In silico approaches to explore toxicity end points: issues and concerns for estimating human health effects

Bibliography

• MATTHEWS EJ, BENZ RD, CONTRERA JF: Use of toxicological information in drug design. J. Molec. Graphics Modeling (2000) 18:605-614.
   PubMed Web of Science ®Google Scholar
• MATTHEWS EJ, CONTRERA JF: A new highly specific method for predicting the carcinogenic potential of pharmaceuticals using enhanced MCASE-ES software. Regul. Toxicol. Pharmacol. (1998) 28:242-264.
   PubMed Web of Science ®Google Scholar
• MATTHEWS EJ, KRUHLAK NL, CIMINO MC, BENZ RD, CONTRERA JF: An analysis of genetic toxicity, reproductive and developmental toxicity, and carcinogenicity data: I. Identification of carcinogens using surrogate categories. Regul. Toxicol. Pharmacol. (2006) 44:83-96.
   PubMed Web of Science ®Google Scholar
• MATTHEWS EJ, KRUHLAK NL, CIMINO MC, BENZ RD, CONTRERA JF: Analysis of genetic toxicity, reproductive and developmental toxicity, and carcinogenicity data: II. Identification of genotoxicants, reprotoxicants, and carcinogens using in silico methods. Regul. Toxicol. Pharmacol. (2006) 44:97-110.
   PubMed Web of Science ®Google Scholar
• VAN DER JAGT K, MUNN S, TØRSLØV J, DE BRU J: Alternative approaches can reduce the use of test animals under REACH. Report of the Institute for Health and Consumer Protection (IHCP). (2003):1-31.
   Google Scholar
• DIRECTORATE-GENERAL, ENTERPRISE AND INDUSTRY, AND DIRECTORATE-GENERAL, ENVIRONMENT: Consultation document concerning registration, evaluation, authorisation and restrictions of chemicals (REACH) (2003).
   Google Scholar
• DIRECTORATE-GENERAL, ENTERPRISE AND INDUSTRY, AND DIRECTORATE-GENERAL, ENVIRONMENT: Commission communication on number of substances impacted by the REACH legislation (2003).
   Google Scholar
• OECD: Report on the regulatory uses and applications in OECD member countries of (quantitative) structure–activity relationship [(Q)SAR] models in the assessment of new and existing chemicals. OECD environment health and safety publications series on testing and assessment No. XX. Draft (May 2006).
   Google Scholar
• OECD: Guidance document on the validation of (quantitative) structure–activity relationship [Q)SAR] models. OECD environment health and safety publications series on testing and assessment No. XX. Draft (May 2006).
   Google Scholar
• OECD: (Q)SAR application toolbox. DRAFT documents on discussion points, progress report, and work plan (May 2006).
   Google Scholar
• DEARDEN JC, BARRATT MD, BENIGNI R et al.: The development and validation of expert systems for predicting toxicity. The report and recommendations of an ECVAM/ECB workshop 24. ATLA (1997) 25:223-252.
   Google Scholar
• NETZEVA TI, WORTH AP, ALDENBER T et al.: Current status of methods for defining the applicability domain of (quantitative) structure–activity relationships. The report and recommendations of ECVAM Workshop 52. ATLA (2005) 33:155-173.
   Google Scholar
• CONTRERA JF, JACOBS AC, DEGEORGE JJ: Carcinogenicity testing and the evaluation of regulatory requirements for pharmaceuticals. Regul. Toxicol. Pharmacol. (1997) 25:130-145.
   PubMed Web of Science ®Google Scholar
• CONTRERA JF, MATTHEWS EJ, BENZ RD: Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices. Regul. Toxicol. Pharmacol. (2003) 38:243-259.
   PubMed Web of Science ®Google Scholar
• CONTRERA JF, MACLAUGHLIN P, HALL LH, KIER LB: QSAR modeling of carcinogenic risk using discriminant analysis and topological molecular descriptors. Curr. Drug Discov. Technol. (2005) 2:55-67.
   PubMedGoogle Scholar
• KIRKLAND D, AARDEMA M, HENDERSON L, MÜLLER L: Evaluation of the ability of a battery of three in vitro tests to discriminate carcinogens and non-carcinogens. I. Sensitivity, specificity, and relative predictivity. Mutat. Res. (2005) 584:1-256.
   PubMed Web of Science ®Google Scholar
• HASEMAN JK, WINBUSH JS, O’DONNELL MW: The use of dual negative control groups to estimate false-positive rates in laboratory animal carcinogenicity studies. Fundam. Appl. Toxicol. (1986) 7:573-584.
   PubMedGoogle Scholar
• MATTHEWS EJ, BENZ RD, KRUHLAK NL, CONTRERA JF: A comprehensive model for reproductive and developmental toxicity hazard identification: I. Development of a weight of evidence QSAR database. Reg. Toxicol. Pharmacol. (2007) (In Press).
   Google Scholar
• MATTHEWS EJ, KRUHLAK NL, BENZ RD, IVANOV J, KLOPMAN G, CONTRERA JF: A comprehensive model for reproductive and developmental toxicity hazard Identification: II. Construction of QSAR models to predict activities of untested chemicals. Reg. Toxicol. Pharmacol. (2006) (In Press).
   Google Scholar
• MATTHEWS EJ, KRUHLAK NL, WEAVER JL, BENZ RD, CONTRERA JF: Assessment of the health effects of chemicals in humans: II Construction of an adverse effects database for QSAR modeling. Curr. Drug Discov. Technol. (2004) 1:243-254.
   PubMedGoogle Scholar
• MATTHEWS EJ, KRUHLAK NL, BENZ RD, CONTRERA JF: Assessment of the health effects of chemicals in humans: I. QSAR estimation of the maximum recommended therapeutic dose (MRTD) and no effect level (NOEL) of organic chemicals based on clinical trial data. Curr. Drug Discov. Tech. (2004) 1:61-76.
   PubMedGoogle Scholar
• CONTRERA JF, MATTHEWS EJ, KRUHLAK NL, BENZ RD: Estimating the safe starting dose in Phase I clinical trials and no observed effect level based on QSAR modeling of the human maximum recommended daily dose. Reg. Toxicol. Pharmacol. (2004) 40:185-206.
   PubMed Web of Science ®Google Scholar
• KRUHLAK NL, CONTRERA JF, BENZ RD, MATTHEWS EJ: Progress in QSAR toxicity screening of pharmaceutical impurities and other FDA regulated products. Adv. Drug Deliv. Rev. (2007) (In Press).
   PubMedGoogle Scholar
• KLOPMAN G: Multicase: a hierarchical computer automated structure evaluation program. QSAR (1992) 11:176-184.
   Web of Science ®Google Scholar
• CONTRERA JF, MATTHEWS EJ, KRUHLAK NL, BENZ RD: In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL-QSAR software. Reg. Toxicol. Pharmacol. (2005) 43:313-323.
   PubMed Web of Science ®Google Scholar
• KIER LB, HALL LH: In: Molecular structure description: the electrotopological state. Lemont B (Ed.), Academic Press, New York, USA (1999).
   Google Scholar
• NIEMELÄ JR, VINGGAARD M, WEDEBYE EB, JENSEN GE: QSAR model for antiandrogenic effect project group. Presentation at the: OECD Ad Hoc Workgroup Meeting. Stresa, Italy (2006).
   Google Scholar
• ZEEMAN M, AUER CM, CLEMENTS RG, NABHOLZ JV, BOETHLING RS: USUS EPA regulatory perspectives on the use of (Q)SAR for new and existing chemical evaluations. SAR QSAR Environ. Res. (1995) 3:179-201.
   PubMedGoogle Scholar