An Adaptive Study to Determine the Optimal Dose of the Tablet Formulation of the PARP Inhibitor Olaparib

BACKGROUND: Olaparib is poorly soluble, requiring advanced drug delivery technologies for adequate bioavailability. Sixteen capsules/day are required for the approved 400 mg twice-daily dose; a tablet formulation was developed to reduce pill burden. This clinical trial evaluated the optimal dose and administration schedule of the tablet formulation. PATIENTS AND METHODS: Two stages of sequentially enrolled cohorts: stage 1, pharmacokinetic properties of tablet and capsule formulations were compared in patients with advanced solid tumours; stage 2, tablet dose escalation with expansion cohorts at doses/schedules of interest in patients with solid tumours and BRCAm breast/ovarian cancers. RESULTS: Olaparib 200 mg tablets displayed similar Cmax,ss, but lower AUCss and Cmin,ss than 400 mg capsules. Following multiple dosing, steady-state exposure with tablets ≥300 mg matched or exceeded that of 400 mg capsules. After dose escalation, while 400 mg twice daily was the tablet maximum tolerated dose based on haematological toxicity, 65 % of patients in the randomized expansion phase eventually required dose reduction to 300 mg. Intermittent tablet administration did not significantly improve tolerability. Tumour shrinkage was similar for 300 and 400 mg tablet and 400 mg capsule cohorts. CONCLUSIONS: The recommended monotherapy dose of olaparib tablet for Phase III trials was 300 mg twice daily, simplifying drug administration from 16 capsules to four tablets per day. CLINICAL TRIAL NUMBER: NCT00777582 (ClinicalTrials.gov

Combining Exploration and Exploitation in Active Learning

This thesis investigates the active learning in the presence of model bias. State of the art approaches advocate combining exploration and exploitation in active learning. However, they suffer from premature exploitation or unnecessary exploration in the later stages of learning. We propose to combine exploration and exploitation in active learning by discarding instances outside a sampling window that is centered around the estimated decision boundary and uniformly draw sample from this window. Initially the window spans the entire feature space and is gradually constricted, where the rate of constriction models the exploration-exploitation tradeoff. The desired effect of this approach (CExp) is that we get an increasing sampling density in informative regions as active learning progresses, resulting in a continuous and natural transition from exploration to exploitation, limiting both premature exploitation and unnecessary exploration. We show that our approach outperforms state of the art on real world multiclass datasets. We also extend our approach to spatial mapping problems where the standard active learning assumption of uniform costs is violated. We show that we can take advantage of \emph{spatial continuity} in the data by geographically partitioning the instances in the sampling window and choosing a single partition (region) for sampling, as opposed to taking a random sample from the entire window, resulting in a novel spatial active learning algorithm that combines exploration and exploitation. We demonstrate that our approach (CExp-Spatial) can generate cost-effective sampling trajectories over baseline sampling methods. Finally, we present the real world problem of mapping benthic habitats where bathymetry derived features are typically not strong enough to discriminate the fine details between classes identified from high-resolution imagery, increasing the possiblity of model bias in active learning. We demonstrate, under such conditions, that CExp outperforms state of the art and that CExp-Spatial can generate more cost-effective sampling trajectories for an Autonomous Underwater Vehicle in contrast to baseline sampling strategies

FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. Results:Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95 confidence interval=1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. Conclusion:Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2. © 2014 Cancer Research UK

HE4 and CA125 as a diagnostic test in ovarian cancer: prospective validation of the Risk of Ovarian Malignancy Algorithm

BACKGROUND: Recently, a Risk of Ovarian Malignancy Algorithm (ROMA) utilising human epididymis secretory protein 4 (HE4) and CA125 successfully classified patients as presenting a high or low risk for epithelial ovarian cancer (EOC). We validated this algorithm in an independent prospective study. METHODS: Women with a pelvic mass, who were scheduled to have surgery, were enrolled in a prospective study. Preoperative serum levels of HE4 and CA125 were measured in 389 patients. The performance of each of the markers, as well as that of ROMA, was analysed. RESULTS: When all malignant tumours were included, ROMA (receiver operator characteristic (ROC)-area under curve (AUC) = 0.898) and HE4 (ROC-AUC) = 0.857) did not perform significantly better than CA125 alone (ROC-AUC = 0.877). Using a cutoff for ROMA of 12.5% for pre-menopausal patients, the test had a sensitivity of 67.5% and a specificity of 87.9%. With a cutoff of 14.4% for post-menopausal patients, the test had a sensitivity of 90.8% and a specificity of 66.3%. For EOC vs benign disease, the ROC-AUC of ROMA increased to 0.913 and for invasive EOC vs benign disease to 0.957. CONCLUSION: This independent validation study demonstrated similar performance indices to those recently published. However, in this study, HE4 and ROMA did not increase the detection of malignant disease compared with CA125 alone. Although the initial reports were promising, measurement of HE4 serum levels does not contribute to the diagnosis of ovarian cancer. British Journal of Cancer (2011) 104, 863-870. doi:10.1038/sj.bjc.6606092 www.bjcancer.com Published online 8 February 2011 (C) 2011 Cancer Research U