In an era of dwindling product pipelines and looming patent expirations, the pain of drug development is particularly acute for pharma. To increase the R&D productivity ratio and reduce the risk of failure in late stage clinical trials or post-production, the life sciences industry is leveraging the use of in silico technologies to support decision-making in the early stages of drug discovery.
Scope
- Identifies the key forces driving the adoption of in silico technologies by the life sciences industry
- Analyzes the crucial issues that will impede the use of computer models and simulations during drug discovery
- Discusses the benefits of using in silico tools and how to get the most out of them
- Offers insight into the in silico technology competitive landscape
Highlights of this title
The use of computer simulations during drug discovery and development can drastically reduce the cost of bringing a drug to market. Computational and mathematical models to better understand how a drug will react in the human body will allow for more informed go/no-go decisions prior to investment in expensive trials, thereby reducing R&D costs.
Although the current approach to drug discovery gives scientists a general idea of how drug candidates will work, in vitro/in vivo models are not the same as humans. Prior to conducting potentially harmful clinical trials, researchers must build models that simulate physiological and biological behaviors in response to varying properties of a drug.
In silico research involves using a variety of technology solutions that range from HPC to simulation and predictive modeling tools to data mining systems to bio and cheminformatics, which are provided by a number of vendors that have expertise in different areas of discovery research.
Key reasons to purchase this title
- Validate your market messaging and positioning in the pharmaceutical industry
- Identify strategies that will increase adoption of in silico technologies by life sciences companies
- Understand the trends that are shaping the future of pharma R&D
