Simulation for Pharmaceutical Manufacturing
Where Capacity Is Constrained by Rules, Not Just Rates
A pharmaceutical line is a manufacturing system with a regulatory system wrapped around it. Batches cannot be interrupted, changeovers carry validated cleaning, material waits on quality release rather than on a conveyor, and the constraint is frequently a step where nothing is physically happening at all.
Who has used it
Eli Lilly · Genentech · Glaxo Wellcome · Pfizer · Teleflex · BioPharm Services
Why the usual throughput analysis misses here
Most capacity arithmetic assumes the constraint is a machine running too slowly. In pharma the binding step is often a wait: a hold for quality release, a validated clean between products, a stability or sterility check that takes as long as it takes. None of those go faster when you buy more equipment, and none of them show up as downtime on a machine report.
That makes the plant a coupled system in which the couplings are procedural rather than mechanical — and it is exactly the case where averages mislead. A step that is idle 80% of the time can still be the constraint, because what matters is when it is available relative to when the batch needs it.
What tends to be binding
Quality hold and release
Material that is physically finished but not yet releasable occupies space, ages, and blocks the step behind it. Release time is variable and largely outside operations’ control, which is precisely the kind of variability that has to be modelled rather than averaged.
Validated changeover and cleaning
Changeovers are not a setup time to be squeezed — they are a validated procedure. That makes campaign length a real commercial lever: longer campaigns amortise the clean but build inventory and reduce responsiveness, and the optimum moves with product mix.
Batch integrity
A batch that cannot be split or interrupted couples upstream and downstream far more tightly than a continuous flow does. Buffering between them is constrained by hold times and stability, so the usual answer — add storage — is bounded by chemistry and by the filing.
Shared suites and utilities
Suites, vessels and clean utilities shared across products couple lines that look independent on a flowsheet. The interaction only appears over time, under a real campaign schedule.
The pattern is the same one this whole site is about, in a stricter setting: the loss report ranks by minutes lost, but what you want ranked is recoverable throughput — what the line actually returns when a constraint is relieved. In a regulated plant, several of the biggest entries on that report cannot be relieved at all, which makes ranking by recovery more important, not less.
Related work on this site
The same mechanisms, documented on other lines:
Buying time instead of buying a line
Two stages that had to run in lockstep, separated by stabilising the intermediate. The direct analogue of a hold-time constraint: what a buffer is worth depends on how long material may legally sit in it.
Run the simulator → Campaign SchedulingThe bottleneck that would not stay still
Change the product format and the constraint relocated, defeating a planning system built on a fixed bottleneck — the campaign-scheduling problem in another industry.
Read the case study →Where to start
The browser sandbox runs a rate-based line with no download and no sign-up. Everything is desktop-native and air-gap compatible — your process data never leaves your network, which in a validated environment is usually the first question asked.
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