PubMed Health⌕ Search

Biomedical subjects

Jeffrey R Haskins

Publications and source records attributed to Jeffrey R Haskins.

5 recordsLinked to original sources

In vitro cytotoxicity assessment.

The most frequent reason cited for withdrawal of an approved drug is toxicity, yet no simple solution exists to adequately predict such adverse effects. Compound prioritization and optimization during in vitro screening cascades need to be based on confidence, not only in efficacy and bioavailability, but also in safety. A wider number and diversity of potential molecular and cellular effects of compound interactions might affect safety than might affect efficacy or bioavailability. Accordingly, cytotoxicity assessment is less specific, more multiparametric, and extrapolatable with less certainty, unless there are specific safety signals indicated by the chemical structure or by precedents. Cytotoxicity assessments have been limited by their inability to measure multiple, mechanistic parameters that capture a wide spectrum of potential cytopathological changes. Assays with multiple parameters for key, multiple, and different features, such as in high content screening (HCS), are more predictive because they cover a wider spectrum of effects. Assays need to be applied to a large set of marketed drugs that produce toxicity by numerous and different mechanisms for assessment of correlation with human toxicity. This will enable determination of the concordance between in vitro and in vivo results. Multiparametric, live cell, prelethal cytotoxic HCS assays for assessing the potential of compounds for causing human toxicity address some of the limitations of traditional in vitro methods. Assays of this class were used to screen a library of drugs with varying degrees of toxicity and it was found that the sensitivity of the assays was 87%, whereas assay specificity was more than 90%, thereby minimizing false positives.

Cell Death↗

Characteristics and value of directed algorithms in high content screening.

High content screening requires image processing algorithms that can accurately and robustly analyze large image numbers without requiring human intervention. Thus, a suite of algorithms that are directed by an understanding of the biology being studied was developed for the optimized automated acquisition and quantitation of cellular images. Two categories of directed algorithms were developed: Developer Tools for assay development and Specific Algorithms for turnkey screening of specific biological situations. The same basic sequence of analysis steps are used in these directed algorithms: 1. Primary object identification. 2. Measurement of primary object properties. 3. Identification and measurements of associated targets. 4. Analysis of raw measurements for specific biological problems. The detailed application of these steps is guided by the biology being studied and the expected phenotypic changes. Most cell biological problems to be analyzed using high content screening can be categorized by either the phenotype of the problem or labeling pattern, or by a standard biological response behavior of the cells. This enables application of directed algorithms optimized for these categories. Examples of the use of directed algorithms for specific categories are discussed, as well as the detailed analysis steps for a specific directed algorithm.

Algorithms↗

Improving high-content-screening assay performance by using division-arrested cells.

As cell-based assays are used more commonly in robotic high-throughput compound screening, cells themselves have become critical reagents. Thus, it has become essential to produce cell reagents with high consistency and quality. We experimented with cells division-arrested with low-level mitomycin C treatment and demonstrate that they perform with better consistency than non-division-arrested counterparts in high-content screening imaging assays. We propose that for cell-based screening, it is possible to uncouple the cell production process from the screening process. Cells can be produced en masse, treated to become irreversibly division-arrested, and cryopreserved. These "ready-to-use" reagents can be thawed, plated, and used in screening with improved consistency and convenience.

Antibiotics, Antineoplastic↗

Advances in high content screening for drug discovery.

Cell-based target validation, secondary screening, lead optimization, and structure-activity relationships have been recast with the advent of HCS. Prior to HCS, a computational approach to the characterization of the functions of specific target proteins and other cellular constituents, along with whole-cell functions employing fluorescence cell-based assays and microscopy, required extensive interaction among the researcher, instrumentation, and software tools. Early HCS platforms were instrument-centric and addressed the need to interface fully automated fluorescence microscopy, plate-handling automation, and seamless image analysis. HCS has since evolved into an integrated solution for accelerated drug discovery by encompassing the workflow components of assay and reagent design, robust instrumentation for automated fixed-end-point and live cell kinetic analysis, generalized and specific BioApplication software (Cellomics, Pittsburgh, PA) modules that produce information on drug responses from cell image data, and informatics/bioinformatics solutions that build knowledge from this information while providing a means to globalize HCS throughout an entire organization. This review communicates how these recent advances are incorporated into the drug discovery workflow by presenting a real-world use case.

Drug Design↗