title: Validation of a predictive modeling approach to demonstrate the relative efficacy of three different schedules of the AKT inhibitor AZD5363.
abstract: OBJECTIVE
  Intermittent dosing of inhibitors of the PI3K/AKT/mTOR network offers the potential to maximize the therapeutic margin. Here, we validate a predictive modeling approach to establish the relative efficacy of continuous and two intermittent dosing schedules of the AKT inhibitor AZD5363.
  
  
  METHODS
  A mathematical model of pharmacokinetics, pharmacodynamics and anti-tumor effect was constructed based upon experimental data from dosing regimens that give constant and transient inhibition of the AKT pathway.
  
  
  RESULTS
  Continuous and intermittent dosing of AZD5363 inhibited growth of BT474c xenografts and caused dose- and time-dependent inhibition of AKT substrate phosphorylation. Both dosing schedules inhibited proliferation, but a higher intermittent dose also induced apoptosis. The mathematical model described this pharmacodynamic and efficacy data well, for both monotherapy and combination dosing with docetaxel, and predicted that equivalent efficacy could be achieved at 1.3- and 1.7× continuous dose when AZD5363 was dosed intermittently for 4 and 2 days per week, respectively. These predictions were confirmed in two independent xenograft models. Moreover, the model also correctly predicted the relative efficacy of three different sequences of intermittent dosing of AZD5363 with docetaxel.
  
  
  CONCLUSIONS
  Equivalent anti-tumor activity to continuous dosing can be achieved at modestly increased intermittent doses of AZD5363. These intermittent dosing regimens may potentially overcome tolerability issues seen with continuous dosing and enable greater flexibility of dosing schedule in combination with other agents, including chemotherapy.
authors.affiliation: Oncology iMED, AstraZeneca, Alderley Park, Mereside, Macclesfield, Cheshire, SK10 4TG, UK, james.yates@astrazeneca.com.
authors.forename: James W T
authors.initials: JW
authors.lastname: Yates
authors.forename: Phillippa
authors.initials: P
authors.lastname: Dudley
authors.forename: Jane
authors.initials: J
authors.lastname: Cheng
authors.forename: Celina
authors.initials: C
authors.lastname: D'Cruz
authors.forename: Barry R
authors.initials: BR
authors.lastname: Davies
mesh_terms: D000818:Animals; D000970:Antineoplastic Agents / Q000008:administration & dosage* / Q000493:pharmacokinetics / Q000494:pharmacology; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000494:pharmacology; D017209:Apoptosis; D054316:Biomarkers, Pharmacological / Q000378:metabolism; D045744:Cell Line, Tumor; D000077143:Docetaxel; D004334:Drug Administration Schedule; D004347:Drug Interactions; D005260:Female; D064593:Heterografts; D008819:Mice, Nude; D008954:Models, Biological; D009368:Neoplasm Transplantation; D051057:Proto-Oncogene Proteins c-akt / Q000037:antagonists & inhibitors*; D011743:Pyrimidines / Q000008:administration & dosage* / Q000493:pharmacokinetics / Q000494:pharmacology; D011758:Pyrroles / Q000008:administration & dosage* / Q000493:pharmacokinetics / Q000494:pharmacology; D043823:Taxoids / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000494:pharmacology; D047368:Tumor Burden / Q000187:drug effects
chemical_list: D000970:Antineoplastic Agents; D054316:Biomarkers, Pharmacological; D011743:Pyrimidines; D011758:Pyrroles; D043823:Taxoids; D000077143:Docetaxel; D051057:Proto-Oncogene Proteins c-akt; C575618:capivasertib