Comparing modelled curves to real lab data

A worked example of anchoring the DoseCurve chart to a single bloodwork point — what the calibration tells you, what it doesn't, and how to read subsequent results in context.

A modelled mg-remaining curve from DoseCurve and a measured serum value from a real lab are not the same kind of number. The chart is in milligrams; the lab is in nanograms per decilitre. Converting between the two requires assumptions about volume of distribution, bioavailability, protein binding and assay technique — none of which DoseCurve estimates. But if you have even one measured lab value at a known time relative to your last injection, you can use it to anchor your personal sense of where the chart sits in serum terms.

This post walks through how. It is a thinking aid, not a clinical workflow. Any actual interpretation of your bloodwork belongs with the clinician who ordered it.

The setup

You're three months into a stable schedule. The DoseCurve chart is well past steady state and shows a steady-state oscillation between, say, 140 and 195 mg over each week. You get bloodwork drawn. The lab reports your total testosterone as 720 ng/dL. The phlebotomist noted the draw happened six days, four hours after your most recent injection.

Two pieces of information matter:

Where does the modelled curve sit at six days, four hours after an injection at steady state?
What is the ratio of measured ng/dL to modelled mg?

Reading the chart at the right time

In DoseCurve, hover the chart at the matching day and timestamp. Suppose the model reads 158 mg at that moment. Your measured value is 720 ng/dL. Your personal ratio is:

720 ng/dL / 158 mg ≈ 4.6 ng/dL per modelled mg

That ratio is now a calibration constant for your specific physiology, formulation, technique, lab assay and protein-binding profile — at this moment in time, with this schedule. As long as none of those change much, you can apply it to any subsequent point on the modelled chart to get an approximate serum-equivalent.

What the ratio includes

The ratio you computed silently bakes in:

Bioavailability of your formulation as administered.
Your volume of distribution at the time of the draw.
Your protein-binding profile (SHBG, albumin) at the time of the draw.
Your clearance, which sets the steady-state level.
The lab assay's measurement technique and reference range.

It is a personal, time-stamped calibration. It is not a universal conversion factor and you cannot share it with another person.

What changes the ratio

If any of the underlying factors changes substantially, the ratio drifts. Common drivers:

Body composition change. Substantial fat loss or gain shifts Vd for lipophilic drugs.
Liver or kidney function change. Shifts clearance.
Concurrent medication starts or stops. Particularly drugs affecting hepatic enzymes or protein binding.
Formulation change. Different ester, different brand, different route.
Lab change. Different assay, different reference range.
Significant time gap. A ratio measured a year ago may not apply now if any of the above has shifted.

When you suspect the ratio has drifted, redo the calibration with a new lab point.

Worked example: anticipating a dose change

Take the previous example. You and your prescriber are considering a 20% dose increase. The model predicts the new steady-state mg-remaining at the same time point will be about 190 mg. Applying your ratio:

190 mg × 4.6 ng/dL/mg ≈ 874 ng/dL

So if your physiology is stable, the new dose at the new steady state should produce a level around 874 ng/dL drawn at the same time relative to injection. That number is a prediction, not a guarantee. The actual lab will tell you how close you got. If it lands within ~15% of the prediction, your ratio held. If it lands very differently, something in your underlying physiology has likely shifted, and the conversation moves from "is the dose right" to "why didn't the model behave as expected".

What this is not

Not a way to skip bloodwork. The whole point of the calibration is that it depends on having labs. You can't do this with zero data.
Not a substitute for prescriber judgement. Anticipating a likely lab value is useful for planning the timing of a follow-up draw. It is not a clinical decision.
Not transferable. Your ratio is yours. A friend's ratio on the same compound and dose will not match.
Not perfectly stable. Physiology drifts. Re-anchor periodically.

Where the method works well

This calibration approach works best on:

Stable, established protocols where physiology has had time to settle.
First-order kinetics (most injectable hormones at typical doses).
Single-compartment-friendly time windows — sample times that aren't right after the absorption peak.
Single-substance protocols without complicating active metabolites contributing to the measured assay.

Where it works poorly

Mixed-ester or blend products where multiple half-lives contribute.
Compounds with substantial active metabolites that get measured by the assay (e.g. measuring nandrolone in someone also using testosterone, where some testosterone might cross-react depending on the assay).
The early absorption phase. The single-exponential DoseCurve model doesn't capture the absorption peak from an oil depot. Calibrating on a sample drawn in the first 24 hours after an IM injection will give a ratio that does not generalise.
Acute physiological changes like sudden weight loss, intercurrent illness or new medications. Calibrate after things settle.

How often to recalibrate

A reasonable default: any time you have new bloodwork, recompute the ratio and see if it still matches. Small variation is expected (lab assay variability alone is typically 5–10%); large variation is a signal that something has shifted underlying. Your prescriber is the right person to help interpret that shift.

Bottom line

The chart shows the shape your protocol produces. A single lab gives you a personal scale factor that turns the shape into approximate serum terms. Together they're a more powerful planning tool than either one alone — but they don't replace ongoing bloodwork or clinical oversight.