Under constant pressure to reduce the cost of drug development, many biopharmaceutical companies and CROs are looking for ways to improve their capacity planning and resource allocation. It is critical for clinical organizations to find a better approach to increase effectiveness in resource capacity planning, especially for a portfolio of clinical trials. An optimal capacity planning solution includes proper resource utilization, allocation between ongoing and new trials, outsourcing strategy, hiring trend and budget allocation strategy for a variety of employee roles, and resource reallocation due to new or cancelled trials. It means identifying resource bottlenecks and optimal scheduling of new trials.

In this presentation, the speaker discusses a powerful decision-making methodology based on rigorous mathematical models for optimal capacity planning and resource allocation in clinical research, a technique which has been shown to reduce costs by up to 30% in some cases by uncovering better resource allocation solutions.

This audio conference covers:

• How to apply optimization technology to capacity planning in biopharma
• How to optimize capacity planning and resource allocation across a portfolio of clinical trials
• How to identify resource bottlenecks using optimization tools
• How to reallocate resources due to inclusion or cancellation of clinical trials
• How CROs can define maximum “throughput” of clinical trials based on current and projected manpower supply, as well as clinical trials allocation across therapeutic areas, and stages of development

About the speaker:

Vladimir Shnaydman, President of ORBee Consulting is responsible for overall operations of the company, developing mathematical models and software. He has made contributions to many industries, including life sciences, computer networking, manufacturing, transportation, hydrology and water resources. Prior to founding ORBee Consulting, Vladimir worked at Biogen Idec, EMC, Netcracker Technology, Tufts University and Russian Academy of Sciences, developing modeling solutions to improve efficiency in planning, operations, and performance analysis.

Vladimir earned Bachelor and Master of Sciences degrees in Electrical Engineering and Computer Science, and a Master of Sciences in Applied Mathematics from Moscow State University, as well as a Ph.D. from Russian Academy of Sciences. He has authored more than 50 papers and co-authored three books.

Who should attend?

• Clinical Operations
• Finance
• Engineering/R&D
• Marketing & Business Development
• Business analysts