Genstruct - Science and Technology

Science and Technology

The Need for a Paradigm Shift

The process of developing a new drug has been estimated to take between 12 and 15 years, and to cost about $802M*. A large proportion of this cost is the cost of failures and the cost of capital amortized over the time period. It almost goes without saying that the cost of developing drugs can be dramatically reduced by:
(1) shortening the discovery and development time
(2) increasing the successes as well as decreasing the failure rate.

The current mantra of the industry - Fail Early, Fail Often - does not address this issue directly nor does this approach increase success. Genstruct believes that the way to decrease the cost and time involved in drug discovery is to increase success rates and speed; in other words- Succeed Early, Succeed Often.

Looking to the technology industries, we can see that increased successes had been accomplished by defining, describing and understanding their technology then developing products based upon this technical knowledge. Furthermore, it seems clear that much of the recent successes in tehcnology product development have been enabled by computer-aided design (CAD) and computer-aided modeling (CAM). Hence, to adopt this approach to drug discovery, Genstruct developed a new, causal framework for computer-aided modeling of biology, and is applying this framework to the modeling of biological systems in order to increase the speed and the success rates of drug discovery and development.

Knowledge-Driven Drug Discovery

Genstruct's paradigm focuses work on Knowledge-Driven Drug Discovery; our goal is to gain systematic understanding of biological mechanisms in order to propel drug discovery to new levels of efficiency. Genstruct delivers on this goal by transforming biology from the abstract mathematical world of data, to the tangible causal world of knowledge, thereby revolutionizing the process of pharmaceutical research and development.

Genstruct’s technologists and scientists have developed the first large-scale causal modeling methodology that can be used to comprehensively model entire biological systems at the level of cells, tissues and organs. Our teams of life scientists use our proprietary platform to build Causal System™ Models of diseases and drug action, and use them to define disease mechanisms, drug mechanisms of activity and toxicity, and mechanistic biomarkers, both independently and with our collaborative partners.

Causal System™ modeling is a rapid and comprehensive process that, when combined with experimental data, is used to define the mechanisms behind the observed expression of diseases and activity of drugs. This ultimately increases the speed and quality of the drug discovery and development process by:

Properly stratifying multiple diseases that may be superficially similar and currently considered as one disease
Defining mechanism of action for diseases and its associated mechanistically based biomarkers
Defining the model and understanding necessary to select and develop the right compounds
Defining the model of drug mechanism, which leads to an understanding of efficacy and toxicity
Identifing the right patients
Delivering biomarkers to follow disease and patient response progress clinically

Causal System™ modeling begins with Genstruct’s human, rat and mouse Knowledge Assembly® Models, and are customized and augmented to make them specific for each cell-type, tissue or organ system. These models represent the cause-effect relationships between the genes, proteins, metabolites and processes gleaned from tens of thousands of primary scientific articles, encoded as causal assertions by our scientists using biological case frames. Individual models are augmented through literature research, data analysis and expert interrogation by our teams of scientific advisors.

Using our Causal System™ modeling and our extensive scientific expertise, we have accomplished the equivalent of four years of research development within four month projects. Genstruct has both defined mechanisms that have perplexed the industry for years and enabled the development of classes of compounds that were previously un-developable. In short, Genstruct is engaged in novel and proprietary discoveries that fully realize the promise of rational, mechanism-based drug discovery.

* Journal of Health Economics 22 (2003) 151–185