Project Management Using R

Project management (PM) is crucial for life sciences projects due to their complexity and interdisciplinary nature. Effective PM ensures that projects are completed within the specified timeline, budget, and scope while meeting regulatory requirements and quality standards. Agile PM allows stakeholders to collaborate, communicate, and adapt to changing requirements, enabling life sciences projects to bring new products and therapies to market quickly and efficiently.

In the example below, we used the open-source programming language, R, to create a common PM tool – the burndown chart – that pulls from various sources to monitor and predict if a project is on target for completion.

The above example tracks different tasks for fixing a production process based on a customer complaint. Many regulatory agencies have strict deadlines for when to report/address complaints (e.g., 30 days after receipt). In our scenario, a complaint was received, and remediation tasks (see the legend) were tracked based on historical hours to complete. Just prior to the halfway point, the response was projected (using linear modeling) to be about a week late. This could result in fines, a warning letter, or worse (patient safety concerns, consent decree, etc.). 

Thanks to the predictive model, management was able to course-correct early (i.e., add another resource to help complete the corrective action, preventive action; CAPA) and finish the project early.