What a freeze-thaw cycle does

Freezing a solution does not freeze it uniformly. Ice forms first from the purest water, which concentrates everything else, the peptide, the salts and the buffer, into a shrinking unfrozen fraction. That fraction can reach concentrations and ionic strengths far above the nominal values, and its pH can shift substantially as buffer components crystallise out at different rates.

The peptide also meets a growing ice-water interface, which is a surface, and surfaces are where peptides unfold and aggregate. Thawing runs the same processes in reverse, through the same intermediate states.

What makes a peptide sensitive

Aggregation-prone sequences suffer most, because the ice interface and the concentration effect both push toward aggregation. Larger peptides have more surface and more conformational freedom, so they generally fare worse than short ones. Peptides carrying oxidation-prone residues accumulate a separate kind of damage each time they spend time at higher effective concentration.

Dilute solutions are also worse off than concentrated ones, counterintuitively: a smaller fraction of the peptide is protected from the interface, and adsorptive losses are proportionally larger.

• •Aggregation-prone sequences: worst affected
• •Larger peptides: more surface, more conformational freedom
• •Dilute solutions: proportionally more interface exposure and adsorption
• •Oxidation-prone residues: accumulate a second kind of damage
• •Lyophilised powder: essentially unaffected

How to reduce the cost

Aliquoting is the intervention that matters. Twenty single-use tubes are each thawed once, instead of one vial being thawed twenty times, and it eliminates the accumulation entirely rather than slowing it.

Thawing slowly at refrigerator temperature, mixing gently rather than vortexing, and returning tubes to the freezer promptly all reduce the per-cycle cost. Self-defrosting freezers should be avoided outright: their defrost cycles warm the contents above freezing repeatedly, which is exactly the cycling aliquoting was meant to prevent.

Why this tool reports a range rather than a number

The model applies a per-cycle loss rate scaled by temperature, solvent and concentration. Those inputs are drawn from general observations about peptide classes, not from stability data on your peptide in your buffer.

That makes it useful for comparing handling plans, which is a relative question, and not for stating what is in a vial, which is an absolute one. The output is rounded to the nearest five percent to reflect what the model can actually support. Only an assay measures potency.

How the freeze-thaw risk is modelled

A per-cycle loss rate for the peptide class, scaled by storage temperature, solvent and concentration, compounded over the number of cycles.

loss per cycle = base rate x temp factor x solvent factor x conc factor
potency after n = 100 x (1 - loss per cycle) ^ n

temperature factors, relative to -20 C:
  -80 C: 0.7    -20 C: 1.0    2-8 C: 1.3    room: 2.5

1. 1Select the physical form. Lyophilised powder short-circuits the model, because there is no liquid phase to concentrate and no interface to form.
2. 2Take the base rate for the peptide class. A per-cycle loss rate reflecting how aggregation-prone and how large the peptide is. These are class-level figures, not measurements of any batch.
3. 3Scale by storage temperature. Colder storage between cycles reduces the damage accumulated while frozen, so minus 80 carries a lower multiplier than minus 20.
4. 4Scale by solvent and concentration. Bacteriostatic water fares slightly better than plain sterile water; dilute solutions fare worse than concentrated ones because more of the peptide meets an interface.
5. 5Compound over the cycles. Each cycle acts on what survived the previous one, so losses compound rather than adding. The result is rounded to the nearest five percent.

What this method cannot tell you

• •The base rates are class-level estimates, not measurements. Two peptides in the same class can differ substantially.
• •It does not model your buffer's specific behaviour on freezing, which is where much of the real variation lives.
• •It reports modelled potency, not measured potency. Only an assay measures what is in the vial.
• •It cannot detect aggregation that has already occurred, which is often the failure mode that matters most.