Article
Clinical Neurology
Sara K. Quinney, Kandasamy Murugesh, Adrian Oblak, Kristen D. Onos, Mike Sasner, Anna K. Greenwood, Kara H. Woo, Stacey J. Sukoff Rizzo, Paul R. Territo
Summary: We propose an unbiased methodology for ranking compounds for preclinical testing in Alzheimer's disease (AD) in order to enhance successful translation to the clinic. Previously compound selection was based solely on physiochemical properties, making ranking challenging. The STOP-AD framework overcomes this limitation by evaluating drug-like properties and performing Monte-Carlo simulations. Highlights: Promising preclinical studies for AD drugs have not translated to clinical success. Systematic assessment of AD drug candidates may increase clinical translatability. We describe a well-defined compound selection framework with clear selection metrics.
ALZHEIMERS & DEMENTIA
(2023)
Article
Pharmacology & Pharmacy
Jose D. Suarez-Torres, Camilo A. Orozco, Carlos E. Ciangherotti
Summary: This study examined the use of statistics-based and regulatory pertinent predictive values approach in preclinical testing data, and applied it to assess the probability of carcinogenicity for 37 pharmaceuticals with inadequate epidemiological evidence but unequivocal mutagenic properties. The results suggest a high probability of carcinogenicity for these drugs, prompting recommendations for significant carcinogenicity warnings, further studies, and potential re-evaluation of authorization for certain medications with estimated high probability of carcinogenicity to humans.
FUNDAMENTAL & CLINICAL PHARMACOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Feifan Li, Tengjiao Fan, Guohui Sun, Lijiao Zhao, Rugang Zhong, Yongzhen Peng
Summary: This study developed a series of quantitative structure-activity relationship (QSAR) models and interspecies quantitative carcinogenicity-carcinogenicity relationship (iQCCR) models to predict the carcinogenicity of fused/non-fused aromatic hydrocarbons (FNFAHs) to rodents. These models demonstrated good predictive performance and can be used to predict the carcinogenic potency of hundreds of unknown compounds.
Review
Biotechnology & Applied Microbiology
Hanieh Gholizadeh, Shaokoon Cheng, Agisilaos Kourmatzis, Hanwen Xing, Daniela Traini, Paul M. Young, Hui Xin Ong
Summary: This article discusses the application of in vitro human organ models in preclinical drug testing. Conventional in vitro tissue models and animal models have failed to accurately predict the clinical success of new therapies. Organ-on-chip technology provides realistic tissue models that mimic the physiological characteristics of human organs and has been successfully applied in drug testing.
BIOENGINEERING-BASEL
(2022)
Article
Computer Science, Software Engineering
Pengcheng Zhang, Bin Ren, Hai Dong, Qiyin Dai
Summary: Deep Neural Network (DNN) technologies have been widely used in various aspects of our life, but existing methods fail to detect erroneous behaviors. To address this issue, we propose a new testing method called CAGFuzz, which can generate adversarial examples for mainstream DNN models to discover potential errors.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Review
Pharmacology & Pharmacy
Jose D. Suarez-Torres, Camilo A. Orozco, Carlos E. Ciangherotti
Summary: The 2-year rodent bioassay (RCB) has been widely used as the benchmark method to screen the carcinogenicity of substances to humans, despite controversy. RCB conducted at maximum tolerated doses (MTDs) showed high sensitivity in detecting human carcinogens while avoiding reactions to non-carcinogens. Specific rodent mechanisms contributed to unspecificity in RCBs, but Bayesian forecasting could help resolve the paradox between sensitivity and unspecificity. Additional caution is advised in discontinuing mouse-RCBs to avoid missing potential human carcinogens.
JOURNAL OF PHARMACOLOGICAL AND TOXICOLOGICAL METHODS
(2021)
Article
Toxicology
Takashi Yamada, Minoru Miura, Tomoko Kawamura, Kazuo Ushida, Kaoru Inoue, Makiko Kuwagata, Naruo Katsutani, Akihiko Hirose
Summary: The study created a reliable and transparent database consisting of DART studies conducted by Japanese government ministries, with 171 substances exhibiting signs of DART. Comparison of LOAELs between DART and RDT revealed that 15 substances had lower LOAEL for DART than RDT, which can be useful for future integrated testing and assessment approaches.
JOURNAL OF TOXICOLOGICAL SCIENCES
(2021)
Article
Pharmacology & Pharmacy
Matthew S. Bogdanffy, Jacob Lesniak, Raja Mangipudy, Frank D. Sistare, Karyn Colman, David Garcia-Tapia, Thomas Monticello, Diann Blanset
INTERNATIONAL JOURNAL OF TOXICOLOGY
(2020)
Article
Pathology
Katerina Vlasakova, Sean P. Troth, Frank D. Sistare, Warren E. Glaab
TOXICOLOGIC PATHOLOGY
(2020)
Article
Toxicology
Wen Kang, Alexei A. Podtelezhnikov, Keith Q. Tanis, Stephen Pacchione, Ming Su, Kimberly B. Bleicher, Zhibin Wang, George M. Laws, Thomas G. Griffiths, Matthew C. Kuhls, Qing Chen, Ian Knemeyer, Donald J. Marsh, Kaushik Mitra, Jose Lebron, Frank D. Sistare
TOXICOLOGICAL SCIENCES
(2020)
Article
Toxicology
Brenda Smith, Josh Rowe, Paul B. Watkins, Messoud Ashina, Jeffrey L. Woodhead, Frank D. Sistare, Peter J. Goadsby
TOXICOLOGICAL SCIENCES
(2020)
Article
Pharmacology & Pharmacy
Yi-Zhong Gu, Katerina Vlasakova, Jarig Darbes, Erjia Wang, Jude Ferraro, Warren E. Glaab, Frank D. Sistare
Article
Pharmacology & Pharmacy
Michael J. Hafey, Robert Houle, Keith Q. Tanis, Ian Knemeyer, Jackie Shang, Qing Chen, Andreas Baudy, James Monroe, Frank D. Sistare, Raymond Evers
DRUG METABOLISM AND DISPOSITION
(2020)
Article
Toxicology
Warren E. Glaab, Daniel Holder, Yudong D. He, Wendy J. Bailey, David L. Gerhold, Carolann Beare, Zoltan Erdos, Pamela Lane, Laura Michna, Nagaraja Muniappa, Jeffrey W. Lawrence, Keith Q. Tanis, Joseph F. Sina, Thomas R. Skopek, Frank D. Sistare
Summary: A new safety testing paradigm utilizing gene expression biomarkers has been developed to identify drug-induced injuries in rats quickly and easily, aiding in drug candidate selection. By identifying differentially expressed genes in targeted tissues following injuries induced by known toxicants, a set of 22 genes was selected and incorporated into a rapid assessment method for tissue degeneration/necrosis in rats. This approach showed high sensitivity and specificity in detecting tissue injuries across various organs, providing a practical tool for early safety evaluation.
TOXICOLOGICAL SCIENCES
(2021)
Article
Pathology
Yi-Zhong Gu, Larry Handt, Katerina Vlasakova, Vasudevan Bakthavatchalu, Roger Smith, Guillermo E. Fernandez, Stephanie L. Born, Warren E. Glaab, Frank D. Sistare
Summary: This study compared the monitoring performance of serum and urine safety biomarkers, gene expression alterations, and conventional serum biomarkers in diagnosing low-grade kidney injury in rhesus monkeys. Gene expression profiling on kidney biopsy specimens and urinary kidney safety biomarkers showed promising results in monitoring kidney injury, highlighting the potential for future definitive studies.
TOXICOLOGIC PATHOLOGY
(2022)
Article
Pathology
Shigeru Hisada, Kenjiro Tsubota, Kenji Inoue, Hisaharu Yamada, Takanori Ikeda, Frank D. Sistare
Summary: Exceeding a high dose level of 50-fold AM in rasH2-Tg mouse carcinogenicity studies does not appear to be of value according to the survey results.
JOURNAL OF TOXICOLOGIC PATHOLOGY
(2022)
Article
Toxicology
Katerina Vlasakova, Jennifer Bourque, Wendy J. Bailey, Shetal Patel, Elizabeth G. Besteman, Raymond J. Gonzalez, Frank D. Sistare, Warren E. Glaab
Summary: This study evaluated 4 biomarkers of tissue remodeling and inflammation, as well as the traditional serum parameter albumin, as potential blood-based biomarkers for monitoring drug-induced tissue injury and systemic inflammatory response. The results showed that these biomarkers performed well in detecting tissue injury and inflammation, with high sensitivity.
TOXICOLOGICAL SCIENCES
(2022)
Article
Toxicology
J. Christopher Corton, Constance A. Mitchell, Scott Auerbach, J. Pierre Bushel, Heidrun Ellinger-Ziegelbauer, Patricia A. Escobar, Roland Froetschl, Alison H. Harrill, Kamin Johnson, James E. Klaunig, Arun R. Pandiri, Alexei A. Podtelezhnikov, Julia E. Rager, Keith Q. Tanis, Jan Willem van der Laan, Alisa Vespa, Carole L. Yauk, Syril D. Pettit, Frank D. Sistare
Summary: There is growing recognition in the scientific community of the potential for using genomic biomarkers to reduce the need for conventional rodent carcinogenicity studies. These biomarkers can predict tumorigenic doses of chemicals by measuring gene transcripts and cancer driver gene mutations.
TOXICOLOGICAL SCIENCES
(2022)
Review
Biotechnology & Applied Microbiology
Keren J. Carss, Aimee M. Deaton, Alberto Del Rio-Espinola, Dorothee Diogo, Mark Fielden, Diptee A. Kulkarni, Jonathan Moggs, Peter Newham, Matthew R. Nelson, Frank D. Sistare, Lucas D. Ward, Jing Yuan
Summary: Studies of human genetics have provided important insights for drug discovery, including predicting potential effects and assessing safety. Human genetic data can be used as a model to anticipate the long-term effects and potential risks of therapeutic targets. This approach is particularly useful for evaluating the safety of drugs without suitable animal models.
NATURE REVIEWS DRUG DISCOVERY
(2023)
Article
Urology & Nephrology
Brian R. Lane, Stephen K. Babitz, Katerina Vlasakova, Allen Wong, Sabrina L. Noyes, William Boshoven, Pam Grady, Cindy Zimmerman, Susan Engerman, Maureen Gebben, Michael Tanen, Warren E. Glaab, Frank D. Sistare
EUROPEAN UROLOGY FOCUS
(2020)
Review
Biochemical Research Methods
Jonathan A. Phillips, Taraka Sai Pavan Grandhi, Myrtle Davis, Jean-Charles Gautier, Niresh Hariparsad, Douglas Keller, Radhakrishna Sura, Terry R. Van Vleet
Review
Biochemical Research Methods
Andreas R. Baudy, Monicah A. Otieno, Philip Hewitt, Jinping Gan, Adrian Roth, Douglas Keller, Radhakrishna Sura, Terry R. Van Vleet, William R. Proctor