Capacity Planning for Radiopharmaceutical Therapy - Making the Clock an Ally

Radiation‑therapy manufacturing doesn’t behave like traditional sterile fill‑finish. Capacity isn’t just about headcount, rooms, and equipment—it’s about physics. Activity decays every minute, upstream isotope supply is lumpy, and release decisions sit behind validation and transport constraints. Below is a practical way we help teams get control without boiling the ocean.

Why radiopharmaceutical therapy capacity planning is uniquely hard

• Time eats inventory - Potency declines continuously; what you “made” at 08:00 is not what you ship at 16:00. This ties capacity to when you run, not only how much you run.

• Supply is stochastic - Reactor/cyclotron output, import schedules, and generator yields introduce variability that standard MRP rarely models well.

• Finite, specialized resources - Hot cells, shielded isolators, dose calibrators, and qualified operators are true bottlenecks; cleaning/validation changeovers compress available blocks even further.

• Release gates - QC/QA steps (HPLC, endotoxin, visual inspections, documentation review) drive the critical path; some sites “ship at risk” with post‑shipment QA, others do not.

• Regulatory shipping windows - Class‑7 packaging, carrier cutoffs, and license checks at ship‑to sites create narrow dispatch windows.

  
  

Planning principle #1 - Start from the patient, work backward

Anchor schedules on T0 = patient administration time. Every upstream activity (pack, QA checks, fill, material prep, isotope receipt) should have a T‑minus time and a tolerance band. The basic math is simple—activity at time t equals the starting activity times an exponential decay—but its implications are profound: capacity is time‑sensitive.

What it looks like in practice

• Define a slot bank by therapy, day, and site (e.g., “Lu‑177: 12 admin slots Tue/Thu”)

• Tie each slot to a potency window and a shipping cutoff; only open slots when upstream capacity is reserved

  
  

Planning principle #2 - Make capacity planning bottlenecks explicit

Map and model finite resources

• Hot cells / isolators (by room and campaign rules)

• QC benches / instruments (run times, queue times, setup/teardown)

• People (qualified roles; shift patterns; radiation exposure/ALARA limits)

• Licensing & logistics (ship‑to approvals, carrier pickup windows)

A lightweight finite‑capacity model that respects these constraints will outperform any spreadsheet that assumes infinite QC or “instant ship.”

Planning principle #3 - Separate horizons (and link them)

Use three connected layers

1. Strategic (4–12 weeks) - Isotope procurement, campaign frequency, slot bank by therapy/site; what demand we commit to

2. Tactical (1–3 weeks) - Detailed hot‑cell sequences, cleaning/validation windows, QC staffing; what we intend to run

3. Operational (today–72 hours) - Day‑of dispatching, rescheduling when a test fails or a courier slips; what we actually run

The hand‑off is data, not slides: available‑to‑promise becomes “available‑to‑potency.”

The minimum data set (don’t skip this)

• Decay constants & reference activities by product (and units).

• Shelf‑life & potency specs at administration (lower bounds, adjustments).

• Process times: prep, fill, test, review, pack; with min/max, not just averages.

• Resource calendars: hot cells, QC, operators (incl. cross‑training and shift rules).

• Logistics: lane times, carrier cutoffs, dangerous‑goods paperwork times.

• Regulatory gates: ship‑to license checks, release authority, validation status.

A 30‑day, no‑drama starter plan

Week 1 — Map & bound

• Draw the T‑minus timeline for one therapy from dose to patient.

• List bottlenecks (cells, QC, people) and their daily hours.

Week 2 — Put numbers on time

• Capture process times and variability (min/typical/max); capture decay and potency windows; confirm shipping cutoffs.

Week 3 — Build a small model

• Create a simple finite‑capacity schedule (spreadsheet or light tool) that books slots only when hot‑cell + QC + courier windows line up and potency stays in spec.

Week 4 — Pilot & learn

• Run two scenarios (steady week, disrupted week); measure misses and rework; adjust slot counts and buffers.

  
  

Metrics that actually help

• On‑time release to pickup (% lots ready before courier cut).

• Hot‑cell utilization (by room/campaign), including lost time to changeovers.

• QC throughput (tests/day; queue time; first‑pass yield).

• Decay‑adjusted yield (activity at pack vs. at admin).

• Slot plan adherence (slots booked vs. executed; cancellations; late reschedules).

• Patient service level (met appointment window without exception).

Common traps to avoid

• Infinite‑QC spreadsheets - If QC isn’t finite in your model, your plan isn’t real.

• Potency blind spots - Planning by volume instead of potency at admin time.

• One giant meeting - Capacity control is a cadence, not a workshop—separate strategic, tactical, and day‑of cycles.

• Too many SKUs, not enough rules - Use campaigns and changeover matrices to standardize where you can.

• Ship‑at‑risk without a plan - If you use it, define evidence, responsibilities, and reconciliation before you need it.

Where teams usually ask for help

• Turning a rough spreadsheet into a finite‑capacity model that accounts for decay and release gates.

• Designing a slotting policy and promise rules that Sales and Ops both trust.

• Mapping validation & SOPs to the plan so “what we run” and “what we document” stay in lockstep.

• Standing up simple, role‑based dashboards (hot‑cell/GMP rooms, QC benches, courier windows) that drive the day.

• Selecting and implementing Capacity Planning software to support business requirements.

  
  

If you’re searching for help with radiopharmaceutical therapy capacity planning, decay‑aware scheduling, finite‑capacity models for hot cells/isolators, QC release gates, risk‑based validation, campaign sequencing, potency at administration, slotting/available‑to‑potency (ATP), isotope supply variability, Class‑7 packaging and carrier cutoffs, customer license checks at ship‑to, or ship‑at‑risk policies, then this guide is for you. I’m happy to share a simple model and templates if that would help your team get moving.