Automating Clinical Development

The Problem: A leading biopharma experienced incredibly rapid growth in the past few years. Capitalizing on their revolutionary technology, they resolved to take a platform-based approach to clinical research and development, enabling an impressive potential portfolio of new therapeutics. But that rapid pace also created a need, to replace previously manual or non-optimized solutions with a digital services and processes to match the company's strategic vision. The most prominent of these needs was to to up-level the processes and systems supporting clinical development.

The Solution: Implement a suite of software solutions, incorporating both vendor software and in-house builds, to automate and streamline the greatest pain points within clinical development process, including:
- Overhaul and and enhancement of LIMS systems supporting clinical biomarkers and supply, across multiple labs and two continents
- Restructure the digital teams supporting clinical systems, moving from a chaotic "throw bodies at the problem" mindset to a sustainable resource model
- Internalize costly vendor-managed solutions governing clinical trial planning, analytics, and budgeting
- Rapidly build, test and evaluate multiple proof of concepts for clinical trial cost forecasting and analytics
- Build a GPT-based tool to rapidly parse and ingest incoming data files from clinical sites and CROs
- Select and implement an solution to streamline risk based quality management

My Role in the Project: As the Senior Director for Product Management, I led the technical side of these initiatives. Within the clinical biomarkers and supply group, I managed a cross-functional team of application and data engineers, product and program managers, business analysts and computer systems validation leads. I successfully transitioned from expensive vendor-supplied external software to unified, secure, and scalable internal solutions, building a foundation to support development activities across the company's clinical portfolio. In this capacity I worked closely with a wide variety of business and technical partners, managed relationships with external vendors, and provided oversight to the company's executive leadership.

Metrics of Success:
- Clinical Biomarkers new study configurations completed within average two-week timeframe
- Reduction in custom coding for analytics and reporting (labs) to less than 20% (from 90%)
- 80% of budget file formats supported by automated data ingestion tool (within two months of initial deployment)
- Successful transition of externally-built reporting and analytics solution to functionally equivalent internal tool, within a secure data warehouse