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Today's innovator organizations are under increasing pressure to rapidly discover and develop first- and best-in-class drugs and diagnostics for unmet medical needs. To reach this goal, they must address increasingly complex data to find the key drivers of outcomes, and establish quantitative, testable hypotheses that integrate the many different types of data relevant to the disease or drug being studied.

GNS, through its REFSTM technology, uniquely fills this critical gap in current drug discovery and development. Starting with raw data, REFSTM can produce robust knowledge of disease and/or drug response that ties together molecular drivers with phenotypic endpoints.

Case Studies
The most effective combination of targets and drugs for treating different forms of cancer. more
The mechanism of efficacy for a new drug candidate, and the clinical markers that are predictive of its efficacy. more
The mechanism of disease for colon cancer. more
To learn what we could do for you, contact us.
Reverse Engineering and Forward Simulation

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Understanding FTI and Taxane Combination Cancer Therapy

Case Study One: Taxane Combination Cancers

Business and Scientific rationale:

Most common diseases are polygenic, and many diseases become refractory to treatment through various resistance mechanisms. Drug combinations can significantly reduce the incidence of resistance and improve outcomes by addressing multiple mechanisms. Combination therapies are high value products that extend the patent life of current therapies and provide a competitive advantage in the treatment marketplace by reducing the amounts of medicines used that have unpleasant side effects but good efficacy, such as taxane. REFSTM provides a way to reduce the time needed to discover effective combinations from years to months.

Desired knowledge

  1. What are the causal intracellular networks and the critical molecular control points in understanding the synergistic molecular mechanisms of farnesyltransferase inhibitor (FTI) and Taxane?
  2. What are the pharmacodynamic markers that can be used as clinical indicators to monitor the efficacy of FTI and Taxane combination therapy?
  3. What are additional targets that can enhance FTI and/or Taxane therapeutic responses?

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Mechanism of efficacy of a diabetes drug relative to other compounds in the same class

Case Study Two: Finding the mechanisms

Business and Scientific rationale

The incidence of metabolic disorders, including type II diabetes, is exploding in the developed world. Despite many new and older treatments, it is difficult to differentiate many drugs for diabetes that are aimed at the same target, or that result in the same phenotypic changes. Furthermore, because diabetes is a complex, polygenic disease, the molecular pathways that contribute causally to the disease remain largely unknown. Discovering promising new targets as well as demonstrating unique mechanisms of action (and potential combinations) for current and emerging targeted treatments is critical to success in this increasingly crowded and growing market.

Desired knowledge

  1. What are the combinations of molecular factors driving the efficacy of a novel diabetes therapy, especially in comparison to other marketed treatments?
  2. Which serum markers can be used as clinical indicators to monitor the efficacy of this new compound (and related compounds) in the clinic?

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Defining the molecular mechanisms of colon cancer

Case Study Two: Finding the mechanisms

Business and Scientific rationale

The American Cancer Society estimates that there will be 150,000 new cases of colorectal cancer diagnosed this year in the US, and nearly 50, 000 deaths attributable to the disease (9% of all cancer deaths). Although the death rate has declined thanks to more aggressive early screening efforts, the molecular causes of this common cancer remain unknown, and thus limited treatment options are available. Furthermore, there is little understanding of the molecular markers that would predict recurrence and survival, and that could be used to guide treatment decisions.

Desired knowledge

  1. What are the causal molecular networks that identify combinations of changes that, when taken together, identify critical control points in colon cancer
  2. What are the subpopulation-defining prognostic markers for recurrence and/or survival for colon cancer?
  3. What therapeutic targets or combinations of targets should be addressed in the subpopulations that have poor prognosis following surgery?