The encyclopedia · R&D & Science · Operational decision · 2019–2021
Eli Lilly optimized its whole drug-development portfolio with one model.
Lilly and Carnegie Mellon built a mixed-integer tool that schedules every CMC activity in a drug portfolio, replacing manual R&D planning.
Eli Lilly and Company
the move
Pharmaceutical R&D constantly juggles which experiments, manufacturing steps and control tests run when, and with which people and equipment.
Lilly and Carnegie Mellon developed a mixed-integer linear-optimization tool that extends classic project-scheduling models to chemistry, manufacturing and controls, computing a portfolio-wide optimal schedule.
The tool runs at the operational level under sequencing, resource and deadline constraints, and also lets teams test how the system reacts to sudden changes.
why it works
- Many R&D projects compete for the same labs and staff
- Each project planned alone wasted shared capacity
- A mixed-integer model schedules the whole portfolio at once
- It also simulates how the plan reacts to a sudden change
what transfers
When many projects compete for shared labs and people, planning them together as one resource-constrained schedule beats each project planning on its own.
what came after
The tool gave Lilly a systematic, largely automated way to schedule CMC activity and re-plan under shifting priorities, showing how optimization can tame a complex R&D portfolio.
references
- Portfolio-Wide Optimization of Pharmaceutical R&D Activities Using Mathematical Programming
- Team creates software to optimize pharmaceutical development
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