Abstract
Bioassays are often used in tiered screening systems to detect potential products, such as crop protection products. Often these assays are not replicated. The ultimate products of these bioassays are decisions, with biologically “active” compounds advanced to the next level of screening. Activity is determined by the response of the test organisms (e.g., weeds, insects or fungi) to each compound. The reproducibility of the bioassay is crucial. There are two types of possible errors in screening, false positives and false negatives. The quality of the decisions based upon these bioassays can be monitored through time using controls. This paper will discuss Decision Quality Metrics, quality control metrics customized for bioassays used to select the most “active” compound. These metrics monitor the reproducibility of the screens, translating bioassays responses to controls into potential impact on decision making.
Keywords
Bioassays, high throughput screening, quality management, decision quality
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Ferry, Nancy and Letsinger, William
(2006).
"DECISION QUALITY METRICS – A TOOL FOR MANAGING QUALITY OF REPEATED BIOASSAYS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1127
DECISION QUALITY METRICS – A TOOL FOR MANAGING QUALITY OF REPEATED BIOASSAYS
Bioassays are often used in tiered screening systems to detect potential products, such as crop protection products. Often these assays are not replicated. The ultimate products of these bioassays are decisions, with biologically “active” compounds advanced to the next level of screening. Activity is determined by the response of the test organisms (e.g., weeds, insects or fungi) to each compound. The reproducibility of the bioassay is crucial. There are two types of possible errors in screening, false positives and false negatives. The quality of the decisions based upon these bioassays can be monitored through time using controls. This paper will discuss Decision Quality Metrics, quality control metrics customized for bioassays used to select the most “active” compound. These metrics monitor the reproducibility of the screens, translating bioassays responses to controls into potential impact on decision making.
