A Dynamic Supply-Demand Model for Electricity Prices

<p>We introduce a new model for electricity prices, based on the principle of supply and demand equilibrium. The model includes latent supply and demand curves, which may vary over time, and assumes that observed price/quantity pairs are obtained as the intersection of the two curves, for any particular point in time. Although the model is highly nonlinear, we explain how the particle filter can be used for model parameter estimation, and to carry out residual analysis. We apply the model in a study of Californian wholesale electricity prices over a three-year period including the crisis period during the year 2000. The residuals indicate that inflated prices do not appear to be attributable to natural random variation, temperature effects, natural gas supply effects, or plant stoppages. However, without ruling out other factors, we are unable to argue whether or not market manipulation by suppliers played a role during the crisis period.</p

Circulating tumor cells: application as a biomarker for molecular characterization and predictor of survival in an all-comer solid tumor phase I clinical study.

Clinical development of cancer drugs has a low success rate. Prognostic and predictive biomarkers using minimally invasive approaches hold promise for increasing the probability of success by enabling disease characterization, patient selection and early detection of drug treatment effect. Enumeration and molecular characterization of circulating tumor cells (CTC) may address some of these needs, and thus were evaluated for utility in a Phase I solid tumor clinical study.Blood samples for CTC analysis were obtained from 24 cancer patients in a multi-center all-comer Phase I study of MEDI-575, a novel anti-PDGFRα antibody. Samples were taken at screening and analyzed for enumeration of CTC using the CellSearch(®) platform and for molecular characterization using a novel quantitative RT-PCR assay.Fifty-nine percent of the patients showed at least 1 CTC per 7.5 ml of blood at baseline. Progression-free survival (PFS) and overall survival (OS) of patients with 0 CTCs at baseline were longer than PFS and Os for patients with 1-3 and >3 CTCs (8.8 versus 1.4 and 1.3 months PFS, P = 0.02; 9.0 vs 7.4 and 3.5 months OS, P = 0.20, respectively). Patients with 0 CTC showed a greater percentage of stable disease than the other 2 groups with 1-3 and >3 CTCs (57% vs 29% and 0%). The multimarker qRT-PCR method detected CTC in 40% of the patients, and 80% of these patients were positive for pre-selected drug target genes.CTC enumeration of patients in an all-comer study is feasible and may allow for patient stratification for PFS and Os to evaluate the clinical response of investigational agents. Gene expression profiling of isolated CTC may provide a means for molecular characterization of selected tumor targets

Circulating tumor cell detection and patient stay on treatment time.

<p>Circulating tumor cell detection and patient stay on treatment time.</p

Kaplan-Meier estimates of probabilities of overall survival (A) and progression-free survival (B) of patients with respect to frequency of CTCs before initiation of therapy.

<p>The red, green, and blue lines represent patients with no CTC, 1-3 CTCs, and above 3 CTCs, respectively.</p

Circulating tumor cell number and disease outcome.

<p>Circulating tumor cell number and disease outcome.</p