Predictive modeling in data-driven drug discovery
Despite growing scientific insight and technological investment, attempts to develop novel therapies still show limited success.
Traditional drug screening approaches oversimplify the complexity of living cells by focusing on a 1-to-1 substance–target relationship. Conversely, modern data-driven drug design utilizes all available layers of information to create predictive models that select compounds likely to have the desired effect on the phenotype. High-quality, carefully curated data is essential for this approach.
In this white paper, you will learn more about:
- Modeling at the single molecule level, network level and multiple substance–target interactions
- Implementing data-driven drug design
- The future of systems-based drug development
Read the white paper.
To access the complimentary white paper 'From molecule to phenotype: Predictive modeling in Data-Driven Drug Discovery', please fill in the form below.
Elsevier's R&D Solutions supporting 'From molecule to phenotype: Predictive modeling in Data-Driven Drug Discovery'
Enable better informed preclinical drug safety decisions with comprehensive, fully searchable FDA/EMA drug approval documents and comparative extracted drug safety data.
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