According to a 2007 article by Pharmaceutical Product Development, Inc., it takes an average of 10 to 12 years to discover and to develop a new medicine. The same article reports that the average cost of bringing a single new medicine to market exceeds $900 million. Of ten compounds that reach the clinical trial stage, only one will make it to approval. Given such daunting statistics, it is imperative to maximize the likelihood of success in the development process by selecting the right compounds for costly clinical development.
Our proprietary drug discovery platform, Pentad™, facilitates the design of highly targeted lead compounds with a greater likelihood of advancement in development than could be achieved using traditional laboratory synthesis and screening methods. Pentad predicts the likelihood that novel compounds will interact with various NNR subtypes, the degree of the interaction and the potential of these compounds to be developed as drugs based on projected pharmacokinetic profiles, all prior to the commitment of medicinal chemistry resources.
Pentad combines extensive biological data from a library of diverse compounds with sophisticated computational simulation methodologies.
Biology Database
We have developed and gathered an extensive database of biological data from a library of diverse compounds over 20+ years of leadership in NNR research—the most extensive experience in the field. Our data archive is bolstered by our own sophisticated cellular and biochemical techniques that are predictive of a drug's therapeutic potential, including:
- Novel pharmacological screening methodologies
- Novel behavioral screening methodologies
- Proprietary receptor targets and clonal cell lines
- High throughput pharmacological screening capabilities
- High throughput electrophysiology
Simulation
We have developed highly predictive computational drug design methodologies to specifically address the challenge of drug design in the absence of the protein target's structure. These proprietary methodologies include unique extensions of multidimensional pharmacophore mapping, quantum chemistry, quantitative structure activity methodologies, as well as machine learning systems and state-of-the-art grid computing technology.