Goldilocks’ Determination of What New In Vivo Data are “Just Right” for Different Common Drug Development Scenarios, Part 1

Knockout mouse models are predictive of malformations or embryo-fetal death in drug safety evaluations

Traditionally, understanding potential developmental toxicity from pharmaceutical exposures has been based on the results of ICH guideline studies in two species. However, support is growing for the use of weight of evidence approaches when communicating the risk of developmental toxicity, where the intended pharmacologic mode of action affects fundamental pathways in developmental biology or phenotypic data from genetically modified animals may increasingly be included in the overall assessment. Since some concern surrounds the use of data from knockout (KO) mice to accurately predict the risk for pharmaceutical modulation of a target, a deeper understanding of the relevance and predictivity of adverse developmental effects in KO mice for pharmacological target modulation is needed. To this end, we compared the results of embryo-fetal development (EFD) studies for 86 drugs approved by the FDA from 2017 to 2019 that also had KO mouse data available in the public domain. These comparisons demonstrate that data from KO mouse models are overall highly predictive of malformations or embryo-fetal lethality (MEFL) from EFD studies, but less so of a negative outcome in EFD studies. This information supports the use of embryo-fetal toxicity data in KO models as part of weight of evidence approaches in the communication of developmental toxicity risk of pharmaceutical compounds.

Knockout mouse models are predictive of malformations or embryo-fetal death in drug safety evaluations

Traditionally, understanding potential developmental toxicity from pharmaceutical exposures has been based on the results of ICH guideline studies in two species. However, support is growing for the use of weight of evidence approaches when communicating the risk of developmental toxicity, where the intended pharmacologic mode of action affects fundamental pathways in developmental biology or phenotypic data from genetically modified animals may increasingly be included in the overall assessment. Since some concern surrounds the use of data from knockout (KO) mice to accurately predict the risk for pharmaceutical modulation of a target, a deeper understanding of the relevance and predictivity of adverse developmental effects in KO mice for pharmacological target modulation is needed. To this end, we compared the results of embryo-fetal development (EFD) studies for 86 drugs approved by the FDA from 2017 to 2019 that also had KO mouse data available in the public domain. These comparisons demonstrate that data from KO mouse models are overall highly predictive of malformations or embryo-fetal lethality (MEFL) from EFD studies, but less so of a negative outcome in EFD studies. This information supports the use of embryo-fetal toxicity data in KO models as part of weight of evidence approaches in the communication of developmental toxicity risk of pharmaceutical compounds.

Predicting the safety of medicines in pregnancy: A workshop report

The framework for developmental toxicity testing has remained largely unchanged for over 50 years and although it remains invaluable in assessing potential risks in pregnancy, knowledge gaps exist, and some outcomes do not necessarily correlate with clinical experience. Advances in omics, in silico approaches and alternative assays are providing opportunities to enhance our understanding of embryo-fetal development and the prediction of potential risks associated with the use of medicines in pregnancy. A workshop organised by the Medicines and Healthcare products Regulatory Agency (MHRA), "Predicting the Safety of Medicines in Pregnancy - a New Era?", was attended by delegates representing regulatory authorities, academia, industry, patients, funding bodies and software developers to consider how to improve the quality of and access to nonclinical developmental toxicity data and how to use this data to better predict the safety of medicines in human pregnancy. The workshop delegates concluded that based on comparative data to date alternative methodologies are currently no more predictive than conventional methods and not qualified for use in regulatory submissions. To advance the development and qualification of alternative methodologies, there is a requirement for better coordinated multidisciplinary cross-sector interactions coupled with data sharing. Furthermore, a better understanding of human developmental biology and the incorporation of this knowledge into the development of alternative methodologies is essential to enhance the prediction of adverse outcomes for human development. The output of the workshop was a series of recommendations aimed at supporting multidisciplinary efforts to develop and validate these alternative methodologies.