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Predictive Teratology: Teratogenic Risk-Hazard Identification Partnered in the Discovery Process

[ Vol. 9 , Issue. 9 ]


K. A. Augustine-Rauch   Pages 971 - 977 ( 7 )


Unexpected teratogenicity is ranked as one of the most prevalent causes for toxicity-related attrition of drug candidates. Without proactive assessment, the liability tends to be identified relatively late in drug development, following significant investment in compound and engagement in pre clinical and clinical studies. When unexpected teratogenicity occurs in pre-clinical development, three principle questions arise: Can clinical trials that include women of child bearing populations be initiated? Will all compounds in this pharmacological class produce the same liability? Could this effect be related to the chemical structure resulting in undesirable off-target adverse effects? The first question is typically addressed at the time of the unexpected finding and involves considering the nature of the teratogenicity, whether or not maternal toxicity could have had a role in onset, human exposure margins and therapeutic indication. The latter two questions can be addressed proactively, earlier in the discovery process as drug target profiling and lead compound optimization is taking place. Such proactive approaches include thorough assessment of the literature for identification of potential liabilities and follow-up work that can be conducted on the level of target expression and functional characterization using molecular biology and developmental model systems. Developmental model systems can also be applied in the form of in vitro teratogenicity screens, and show potential for effective hazard identification or issue resolution on the level of characterizing teratogenic mechanism. This review discusses approaches that can be applied for proactive assessment of compounds for teratogenic liability.


Proactive discovery safety assessment, teratogenic, teratogenicity screen, risk and hazard assessment


Research Fellow Drug Safety-Pre Clinical Optimization, Bristol Myers Squibb Research Institute, Mail Code: 17-02- 233, 311 Pennington-Rocky Hill Rd., Hopewell, NJ 08534, USA.

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