Our decade long experience in the development of research and algorithm based analytics, has resulted in an industry leading proprietary platform that combines the efficiencies of big data analytics and machine learning based artificial intelligence with highly specialized expert teams in drug discovery and development.

Our two platform technologies are being commercialized by Inveni Corporation

PharmGPS® provides an unprecedented opportunity to systematically and efficiently analyze, screen and match a pharmacological space (the right drug) to a disease pathophysiological space (the right disease) to the most applicable molecular targets, while mapping this with a patient journey (the right patient population) to develop the next wave of medicines that will ultimately benefit patients, the community, and the healthcare system.

PharmGPS® also provides an additional competitive advantage in the therapeutic development process with real-time analytics that provides standard of care (SoC), product opportunities, key market movers, product blueprints, portfolio impact, and go to market launch scenarios for all major therapeutic areas and especially the rapidly growing immuno-oncology space. The platform also permits the identification of disease and patient segments with unmet need and limited competition to prioritize the initial discovery efforts.


Evolvere is designed to optimize therapeutic value of diseases, disease biology, therapeutic modalities and drugs. Starting from the universe of disparate information with a well defined question, our partners leverage Evolvere to augment R&D decisions by performing complex therapeutic area focused queries, with hundreds-to-thousands of proprietary therapeutic area specific pharma probes designed by our drug discovery and translational experts. This query and analysis is conducted using multiple pharma probes in an iterative fashion by scanning pharmacological and pathophysiological data lakes (text and quantitative) at what we believe is at an unprecedented speed. This results in robust disease association maps or Galactic Maps that generate a comprehensive analysis of a given disease state with first, second, and third degree interactions and network-based relationships between genes, pathways, pharmacology and pathophysiology. The Galactic Maps become the ‘‘screening library’’ that is further analyzed using proprietary and predictive algorithms to identify new therapeutic hypotheses, (right drug-right disease-right patient), that have a high likelihood of clinical and regulatory success.