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S S Herrick

Publications and source records attributed to S S Herrick.

8 recordsLinked to original sources
PubMed1979

NCTR computer systems designed for toxicologic experimentation. V. Post-experiment information system.

The Post-Experiment Information System (PEIS) is an automated data collection and reporting system composed of three specialized subsystems: Pathology, Chemistry and Microbiology. These subsystems function either independently or collectively to construct and maintain a comprehensive data base of all experimental values derived from, or associated with, an animal carcass. All data are retrievable by the unique Carcass Identification (CID) number assigned at death, which is the correlative of the Unique Identification Number (UIN) assigned to the animal at birth and used throughout its lifespan. Elements processed under the PEIS include gross and microscopic pathological observations, organ weights, hematologic data, chemical data, and microbiological analyses. The ability of the system to integrate the post-experiment data with the information collected on an animal from birth (BIS) and during the experiment (EIS) provides a complete animal history to the Principal Investigator or other requestor.

Animals↗
PubMed1977

Computer-assisted collection and analysis of pathology data.

At the National Center for Toxicological Research, long-term experiments with mice requiring the collection, storage, retieval, and analysis of an inordinate amount of data necessitated the development of an automated pathology information system. The system included automatic collection of mouse body and organ weights and hematologic findings; the use of mark-sensitive forms for the collection of gross and microscopic findings; and the use of computers for the storage, retrieval, and analysis of pathology data.

Animals↗
PubMed1976

Research data integrity: a result of an integrated information system.

The toxicologic problems of today frequently require long-term, multidisciplinary experimentation involving large numbers of animals. In order to provide the extensive safety evaluation necessary to produce data that can be reasonably extrapolated to humans, automated research support systems have transcended the position of useful tools and have become an integral part of the total design of experimental protocols. For an automated information system to fully represent the reality of the experiment, it must be able to assure integrity, as well as provide for the storage, calculation, and retrieval of data values of the quality and quantity necessary for fulfilling protocol requirements. Guarantees against error and loss of data, in addition to flexibility and easy access, must be an inherent part of the system if the acceptance and condifence of the investigator are to be obtained. This paper discusses the criteria, philosophies, and benefits of integrated data systems that ensure integrity of toxicologic research support.

Computers↗
PubMedDate not supplied

NCTR computer systems designed for toxicologic experimentation. I. Overview.

Established in 1971 by the Food and Drug Administration (FDA) and the Environmental Protection Agency (EPA), the National Center for Toxicological Research is committed to the study of long-term, low-dose effects of potentially toxic substances, including carcinogens. The Scientific Information Systems Division (SISD) facility provides logistic support for complex experiments involving large numbers of test animals. Animal population at the Center, including the breeding colony and animals on experiment, can be as high as 80,000. Each animal must be accounted for, fed and watered under strict control, and continually observed. From birth to final examination, an individual animal might have as many as 3,000 individual elements of information associated with it. This paper introduces a series of reports dealing with an integrated and comprehensive system of experiment planning and implementation (including information gathering, classification, analyses and reporting), employing state-of-the-art data processing techniques. This extensive use of computer technology has permitted the collection, proper classification, and rapid retrieval of virtually error-free data, resulting in cost-sensitive experiment planning.

Computers↗