Ivelina Gueorguieva, Ann L. Cleverly and Michael Lahn
Lilly Research Laboratories, Sunninghill Road, Windlesham, Surrey, UK
Objectives: To prospectively identify a safe therapeutic window, based on a PK/PD model, for administration of the novel oral TGF-b inhibitor LY2157299 monohydrate. This PK/PD model was updated after completion of each cohort during the First-in-Human Dose (FHD) study. Simulations of population plasma exposures and biomarker responses in tumor were performed, and optimal sampling windows for future trials in glioblastoma and other cancer populations were calculated. Exploratory Bayesian inferences with exposure, biomarker and tumor size change were also carried out.
Methods: The PK/PD model was updated after completion of each cohort during the FHD study. The flexible design, with dose escalation starting at a total daily dose of 40 mg and increasing up to (potentially) 360 mg, allowed continuous assessment of PK variability by recruiting the required number of patients in each cohort. NLME analysis, with exposure, target-linked biomarker and tumor size under Bayesian inference, were performed in WinBUGS [1] with informative priors on biomarker and vague priors on exposure and tumor size. Component WBDiff, with “Adjust” procedure was used.
Results: During the course of the FHD study no medically significant safety issues were observed and no dose limiting toxicities were established. Based on 30% inhibition of pSMAD [2], biologically effective exposures were anticipated to be reached from Cohort 3 (160 mg) onwards. Additionally, doses above 360 mg/day were predicted to have an unacceptable risk of an individual patient exceeding a potentially toxic exposure. Therapeutic widow was identified to be between 160 and 300mg/day [3]. We predicted, based on clinical exposure, that doses above 300 mg/day to have an unacceptable risk of an individual patient exceeding a potentially toxic exposure.
Conclusions: A therapeutic window for the clinical investigation of LY2157299 in cancer patients was defined using a targeted PK/PD approach, which integrated translational biomarkers and preclinical toxicity. Using modelling can help define a therapeutic window for other TGF-beta inhibitors. Further, integrating exposure, biomarker and tumor size change in the same model, using Bayesian inference, can provide insights for future drug development in Phase 2 and 3 studies.
References:
[1] Lunn D.J., Best N., Thomas A., Wakefield J. and Spiegelhalter D.. Bayesian analysis of population PK/PD models: general concepts and software. J. Pharmacokin. Pharmacodyn. 29 (3): 271-307.
[2] Bueno L, deAlwis DP, Pitou C, et al: Semi-mechanistic modeling of the tumor growth inhibitory effects of LY2157299, a new type I receptor TGF-β kinase antagonist, in mice. Eur J Cancer 44:142-150, 2008.
[3] Gueorguieva I, AL Cleverly, A Stauber, NS Pillay, J Rodon, C Miles, JM Yingling and M Lahn: Defining a therapeutic window for the novel TGF-β inhibitor LY2157299 monohydrate based on a pharmacokinetic/pharmacodynamic (PK/PD) model, Journal of Clinical Oncology, submitted.
Reference: PAGE 21 () Abstr 2512 [www.page-meeting.org/?abstract=2512]
Poster: Oncology