Optimizing first-time-in-human trial design for studying dose proportionality

Optimizing first-time-in-human trial design for studying dose proportionality

Yin, Yin

Mixed effect models are becoming common in analyzing data from clinical trials involving several measurements for each subject. However designs using mixed effect models have not received as much attention. Data collected from first-time-in-human studies are frequently used for studying dose proportionality. Two design types were evaluated theoretically for a hypothetical study conducted at six doses evenly spaced on a log scale for a drug whose AUC-dose relationship can be described by a mixed effect power model. In sequential panel design, subjects receive consecutive doses and in alternate panel design, subjects receive nonconsecutive doses. Sample sizes required to characterize the AUC-dose relationship to the same level of precision by both designs were calculated at given inter- and intra-subject variabilities. The conclusion is that an alternate panel design always requires fewer subjects than a sequential panel design. In many common cases, less than half as many subjects are required.

Key Words: Dose proportionality; First-time-in-human (FTIH); Power model; Mixed effect model; Design


THE USUAL OBJECTIVES of a first-time-in-human (FTIH) study for an investigational drug are to assess the safety/tolerability and the pharmacokinetics of the compound over a range of doses. Dose proportionality, one aspect of pharmacokinetics, characterizes whether a change in the dose results in a proportional change in the maximum circulating concentration (C ^sup MAX^) or the systemic exposure, which is usually represented by the area under the circulating concentration versus time curve (AUC). Early understanding of the dose proportionality is important for several reasons:

1. It helps guide dose selection for subsequent clinical trials,

2. It determines the regimen for dosage adjustment in clinical practice and the need for therapeutic concentration monitoring, and

3. It contributes to the evaluation of the ease of clinical use and, therefore, the commercial viability of a potential product.

Since in FTIH studies a wide range of doses are given in a controlled environment where the safety of the test subjects is closely monitored, these studies are ideal opportunities for investigating dose proportionality. Given the dose levels to be tested, among the key questions often asked about the design of a FTIH study are:

* How many subjects should receive each dose? and

* How many and which doses each subject should receive?

Mixed effect models are now increasingly widely employed to describe the relationships among dose, concentration, and response data collected in clinical trials. However, less progress has been made in applying this approach in trial designs. Using a mixed effect model, we evaluated FTIH design alternatives for their precision in estimating dose proportionality.

The designs will be described in the next section. The power model will then be reviewed, followed by the results and an example, discussion, and the conclusion.


Alternate panel designs are preferred over sequential panel designs in assessing dose proportionality using a mixed effect power model, especially when intrasubject variability is small. Therefore, without sacrificing safety concerns, alternate panel designs should be used to increase efficiency.

Acknowledgment-The authors would like to thank Professor Gary Koch and all reviewers for their helpful comments.


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Statistical and Data Sciences Leader, Metabolic, Musculoskeletal and Viral Diseases Center of Excellence for Drug Discovery


Senior Clinical Pharmacokineticist, Clinical Pharmacology & Experimental Medicine GlaxoSmithKline, Research Triangle Park, North Carolina

Reprint address: Yin Yin, GlaxoSmithKline, 5 Moore Drive, Research Triangle Park, NC 27709.

Copyright Drug Information Association Oct-Dec 2001

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