Binary Republik was supplied with raw data from Pinscriptive. The task involved processing the data using adaptive algorithms capable of identifying Hepatitis C patients. Additionally, this process encompassed the removal of irrelevant data from the aggregated dataset.

This system was designed specifically for use by physicians, healthcare providers, insurance companies, and pharmacists.

Employing diverse adaptive algorithms and big data analytics techniques, we processed the data and presented it to specialized doctors for authentication. Further segmentation of the data was required based on the users utilizing the system.

We needed to develop an architecture and platform that would be beneficial for various user groups, considering the processed data. This processed data was visualized using custom visualization tools, including Python and various other technologies.

Data analysis is conducted using a set of algorithms to uncover correlations within the clinical data. Subsequently, various charts are generated to visually represent the clinical data. Predictive analytics are then applied to further analyze the data, determining the optimal drug for the patient while considering the ideal scenario. Additionally, predictive models are developed based on the received data to forecast outcomes for unknown patients.

Therefore, this tool proves valuable for specialty biopharmaceutical manufacturers, providing a model that transitions their products "from volume to value." It supports risk-based contracts with precision analytics, thereby boosting sales, fostering innovation in specialty drugs, managing healthcare budgets, and offering insights into current market trends and scenarios.

This product will facilitate the delivery of insights into specialty drug usage and costs, harnessing the power of Big Data analytics, a suite of proprietary algorithms, and the integration of real-world data from Electronic Medical Records (EMRs).

By employing machine learning, population analytics, and leveraging existing knowledge and experience, this tool aids in managing specialty drug trends, thereby enabling the implementation of a disruptive pricing model.

Assists insurance companies, patients, and their physicians in discovering cost-effective specialty drug solutions by identifying the precise drug for the right patient at the appropriate price

Most precise data regarding Hepatitis C patients.

Assists payers, at-risk health systems, and accountable care organizations in optimizing specialty drug decisions through foolproof decision-making, taking into account both quality and cost insights.

Clients can access visualizations to gain insights into the market landscape.

Physicians can determine whether the data is missing or if the treatment is incorrect.