Search PubMedSearch

PubMed · 10261828

The data processing dilemma.

Abstract

With the inevitability of automation at hand, today's medical groups must face the data processing dilemma with objectivity and thoroughness. The author sketches a background of the evolution of data processing for medical groups and briefly reviews the factors involved in the decision of whether to use a service bureau or buy a computer system. The essence of this article, however, is a discussion of the development of an RFP. A detailed outline of the elements necessary to include is provided, and format, distribution, and evaluation of proposals are all addressed. In conclusion, important considerations in the final selection, negotiation, and conversion processes are presented.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

S G Clayton. The data processing dilemma.. https://pubmed.ncbi.nlm.nih.gov/10261828/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Avatars in space.

Explore the source record for details and available documents.

Computers

Structure-based inhibitor design.

Time and costs associated with the discovery of new drugs have been significantly reduced by enzyme structure-based approaches to the discovery of new chemotherapeutic agents. However, fundamental components of the overall approach continue to rely on technologies which, by their nature, involve relatively random processes (i.e., combinatorial chemistry and high-throughput screening). Thus, the efficiency of the drug discovery process potentially could be further improved through better use of structural information. In this regard, three-dimensional structures of enzymes are now being solved at high resolution and/or in conformations that provide data that should be more useful for inhibitor design or discovery. Scientists are beginning to appreciate the importance of water as a possible competitor of inhibitors for binding to target enzymes. New computational algorithms are improving the efficiency of identifying flexible inhibitors from among the large numbers of compounds in chemical databases. Also, tools of molecular genetics together with structures of target enzymes are likely to be used more frequently in dealing with the development of resistance to novel chemotherapeutic agents. Instead of detailing success stories in structure-based drug discovery, the following article considers how future efforts to discover or design new drugs may increasingly rely on information about molecular targets and less on data acquired via approaches involving random methodologies.

Computers