Regulatory Aspects of PK/PD – (modelling)

Karolina TörnekeSenior expert, member of the CVMP

Part 1A-CAdministrative data and product information

Part 2Pharmaceutical documentation

Part 3A-BPharmaco/toxicological and residue documentation

Part 4.1 Clinical pharmacology and toxicology

Part 4.2 Clinical trials

Why use PK/PD (modelling)?

It increases the amount of information available It reduces the risk for ”PK-bias” It enables species comparison

Even if the guidelines don’t talk about PK/PD as mandatory, integration of PK and PD data could be very informative and helpful

Collect PK data in experimental studies Discuss PK and PD data in an integrated way Use any model that could be justified

dependent on the size and quality of the dataset

If no model fit – present the data anyway!

Safety assessment – ”Antibact”

50 mg/kg: all experienced serious adverse reactions.30 mg/kg: 4/520 mg/kg: 1/80-15 mg/kg: zero events

Can 5-20 mg/kg be regarded as safe?

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Antibact plasma concentrations vs adverse reactions

Lowest observed adverse effect conc.

Individual data

Geometric mean ± SD

Use all available data!

The ”Painkill” example

How to find the dose for a new specieswhen several species are approved already with different doses?

Painkill is approved for several species…

But pharmacokinetics might differ between species, e.g. differences in total body clearance and protein binding level might be prominent. And pharmacodynamics might differ, e.g. potency or potency ratio for COX. There might also be differences in disease pattern

So before Painkill can be approved for a new species new clinical documentation on dose finding must be presented. Then PK/PD might be a valuable shortcut.

PD data for Painkill were never related to PK

TXB2 concentrations measured at several time points. Results: Sex differences were recorded (lower TxB2 concentrations in females). The effect peaked at 1 h with 70 % inhibition of baseline values. At 24 h the inhibition was 40 %. Plasma concentrations of painkill measured at the same time points. Results: AUC was larger in females than in males. There was a pronounced feed interaction recorded.

Clearance for painkill:

Sp 1: 1 (standardized unit/kg bw) Sp 2: 5The dose differed accordingly and the systemic exposure was similar!

New species: 5

Knowledge about the PK/PD relationships for efficacy and safety is important for the development of appropriate dosing recommendations. The pharmacodynamics could be altered in renal impairment, which could lead to altered PK/PD relationships.

(EU NfG Renal impairment studies (2004))

Bridging to special patient groups

Pharmacogenomics!

What is important from a regulatory point of view?

The best and most advanced of all study designs might give results that are useless for assessors!

The regulator’s golden questions

Is the benefit/risk positive? Is adequate and sufficient information presented in the

SPC?

If both those questions could be answered and the

answer is “yes” to both then the rest is “nice to know”!

Zeal to be a front runner?

Industrial scientist

Regulatory scientist

Academic scientist

The objectives should be predefined. The PD endpoint should be predictive for a relevant clinical effect. Relevant subjects should be included. The number of included subjects should be adequate. An appropriate dose span should be covered when PK/PD modelling is used in dose finding.

Appropriate objectives?

PK/PD-modelling could give valuable information – if clinically relevant data is collected:

The endpoints should be relevant for the suggested indication including choice of bacterial species. A “dose limiting strain” should be used (i.e. a strain with a MIC similar to the clinical breakpoint).

One slide on antimicrobials…

Study report possible to assess?

The selected model should be justified. Individual data including CI% for final parameters

should be presented. Goodness of fit data should be given including plots. Conclusions should not be extrapolated. The clinical relevance of the results should be

discussed when surrogate markers are used.

Conclusions

A PK/PD approach is of great value (with or without computer models)

Results could be pivotal or “nice to know” The objectives should be predefined The predictive value of the selected endpoints should be

justified The quality of the presentation is important Sufficient knowledge is a prerequisite for everything else…