Introduction:

In response to the evolving needs of a global pharmaceutical and healthcare company, the Real-World-Data (RWD) Indication Finder Capability was developed. This transformative platform aimed to revolutionise data-driven decision-making in the pharmaceutical industry.

Challenges Faced:

1. Limited ability to efficiently generate and validate hypotheses from RWD.

2. Complexities in interpreting and leveraging real-world data for indication finding.

3. Lack of user-friendly tools for non-analytics stakeholders to engage with RWD effectively.

Objectives:

1. Develop a platform for hypothesis generation and scientific validation using RWD.

2. Enhance usability and accessibility of RWD tools for a diverse user base.

3. Industrialize the approach through robust and user-friendly interfaces.

My Role and Methodology:

Design Strategy and Implementation:

• Redesigned use-cases to align with technology choices and prioritise intuitive visualisations.

• Improved user experience through standardised filters and intuitive placements.

• Facilitated value-mapping and operationalisation workflows to address user needs effectively.

• Collaborated closely with cross-functional teams to integrate design solutions seamlessly.

• Ensured effective handover of designs, minimising content iterations and maximising alignment with project requirements.
  
  

Key Pointers:

1. Ranked Indication Generation:

   • Implemented a robust algorithm to generate a ranked list of indications based on observed similarities in RWD.

   • Industrialised the approach through an intuitive and user-friendly interface, enabling efficient data manipulation.

2. Interpretation of Real-Time Data:

   • Transformed real-time data interpretation into a self-serving tool, empowering users to derive insights instantaneously.

3. Statistical Methods and Comparison:

   • Enabled the generation of statistical methods and facilitated comparison, enhancing decision-making capabilities.

4. Cross-Team Collaboration:

   • Provided teams across the organisation with the ability to interact and converse with their data, fostering collaboration and knowledge sharing.

5. Performance Enhancement:

   • Unlocked performance to deliver enhanced RWD capabilities, enabling the company to compare complex datasets rapidly and effectively.

Conclusion: Through collaborative efforts and a focus on user-centric design, the Real-World-Data Indication Finder Capability has revolutionised the pharmaceutical company's approach to data-driven decision-making. By leveraging intuitive visualisations, standardised filters, and seamless integration, the platform has empowered users to explore and interpret RWD effectively, driving innovation and advancing pharmaceutical research and development initiatives.