. McGuire, T. van den Bergh, R. P. Bywater, L. Oliveira, G. Vriend |
Abstract |
In its first 25 years JCAMD has been disseminating a large number of techniques aimed at finding better medicines faster. These include genetic algorithms, COMFA, QSAR, structure based techniques, homology modelling, high throughput screening, combichem, and dozens more that were a hype in their time and that now are just a useful addition to the drug-designers toolbox. Despite massive efforts throughout academic and industrial drug design research departments, the number of FDA-approved new molecular entities per year stagnates, and the pharmaceutical industry is reorganising accordingly. The recent spate of industrial consolidations and the concomitant move towards outsourcing of research activities requires better integration of all activities along the chain from bench to bedside. The next 25 years will undoubtedly show a series of translational science activities that are aimed at a better communication between all parties involved, from quantum chemistry to bedside and from academia to industry. This will above all include understanding the underlying biological problem and optimal use of all available data. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 2% |
Germany | 3 | 2% |
Brazil | 2 | 1% |
Colombia | 1 | <1% |
Portugal | 1 | <1% |
Italy | 1 | <1% |
Bulgaria | 1 | <1% |
Malaysia | 1 | <1% |
Czechia | 1 | <1% |
Other | 3 | 2% |
Unknown | 158 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 38 | 22% |
Student > Ph. D. Student | 36 | 20% |
Student > Master | 23 | 13% |
Student > Bachelor | 14 | 8% |
Professor | 10 | 6% |
Other | 32 | 18% |
Unknown | 23 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 49 | 28% |
Chemistry | 43 | 24% |
Biochemistry, Genetics and Molecular Biology | 14 | 8% |
Computer Science | 10 | 6% |
Pharmacology, Toxicology and Pharmaceutical Science | 9 | 5% |
Other | 25 | 14% |
Unknown | 26 | 15% |