SERVICE

Developed a flexible and dynamic single click tool that reduced efforts by 4x time

Developed a Pre-launch tracker through a broad range of analyses like market assessment, competitive intelligence, etc.

We partner with our clients to establish a single source of truth for tracking market performance for the launch of a strong pipeline drug in a very complex Severe Asthma space

Times effort savings by a systematic approach

%

Additional penetration

“The level of automation incorporated in the process was outstanding. We are able to access the market insights in 1/4th of the time and with almost no manual intervention in the process.

D Cube Analytics has shown great attention to detail in not just meeting our requirements, but exceeding them.”

Objective

The client wanted to understand the overall Severe Asthma Market for an upcoming drug launch.

Hence, they required a data pack as a one-stop solution to get better insights of the market, understand the detailed classification of patients for key metrics like drug performance analysis, Source of Business Analysis, strength analysis for the closest analog, etc. using patient, sales and prescription level data which can be tracked at a regular cadence with automated refreshes.

Introduction

Used an analytical approach to develop an advanced algorithm to analyze the data and then outline the suitable KPI metrics and accurately reflecting the Severe Asthma population through extensive research and in-house domain expertise which helped the stakeholders to make key business decisions.

Solution

Collaborated and driven business rules discussions with customer team in finalizing the standardized business rules to be used for patient universe identification and KPI definitions.

Developed composite KPIs that provides insights around –

  • Biologics Performance Analysis: Understand the performance of the Biologics in recent time in terms of DoT trends and shares
  • Source of Business Analysis: Source of Business for all the Biologics (Bio-Naive, Bio-Switch, Continuing, Restart, etc.)
  • Treating Specialty Analysis: Specialties driving the treatment initiations and continuations

Developed master datasets by applying business rules and automated monthly PySpark code refreshes using data bricks notebook scheduler and migrated final tables from Databricks to Redshift.

Outcome

  • Pre-Launch Tracker captures Biologic Performance analysis, Source of Business analysis, Treating specialty analysis, and Dosage analysis which helped the customer to gain better insights and assess the market before launch
  • The data pack helped minimize the dependency on the analysts for quick turnaround analyses. Also useful for data science-related analysis as the data is already cleaned up and variables required are already present
  • Re-usable and modularized codes help in quick enhancements and easy refreshes to reduce the additional effort

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