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- W2887924918 abstract "Predictive technologies can be applied to a wide spectrum of toxicological issues in drug development. Applications include hazard identification through screening, specific compound analysis, potential genotoxic impurities, investigative studies on the mechanism of action for toxicity, exposure assessment, guidance on off-target effects linked to potential safety liabilities, enabling of data integration, and the study of systems-level analysis of toxic responses. A major advantage of predictive computational toxicology is its versatility and the capacity to reduce time and resources to better define areas of risk so that they may be appropriately managed and mitigated. In this chapter, methods and design of technologies will be emphasized using case examples and investigative studies to present the current and future roles of predictive computational toxicology methods in early drug development. Objectives of this chapter will be to identify, characterize, update, and assess predictive computational toxicology methods in the context of early drug development. The challenges in interpreting and applying data from these newer technologies will also be covered. The goal to be achieved for readers is to increase confidence and heighten interest in how predictive computational toxicology methods can help guide pharmaceutical researchers experienced in drug development processes and also toxicologists who are nonspecialists in this field. Thus, employing the use of these predictive technologies to support the design of safer drug product and substance and refine the targeting for efficacy to support and help solve practical research and drug development challenges is a primary objective." @default.
- W2887924918 created "2018-08-22" @default.
- W2887924918 creator A5075760054 @default.
- W2887924918 date "2018-08-03" @default.
- W2887924918 modified "2023-10-16" @default.
- W2887924918 title "Early Drug Development" @default.
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- W2887924918 doi "https://doi.org/10.1002/9783527801756.ch20" @default.
- W2887924918 hasPublicationYear "2018" @default.
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