2-AMINO-4-QUINAZOLINONES AS LXR NUCLEAR RECEPTOR BINDING COMPOUNDS

Details for Australian Patent Application No. 2003296861 (hide)

Owner LION BIOSCIENCE AG

Inventors HERMANN, Kristina; DEUSCHLE, Ulrich; LOEBBERT, Ralph; BLUME, Beatrix; KOEGL, Manfred; KREMOSER, Claus; KOBER, Ingo; BAUER, Ulrike

Pub. Number AU-A-2003296861

PCT Number PCT/EP2003/0070

PCT Pub. Number WO2004/024162

Priority 02020255.2 10.09.02 EP

Filing date 2 July 2003

Wipo publication date 30 April 2004

International Classifications

A61K 031/517 - ortho- or peri-condensed with carbocyclic ring systems, e.g. quinazoline, perimidine

C07D 403/04 Heterocyclic compounds containing two or more hetero rings, having nitrogen atoms as the only ring hetero atoms, not provided for by group

A61P 003/06 Drugs for disorders of the metabolism

C07D 239/95 Heterocyclic compounds containing 1,3-diazine or hydrogenated 1,3-diazine rings

C07D 401/12 Heterocyclic compounds containing two or more hetero rings

Event Publications

6 May 2004 Complete Application Filed

  Priority application(s): 02020255.2 10.09.02 EP

20 May 2004 Application Open to Public Inspection

  Published as AU-A-2003296861

21 July 2005 Application Lapsed, Refused Or Withdrawn, Patent Ceased or Expired

  This application lapsed under section 142(2)(f)/See Reg. 8.3(3). Examination has not yet been requested or directed for this application. Note that applications or patents shown as lapsed or ceased may be restored at a later date.

Legal

The information provided by the Site not in the nature of legal or other professional advice. The information provided by the Site is derived from third parties and may contain errors. You must make your own enquiries and seek independent advice from the relevant industry professionals before acting or relying on any information contained herein. Check the above data against the Australian Patent Office AUSPAT database.

Next and Previous Patents/Applications

2003296862-SELF-GENERATING FOAMED DRILLING FLUIDS

2003296860-EXTRACTING INFORMATION FROM INPUT DATA USING A SEMANTIC COGNITION NETWORK