Decide which DDI studies you still need

What is at stake

Each clinical DDI study adds months, cost and volunteers. A verified PBPK model can answer some interaction questions without a study, and gives credible label language for the rest.

Question of interest

Which drug-drug interactions need a dedicated clinical study, and what should the label say about the others?

A PBPK model, verified against clinical PK and at least one clinical DDI study, predicts the effect of untested perpetrators or victims. Predictions inform which clinical DDI studies are run and support labelling where the model is adequately verified.

What reviewers will ask

Is the fraction metabolized by the enzyme verified clinically?

We verify it against an observed interaction, usually with a strong inhibitor, before simulating anything untested.

Is the platform qualified for this use?

We use the open PK-Sim platform and cite its published qualification for the interaction type, or explain why it does not apply.

How sensitive are the predictions to uncertain inputs such as Ki?

Sensitivity analyses on the parameters that drive the interaction are reported next to the predictions.

What you file with the agency

PBPK report following FDA's format-and-content guidance for PBPK analyses
Proposed DDI labelling text
Rationale for each clinical DDI study run or not run
Model files and simulation code for agency review

What we need from you

In vitro ADME and enzyme or transporter data (inhibition, induction, fm estimates)
Clinical PK data, including any completed DDI studies
Planned co-medications and the target label population

Predicted victim drug concentrations alone and with a strong CYP3A inhibitor, with variability bands and observed data overlaid. — PBPK verification against an observed interaction.

What it may replace

A verified PBPK model can replace some clinical DDI studies, for example with moderate inhibitors once a strong-inhibitor study has confirmed the metabolic pathway. Whether it can for your compound depends on the verification data, and we say so in the scoping call.

Scientific approach

Model building. Middle-out PBPK in PK-Sim (Open Systems Pharmacology), with compound parameters from in vitro data refined against clinical PK.

Verification. Prediction of an observed clinical interaction before any untested scenario is simulated. Acceptance criteria for predicted versus observed ratios are fixed in the MAP.

Prediction. Perpetrator and victim scenarios across dose, regimen and population, with virtual-population variability.

Sensitivity. Systematic sensitivity analyses on the parameters that drive the interaction, so the label proposal states how robust it is.

Relevant guidance: ICH M12 on drug interaction studies; FDA guidance on PBPK analysis reports; EMA guideline on the qualification and reporting of PBPK models; ICH M15.

Is this the decision in front of you?

Fixed price, paid in two milestones. A guaranteed date. Agency questions on this analysis answered at no extra cost. Pricing · How we work

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