Linked Life Data

1314137

Source:http://linkedlifedata.com/resource/pubmed/id/1314137

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
9 Suppl
pubmed:dateCreated
1992-5-21
pubmed:abstractText
Strategies to block the effects of tumor growth factors, such as estrogen, and to recruit other regulatory elements, such as with retinoids, have focused interest on the possibility of successful tumor intervention approaches. Approaches that neutralize the effects of critical molecules that drive tumor promotion are attractive targets for evaluation as new intervention agents. Clinical intervention trials with early stage patients or with subjects from "high risk" populations impose stricter types of constraints than conventional chemotherapy approaches in advanced stage patients. The potential for short-term toxicity has to be considered, as it may affect subject accrual or compliance. The longer expected survival of intervention subjects mandates closer attention to the possibilities of unexpected long-term toxicities with chronic administration of an intervention agent. As part of a Phase I clinical trial evaluating the utility of a monoclonal antibody directed against the autocrine growth factor, gastrin-releasing peptide to block the growth of small cell lung cancer, we developed a mathematical model to predict the requisite amount of antibody to neutralize growth factor effect. This model requires knowledge of the equilibrium concentration of the secreted growth factor, specific receptor, and bioavailability of the antibody in the tumor interstitium. A range of possible target doses of antibody can be developed to address the potential for heterogeneity frequently encountered in such systems, including a range of levels for peptide production and specific receptor expression. This approach could be applied to rationally derive treatment or intervention in which specific information regarding the relevant binding parameters is available. Through refinement of this modeling approach more context-specific dosing of agonist/antagonists could be determined which may decrease side effects associated with the drug administration.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0008-5472
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
52
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2743s-2746s
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1992
pubmed:articleTitle
The correct dose: pharmacologically guided end point for anti-growth factor therapy.
pubmed:affiliation
Biomarkers and Prevention Research Branch, National Cancer Institute, Kensington, Maryland 20895.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.