The Role of Modeling in the Process of Drug Discovery and Development

Drug development is a complex, multi-dimensional, process. It is an expensive process, typically requiring investment of more than $1 billion dollars, and requiring several years from target identification and molecular scaffold (lead) selection, to eventual clinical development, the latter itself also a multi-year process. Owing to its complexity, drug development is a risky undertaking. In the past two decades, application of modeling and simulation approaches along the continuum of lead selection to lead optimization to preclinical candidate development to clinical development to regulatory approval has reduced risks and improved efficiency of this multi-phasic and -dimensional process. This brief presentation will present an overview of key modeling and simulation platforms that drive drug discovery and development. Attention will be given to 1) how models improve translational fidelity from pre-clinical experimental models, and 2) how they inform clinical trial design. For slides for this presentation see: https://drive.google.com/file/d/1_TIqjWNLVopT6TpfvffqV3cGO0BzTx0H/view?usp=sharing Innate and Adaptive Immune Response Subgroup Plan Veronika Zarnitzyna, PhD Emory University We will consider mathematical models of immune response to viral infections. Some viruses (e.g. influenza) cause acute infection, some (e.g. HIV, herpesviruses such as CMV and EBV) results in persistent infection and some (hepatitis C and hepatitis B) may generate both outcomes in immune-competent humans. Considerable evidence has shown that differential immune response is a major factor in disease outcome in many viral infections. What features of the virus and which factors of the immune system (both innate and adaptive) affect the outcome? What contributes to the heterogeneity in the outcome? Is it possible that SARS-CoV-2 establishes a persistent infection in a fraction of otherwise healthy (at the moment of virus introduction) people? Are long-haulers dealing with organ damage after virus clearance or with low-grade reactivation of the virus? The inherent complexity of the immune system requires modeling approaches in order to reveal the molecular and cellular mechanisms that promote unhealthy or non-optimal immune responses. Moreover, the models will be valuable for expediting the discovery and optimization of immunomodulatory treatments of virus infection. For slides for this presentation see: https://drive.google.com/file/d/1SoaH3H3rGltyncQcBGsZezK7Wp2vNc5M/view?usp=sharing If you found this video useful, please check out our other videos on computational modeling, infection and immunology: https://youtube.com/playlist?list=PLiEtieOeWbMKh9VcQoinSwODcSZKMTGat Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/content/msm-viral-pandemics-meetings Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/