Clinical Trial Feasibility, Planning and Forecasting
Discovery and design of a clinical trial feasibility & planning product, with data-driven insights & active decision making, of pharmaceutical sponsors, RWD and benchmark-integrated data.
The Challenge: Modernizing feasibility and forecasting to reduce risk in planning for a more predictable outcome of clinical trial completion.
The client engaged with Windmill Digital Healthcare, to support them in the Discovery, Design Thinking led Sprints and Designs of a new forecasting intelligence solution incorporating predictive analytics. The proposed solution would incorporate integrated data, powering the clinical trial planning and forecasting workflow.
Why the client chose Windmill Digital Healthcare
Windmill Digital Healthcare was enlisted to design the solution, due to their understanding of the complexities and dependencies of multifaceted data and business intelligence, across complex sectors, including life sciences and financial modelling. Previous projects delivered, demonstrated capability of designing products for decision making in planning, forecasting, benchmarking, analyzing, comparing, and reporting.
Windmill Digital Healthcare (WMD HC) demonstrated its ability to understand user-workflows and grasp challenges of buyer and decision-making requirements. This resulted in designing digitized experiences that clearly simplified processes, visualized complex data storytelling, across many data points and data layers.
How Windmill Digital Healthcare Responded
WMD HC engaged with the client to conduct multiple stakeholder discovery interviews from the Pharmaceutical and Life Sciences industry, to understand the user and buyer needs, challenges, and gaps in the current clinical trial feasibility, planning and forecasting processes, and determine opportunities for differentiation to other solutions currently on the market.
The Windmill team worked in parallel with the client’s data science team, to incorporate the complexity of the data and associated predictive AI-models into its designs.
The Windmill team contributed towards translating the front-end visuals into requirements, further enhancing the value of a complex SaaS solution, to ensure success of the future developed product.
Impact
The product designs captured the requirements of the stakeholders, for consistently positive feedback for its ability to simplify the complexity of the tasks through its designs and proposed workflow and its prescriptiveness for decision making.
A prototype was delivered that gained excellent traction from the clinical trial community in individual stakeholder meetings, and at a major industry conference, with feedback demonstrating its differentiation to the current solutions on the market.
