Case Studies

Check out some of our success stories below


Innovating to provide a competitive edge to our big pharma clients in the development of super specialty novel therapies.

Business Challenge

A major pharmaceutical company wanted to accelerate the development of a novel therapy line and identify where and how it can differentiate its early stage assets.

Our approach

  • We did an end-to-end mapping of clinical and pre-clinical activities and a deep dive across the scientific ecosystem. Our capabilities allowed us to screen public data for key assets, existing capabilities, pipelines and resources in the innovation ecosystem.
  • We could identify early stage assets by landscaping competitor activities and related developments. This helped us anticipate competitor strategy and identify key opportunities and possible risks to our programs.
  • We then extracted development information from scientific studies, clinical and pre-clinical activities and, key research and market information from public data.
  • We used network analysis to identify peripheral capabilities that can be leveraged for innovation.



We used proprietary algorithms to collect and assimilate data from specialized public databases. Leveraging Ontologies, the datasets were normalized and were given a frame of reference with respect to the development target.

Further, processing was done using network analysis algorithms to study momentum of IP as well as potential hotspots for exploratory innovation. This enabled the client to make informed decisions, minimize risks and identify niche opportunities.


Augmenting information with respect to specialization of nurse practitioners and physician assistants for targeting of physicians associated with the same.

Business Challenge

The task of identifying and engaging physicians with high market potential and diffusion degree is quite challenging. Hence, it becomes vital to identify the respective nurse practitioners and physician assistants who can bridge the gap of reaching out to the physicians given the resources and budget.

Our approach

  • Leveraging our DaaS platform – iPlexusTM, we extracted information related to medical assistants such as specialization, field of interest, geographical location etc. This data belonged to multiple sources like institutes, IDNs, hospitals, networking sites, associations and more.

  • Structured and unstructured data was tagged to identify sections of the page/content having relevant information.

  • Using our proprietary name normalization technique, the names of all the medical assistants procured from multiple public data sources were normalized. The concept based tagging of entities also resolved the issues pertaining to multiple records of a single profile.

  • While extracting and tagging relevant information such as specialization of the medical assistant, the source of information was prioritized based upon the type of source (e.g. individual website, aggregator etc.) and the exclusivity and non-conflicting information within the source. This enabled us to provide a confidence index to each piece of information that was extracted, assisting the client to understand the accuracy of the extracted information.



An automated and real time system was developed providing detailed profiles of the medical assistants. It helped our client in strategizing marketing initiatives to cover maximum physician network, hence maximizing ROI.

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