Toxicology Letters 1995: Vol 79 Index

4 Pages·1995·0.96 MB·English

Toxicology Letters 79 (1995) 313-314
Author index
Volume 79 (1995)
Al-Bayati, M.A., see Knaak, J.B. 79, 87 Fiserova-Bergerova, V., Extrapolation of physiological
Andersen, M.E., Development of physiologically based phar- parameters for physiologically based simulation models
79, 77
macokinetic and physiologically based pharmacodymamic
models for applications in toxicology and risk assessment Frederick, C.B., Summary of panel discussion on the ‘advan-
79, 35 tages/limitations/uncertainties in the use of physiologically
Arcos, J.C., see Woo, Y.-t. 79, 219 based pharmacokinetic and pharmacodynamic models in
Argus, M.F., see Woo, Y.-t. 79, 219 hazard identification and risk assessment of toxic sub-
stances’ 79, 201
Basak, S.C., S. Bertelsen, G.D. Grunwald, Use of graph
Gombar, V.K., see Mumtaz, M. 79, 131
theoretic parameters in risk assessment of chemicals 79,
Grunwald, G.D., see Basak, S.C. 79, 239
239
Bertelsen, S., see Basak, S.C. 79, 239
Hansch, C., D. Hoekman, A. Leo, L. Zhang, P. Li, The
Blake, B.W., see Mumtaz, M. 79, 131
expanding role of quantitative structure-activity relation-
Bradbury, S.P., Quantitative structure-activity relationships
ships (QSAR) in toxicology 79, 45
and ecological risk assessment: an overview of predictive
Hertzberg, R., see Durkin, P. 79, 251
aquatic toxicology research 79, 229
Hoang, K.-C.T., Physiologically based pharmacokinetic mod-
Bristol, D.W., Summary and recommendations for Session B:
els: mathematical fundamentals and simulation implemen-
activity classification and _ structure-activity relationship
tations 79, 99
modeling for human health risk assessment of toxic sub-
Hoekman, D., see Hansch, C. 79, 45
stances 79, 265
Hollebone, B.R. L.J. Brownlee, A thermodynamic QSAR
Brownlee, L.J., see Hollebone, B.R. 79, 157
analysis of the polysubstrate monooxygenase responses to
xenobiotic chemicals 79, 157
Childress, T.A., see Mattie, D.R. 79, 291
Huque, K.I., see Mumtaz, M. 79, 131
Cibulas, W., see Wilson, J.D. 79, |
Clewell II], H.J.. The application of physiologically based Jarabek, A.M., The application of dosimetry models to iden-
pharmacokinetic modeling in human health risk assessment tify key processes and parameters for default dose-response
of hazardous substances 79, 207 assessment approaches 79, 171
Constan, A.A., see Yang, R.S.H. 79, 193 Johnson, B.L., Welcome address 79, 3
Johnson, B.L., ATSDR’s information databases to support
DeRosa, C.T., Charge to workshop 79, 7 human health risk assessment of hazardous substances
DeRosa, C.T., see Mumtaz, M. 79, 131 79, 11
DeRosa, C.T., Decision Support Methodologies for Human
Health Assessment of Toxic Substances: Agency for Toxic Kent, R.J., see Wagner, P.M. 79, 67
Substances and Disease Registry’s perspectives on collabo- Klopman, G., H.S. Rosenkranz, Toxicity estimation by chem-
ration and infrastructure development among government, ical substructure analysis: the TOX II program 79, 145
academia, and industry 79, 283 Knaak, J.B., Perspectives on collaboration and infrastructure
Durkin, P., R. Hertzberg, W. Stiteler, M. Mumtaz, The development: industry perspectives 79, 305
identification and testing of interaction patterns 79, 251 Knaak, J.B., A. Al-Bayati, G. Raabe, Development of parti-
tion coefficients, V,,.. and K,, values, and allometric rela-
El-Masri, H.A., see Yang, R.S.H. 79, 193 tionships 79, 87
0378-4274) 95/$09.50 © 1995 Elsevier Science Ireland Ltd. All rights reserved
314 Author index | Toxicology Letters 79 (1995) 313-314
Knauf, L.A., see Mumtaz, M. 79, 131 Paustenbach, D.J., see Leung, H.-W. 79, 55
Kohn, M.C., Achieving credibility in risk assessment models Peirano, W.B., see Mumtaz, M. 79, 131
79, 107
Raabe, O.G., see Knaak, J.B. 79, 87
Lai, D.Y., see Woo, Y.-t. 79, 219 Ramanujam, V.M.S., see Mumtaz, M. 79, 131
Leo, A., see Hansch, C. 79, 45 Reisman, D.J., see Mumtaz, M. 79, 131
Leung, H.-W., D.J. Paustenbach, Physiologically based phar- Richard, A.M.,Role of computational chemistry in support of
macokinetic and pharmacodynamic modeling in health risk hazard identification (ID): mechanism-based SARs _ 79,
assessment and _ characterization of hazardous sub- 115
stances 79, 55 Rosenkranz, H.S., see Klopman, G. 79, 145
Li, P., see Hansch, C. 79, 45
Scheuplein, R.J., Information needed to support hazard
identification and risk assessment of toxic substances 79,
Machuga, E.J., see Matthews, E.J. 79, 123
23
Martin, L.S., see Mattie, D.R. 79, 291
Schwetz, B.A., Use of mechanistic and pharmacokinetic data
Matthews, E.J., E.J. Machuga, Threshold of estimated toxic-
for risk assessment at the National Institute of Environ-
ity for regulation of indirect food additives 79, 123
mental Health Sciences (NIEHS) 79, 29
Mattie, D.R., L.S. Martin, T.A. Childress, Program develop-
Stiteler, W., see Durkin, P. 79, 251
ment in military toxicology laboratories 79, 291
Medinsky, M., The application of physiologically based phar-
Thomas, R.S., see Yang, R.S.H. 79, 193
macokinetic/pharmacodynamic (PBPK/PD) modeling to
understanding the mechanism of action of hazardous sub-
Vandenberg, J.J., Risk assessment and research: an essential
stances 79, 185 link 79, 17
Menzel, D.B., Extrapolating the future: research trends in
modeling 79, 299 Wagner, P.M., J.V. Nabholz, R.J. Kent, The new chemicals
Mumtaz, M., see Durkin, P. 79, 251 process at the Environmental Protection Agency (EPA):
Mumtaz, M., L.A. Knauf, D.J. Reisman, W.B. Peirano, C.T. structure-activity relationships for hazard identification and
DeRosa, V.K. Gombar, B.W. Blake, K.I. Huque, V.M.S. risk assessment 79, 67
Ramanujam, Assessment of effect levels of chemicals from Wilson, J.D.. W. Cibulas, E. Murray, Introduction 79, |
quantitative structure-activity relationship (QSAR) models. Woo, Y.-t., D.Y. Lai, M.F. Argus, J.C. Arcos, Development
I. Chronic lowest-observed-adverse-effect-level (LOAEL) of structure-activity relationship rules for predicting car-
Murray, E., see Wilson, J.D. 79, | cinogenic potential of chemicals 79, 219
Nabholz, J.V., see Wagner, P.M. 79, 67 Yang, R.S.H., H.A. El-Masri, S. Thomas, A. Constan, The
application of physiologically based pharmacokinetic
O'Flaherty, E.J., Perspectives on collaboration and_ in- pharmacodynamic (PBPK/PD) modeling for exploring
frastructure development among government, academia, risk assessment approaches of chemical mixtures 79,
and industry 79, 297 193
Olden, K., NIEHS perspectives on collaboration among gov-
ernment, academia, and industry 79, 287 Zhang, L., see Hansch, C. 79, 45
Toxicology Letters 79 (1995) 315-316
Subject index
Volume 79 (1995)
Academic 79, 297 Food and Drug Administration (FDA) 79, 305
Acceptable daily intake 79, 23 Food substances 79, 23
Activity classification 79, 265
Adverse health effects 79, 11 Graph invariant 79, 239
Agency for Toxic Substances and Disease Registry
(ATSDR) 79, 305 Hazard assessment 79, 67
Allometry 79, 87 Hazard identification 79, 115, 201, 219, 229, 265
Antagonism 79, 251 Hazardous substances 79, 207
Aquatic toxicology 79, 229 Hazardous waste sites 79, 11, 193
Artificial intelligence 79, 265 Health risk assessment 79, 17, 55
Atom pairs 79, 239 Heuristic analysis 79, 265
Human expert system 79, 265
Hydroquinone 79, 185
Benzene metabolism 79, 185
Indirect food additive 79, 123
Calfornia EPA (CALEPA) 79, 305
Information databases 79, 11
Chemical carcinogen 79, 219
Inhaled dose 79, 77
Chemical emergencies 79, 11
Intelligent computer system 79, 265
Chemical functionality 79, 145
Interspecies scaling 79, 171
Chemical mixtures 79, 193
Isofenphos 79, 87
Chlorinated solvents 79, 87
Chronic toxicity assessment 79, 131
K,, 79, 87
Collaboration 79, 287
Knowledge bases 79, 29
Computational chemistry 79, 115
Computer simulations 79, 99
Linear free energy relationships (LFERs) 79, 145
Continuing education 79, 297
Lowest-observed-adverse-effect level (LOAEL) 79, 131
Cytochrome P-450 induction 79, 45
Machine learning 79, 265
Decision support 79, 265
Mathematical models 79, 99
Decision-support methodologies 79, 283
Mechanism-based structure-activity 79, 115
Default assumptions 79, 201
Mechanistic structure-activity relationship 79, 157
Department of Defense 79, 291
Military toxicology 79, 291
Dosimetry 79, 171
Mode of toxic action 79, 229
Molecular modeling 79, 115
Environmental Protection Agency (EPA) 79, 305 Molecular similarity 79, 239
Environmental 79, 287 Monte Carlo analysis 79, 251
Ethylacrylate 79, 87 Mutagenicity 79, 239, 45
Expert system 79, 219
Extrapolation 79, 35, 55 New York State Department of Health (NYSDH) 79, 305
Feature selection 79, 265 PBPK modeling 79, 207
Food additives 79, 23 PBPK models 79, 107
0378-4274/95/$09.50 © 1995 Elsevier Science Ireland Ltd. All rights reserved
316 Subject index | Toxicology Letters 79 (1995) 315-316
PBPK/PD modeling 79, 193, 55 Research 79, 17
PCBTF 79, 87 Risk 79, 157
Partition coefficients 79, 87 Risk assessment 79, 35, 67, 77, 107, 171, 193, 201, 207, 219,
Pattern recognition 79, 265 239
Pharmacodynamics 79, 35 Risk management 79, 17
Pharmacokinetic compartments 79, 77
Pharmacokinetic studies 79, 29 Safety factor 79, 23
Pharmacokinetics 79, 35, 207 SAR _ 79, 115
Phenol metabolism 79, 185 Structure-activity relationship 79, 265
Physician education 79, 11 Structure-activity relationship analysis 79, 219
Physiologically based pharmacokinetic 79, 99 Structure-activity relationships 79, 299
Physiologically based pharmacokinetic (PBPK) model 79, 87 Structure-activity relationships (SAR) 79, 67, 305
Physiologically based pharmacokinetic modeling 79, 171, 201 Substance-specific applied research program 79, 283
Physiologically based pharmacokinetic models 79, 77, 297 Superfund 79, 11
Physiologically based pharmacokinetic/pharmacodynamic Synergism 79, 251
(PBPK/PD) modeling 79, 185 :
Physiologically based pharmacokinetics 79, 299 Teaching 79, 297 :
Physiologically based pharmacokinetics (PBPK) 79, 305 Threshold of Regulation 79, 123
Polysubstrate monooxygenase 79, 157 Topological indices 79, 239
Predictive toxicology 79, 265 Toxicity studies 79, 29
Priority data needs 79, 283 Toxicodynamic models 79, 299
Program development 79, 291 Toxicologic interactions 79, 251
Public health assessments 79, 11 Toxicology 79, 287
Toxicophores 79, 145
QSAR 79, 45 TOX II program 79, 145
Quantitative Structure Activity Relationships (QSAR) 79, 123 benim nerostvina nines Altideae
Quantitative structure-activity relationship 79, 297 Uncertainty 79, 171, 201
Quantitative structure-activity relationship (QSAR) model-
ing 79, 131 V, 79, 87
max
Quantitative structure-activity relationships 79, 229 Validation of models 79, 107