Core Facility Numbers: The Grant Calendar, the Recharge Rate and the Lines That Grow
By PlainSight — Insightful Actions · Updated October 2026 · ~8 min read
A cell and molecular biology lab that bills — a university core facility, a departmental sequencing or imaging core, a small contract lab — runs on a few numbers the grant calendar sets for it: what came in by lab, by service and by funder; which month carried the year and which was quiet; how much of the money is one account; and whether the lines that are growing everywhere (NGS, authentication) are growing here. This guide names them, says what good looks like, and shows the arithmetic on an example book.
Where your numbers live
Your billing or recharge system (iLab, Stratocore, a departmental ledger, or the spreadsheet the manager keeps) exports one row per job: the date, the lab or account billed, the service, the platform it ran on, the account's funding source if you record it, and the charge. That is the whole file PlainSight needs. No sample identifiers, no protocol data, no names of people — the lab's name is enough, and the file never leaves your browser.
The numbers that tell you the core is set up for the whole year
1. Money by month, against the same month last year
What good looks like: each month ahead of its own last year, and September understood as the rush it is.
The US federal fiscal year ends September 30 and every NIH budget period ends on its own anniversary, so labs spend what is left in the weeks before both. Compare each month with the same month a year earlier, not with the month before; then read the holiday weeks for what they are. In the example book, September is the busiest month and late December into January brings in about half of it.
2. The mix by platform: sequencing, molecular, imaging, cytometry, cell services, training
What good looks like: the lines that grow everywhere growing here.
Add each platform's share of the year, then do it for the year before. NGS library prep and sequencing grow in nearly every core; Sanger slips as vendors take the big batches; authentication and mycoplasma testing grow because journals and NIH ask for them. In the example, sequencing is 46% of the year, with NGS up about 18% a year and Sanger slipping.
3. Concentration: your largest account's share
What good looks like: known, and under the limit your institution's recharge rules set for outside and industry users.
Divide each lab's billing by the year's total and read the top three. An industry account that pays a higher tier can become your largest client without anyone deciding it; that is steady money and a question your rate review will ask. In the example, one company is about 18% of the year, and industry accounts together are a fifth of the jobs and about 31% of the money because they pay about 1.8× the academic rate.
An example, to show the arithmetic (not a benchmark)
| Account | Jobs | Share of the year | Rate tier |
|---|
| A company account | About 1 in 10 | About 18% | Industry, ~1.8× academic |
|---|
| The largest academic lab | About 1 in 6 | About 15% | Internal recharge rate |
|---|
| All industry accounts | About 1 in 5 | About 31% | Industry |
|---|
4. The recharge rate against actual cost
What good looks like: reviewed once a year, breaking even over time, the subsidy explicit.
A university core bills its own institution's labs at a rate that recovers direct costs — service contracts, reagents, the hands that run the instrument — and US federal cost rules (2 CFR 200.468) require a recharge rate to break even over time, not profit from federal awards. Put the year's billing beside the year's costs by platform; the platform that never breaks even is the one to re-price or to subsidize on purpose.
5. Authentication and mycoplasma testing: lines, and the share of lines you see
What good looks like: every line in and every line out, tested.
Count cell line authentications (STR profiling) and mycoplasma tests by month, and divide by the lines your core handles. NIH expects key biological resources — cell lines among them — to be authenticated, in a plan attached to every application since January 2016 (NOT-OD-15-103); ICLAC's register lists 608 misidentified lines, 560 with no authentic stock known, and HeLa is 145 of them. In the example, authentication is the fastest-growing service — about 170 lines a year, up about 30% — and mycoplasma testing about 300 samples.
6. Turnaround, as a number you meet
What good looks like: a published turnaround per service, met on nine jobs in ten, and a note when it won't be.
If your system records the date a sample arrived and the date results went out, the difference is the number labs judge you on before anything else. Read it per service, and read September separately: a core that meets its turnaround in April and misses it in September has a staffing calendar, not a turnaround problem.
7. Instrument hours sold against hours available
What good looks like: assisted hours where new users are, unassisted where trained ones are, and a replacement schedule written down.
Imaging and cytometry sell hours. Divide the hours billed by the hours an instrument could run; a confocal at 20% has room, a sorter at 80% needs a second shift or a second instrument. In the example, imaging and cytometry together are about 19% of the year and the steadiest lines in it.
8. Training, and the users it makes
What good looks like: small money that pays twice.
Count training sessions and the users who then book unassisted hours. A trained user books more hours and breaks fewer instruments; the fee is the smaller half of what training earns.
Warning signs worth acting on
- A September that misses turnaround every year — the calendar is known; the staffing isn't planned for it.
- One account over a quarter of the year — ask your institution's rate and outside-user rules before it asks you.
- Authentication flat while every journal asks for it — usually a service nobody offers at intake, not one nobody wants.
- A platform billed below its service contract — a subsidy nobody chose.
- Favors and departmental jobs with no record — the usage case for the next instrument is being thrown away.
Make it a monthly rhythm
Export the billing once a month and read it three ways — by lab, by service and by funder — each against the same month last year. Pick the one gap worth closing this month: a line to offer at intake, a rate to review, a September to staff. Then check it next month.
Let PlainSight read your billing
Upload a billing export and PlainSight breaks the year down by lab, service and funder, shows the grant-year shape, finds the concentration and the growing lines, and writes the specific next step in plain English — with The Bench beside it: the desk's lectures and techniques, the bench's links and four calculators.
See it on a live example →
Running or starting a core? Read the free handbook · Open The Bench
Frequently asked questions
- What file does PlainSight need from a core facility or contract lab?
- A billing export with a date, the lab or account billed, the service and the amount. A platform column and a funding-source column add those cuts. No sample identifiers, protocol data or people's names are needed, and the file is read in your browser.
- Is a PI's own lab a fit, or only a core?
- PlainSight reads a book of money in, so the fit is the lab that bills: a core, a contract lab, a biotech services bench. A PI's lab is usually a customer of one; its own spend by grant and category is a different book. The Bench — the desk, the links and the calculators — is for both.
- Is my data safe if I use PlainSight?
- Yes. Files are processed entirely in your browser and never uploaded. Optional AI features send only anonymized summary totals, never names or raw rows.
- How much history do I need?
- One month shows billing by lab and service. Twelve months shows the grant-year shape, and two years shows each month against its own last year.
- Is this regulatory, safety or medical advice?
- No. Biosafety, select agents, human-subjects and animal protocols, export controls and your institution's recharge and cost-accounting rules all apply first; follow them and your biosafety officer. This is general information, not legal/tax advice.
Sources
- International Cell Line Authentication Committee, Register of Misidentified Cell Lines, version 14 (15 February 2026): 608 cell lines, 560 with no authentic stock known, HeLa the commonest contaminant (145 entries).
- National Institutes of Health, NOT-OD-15-103, Enhancing Reproducibility through Rigor and Transparency (June 2015): authentication of key biological and/or chemical resources, for applications from the January 25, 2016 due date.
- National Institutes of Health, NOT-OD-25-105, NRSA stipends for FY 2025 (May 2025): postdoctoral year 0 $62,232; predoctoral $28,788.
- National Human Genome Research Institute, DNA Sequencing Costs: Data: what the cost series counts, and the January 2008 move from Sanger to second-generation sequencing.
- US Office of Management and Budget, 2 CFR 200.468, Specialized service facilities: recharge rates that break even over time.
This guide is general information for people who run or use a cell and molecular biology core or contract lab, not financial, legal, safety or medical advice. Recharge, biosafety and cost-accounting rules vary by institution and funder. This is general information, not legal/tax advice.