Compound ranking based on a new mathematical measure of effectiveness using time course data from cell-based assays

Model-based assessment of combination therapies - ranking of radiosensitizing agents in oncology

BACKGROUND

To increase the chances of finding efficacious anticancer drugs, improve development times and reduce costs, it is of interest to rank test compounds based on their potential for human use as early as possible in the drug development process. In this paper, we present a method for ranking radiosensitizers using preclinical data.

METHODS

We used data from three xenograft mice studies to calibrate a model that accounts for radiation treatment combined with radiosensitizers. A nonlinear mixed effects approach was utilized where between-subject variability and inter-study variability were considered. Using the calibrated model, we ranked three different Ataxia telangiectasia-mutated inhibitors in terms of anticancer activity. The ranking was based on the Tumor Static Exposure (TSE) concept and primarily illustrated through TSE-curves.

RESULTS

The model described data well and the predicted number of eradicated tumors was in good agreement with experimental data. The efficacy of the radiosensitizers was evaluated for the median individual and the 95% population percentile. Simulations predicted that a total dose of 220 Gy (5 radiation sessions a week for 6 weeks) was required for 95% of tumors to be eradicated when radiation was given alone. When radiation was combined with doses that achieved at least 8 [Formula: see text] of each radiosensitizer in mouse blood, it was predicted that the radiation dose could be decreased to 50, 65, and 100 Gy, respectively, while maintaining 95% eradication.

CONCLUSIONS

A simulation-based method for calculating TSE-curves was developed, which provides more accurate predictions of tumor eradication than earlier, analytically derived, TSE-curves. The tool we present can potentially be used for radiosensitizer selection before proceeding to subsequent phases of the drug discovery and development process.

Eco-toxicological effect of a commercial dye Rhodamine B on freshwater microalgae Chlorella vulgaris

In this study, the acute toxicity effects of a fluorescent xanthene dye, Rhodamine B (RhB), widely used in textile, paper, and leather industries was investigated on a freshwater microalgae Chlorella vulgaris. The acute toxicity of RhB on C. vulgaris was determined by examining the growth, cell morphology, pigment production, protein content, and the activities of oxidative stress enzymes. Based on the results of the toxicity study of 24-96 h, the median inhibitory concentration (IC₅₀) values ranged from 69.94 to 31.29 mg L^-1. The growth of C. vulgaris was conspicuously inhibited by RhB exposure, and the cell surfaces appeared to be seriously shrunk in SEM analysis. The growth of C. vulgaris was hindered after exposure to graded concentrations (10-50 mg L^-1) of RhB. A significant reduction in growth rate, pigment synthesis (chlorophyll a, chlorophyll b, and carotenoid), and protein content was recorded in a dose-dependent manner. After 96 h exposure of C. vulgaris to 50 mg L^-1 RhB, chlorophyll a, chlorophyll b, carotenoids, and protein contents were reduced by 71.59, 74.90, 65.84, and 74.20%, respectively. The activities of the antioxidant enzymes peroxidase (POD), and catalase (CAT) also increased markedly in the presence of RhB. A notable effect was observed on oxidative enzymes catalase and peroxidase, indicating that oxidative stress may be the primary factor in the inhibition of growth and pigment synthesis. Consequently, the experimental acute toxicity data were compared to the QSAR prediction made by the ECOSAR programme. Results showed that the experimental acute toxicity values were 67.74-fold lower than the ECOSAR predicted values. The study provides convincing evidence for the metabolic disruption in the ubiquitous microalgae C. vulgaris due to the RhB dye toxicity.

In vitro cytotoxicity and docking study of novel symmetric and asymmetric dihydropyridines and pyridines as EGFR tyrosine kinase inhibitors

Quinolines have a weighty effect as anticancer agents and 1,4-DHPs have demonstrated efficacy as anticancer agents in several studies, as well. New hybrid models of symmetric and asymmetric 1,4-DHPs and pyridines linked at C₃ of 2-chloroquinoline as a new anticancer scaffold, were designed and synthesized. Hantszch 1,4-DHPs method was adopted for chemical synthesis. MTT assay was performed for the evaluation of cytotoxicity, and EGFR tyrosine kinase assay was performed to investigate binding to our selected compounds, measured by ELISA. The IC₅₀ expressed in µM values revealed that compounds 4a,b, and 5i,k showed the best results against the tested four cell lines than the reference drug 5-Flurouuracil. Compound 5k displayed the most potent cytotoxic activity with IC₅₀  values in the low µM range (12.03 ± 1.51: 20.09 ± 2.16 µM), compared with 5-Fu IC₅₀ range (40.74 ± 2.46: 63.81 ± 2.69 µM). The incorporation of 2-chloroquinoline at C₃ to C₄ of 1,4-DHP could be proposed as an anticancer scaffold rather than its analogous pyridines. Ester fragments connected to 1,4-DHPs ring as a lipophilic part are essential for anticancer activity. The chirality at C₄ improved the anticancer activity. The hydrogen and halogen bond facilitated protein-ligand binding mode and affinity.

Measuring and Statistically Testing the Size of the Effect of a Chemical Compound on a Continuous In-Vitro Pharmacological Response Through a New Statistical Model of Response Detection Limit

Biomolecular screening research frequently searches for the chemical compounds that are most likely to make a biochemical or cell-based assay system produce a strong continuous response. Several doses are tested with each compound and it is assumed that, if there is a dose-response relationship, the relationship follows a monotonic curve, usually a version of the median-effect equation. However, the null hypothesis of no relationship cannot be statistically tested using this equation. We used a linearized version of this equation to define a measure of pharmacological effect size, and use this measure to rank the investigated compounds in order of their overall capability to produce strong responses. The null hypothesis that none of the examined doses of a particular compound produced a strong response can be tested with this approach. The proposed approach is based on a new statistical model of the important concept of response detection limit, a concept that is usually neglected in the analysis of dose-response data with continuous responses. The methodology is illustrated with data from a study searching for compounds that neutralize the infection by a human immunodeficiency virus of brain glioblastoma cells.

The University of Kansas High-Throughput Screening laboratory. Part I: meeting drug-discovery needs in the heartland of America with entrepreneurial flair

The University of Kansas High-Throughput Screening (KU HTS) core is a state-of-the-art drug-discovery facility with an entrepreneurial open-service policy, which provides centralized resources supporting public- and private-sector research initiatives. The KU HTS core applies pharmaceutical industry project-management principles in an academic setting by bringing together multidisciplinary teams to fill critical scientific and technology gaps, using an experienced team of industry-trained researchers and project managers. The KU HTS proactively engages in supporting grant applications for extramural funding, intellectual-property management and technology transfer. The KU HTS staff further provides educational opportunities for the KU faculty and students to learn cutting-edge technologies in drug-discovery platforms through seminars, workshops, internships and course teaching. This is the first instalment of a two-part contribution from the KU HTS laboratory.