067: The Impact of Late-Runner Participants on PK Variability in Healthy Volunteer, Single-Ascending Dose Trials

Statement of Purpose, Innovation or Hypothesis: Clinical Pharmacology trials are normally conducted in cohorts with all participants dosed in staggered fashion on the same day. Pharmacokinetic (PK) variability is minimized as much as possible through certain study design aspects, including the enrollment of healthy participants, restrictive enrollment criteria, and procedural controls. Occasionally, complete cohorts cannot be enrolled as planned, with remaining participants dosed on different date(s) to complete a full panel. This analysis was aimed to assess the impact of late-runner participants on PK data outcomes, as determined by changes in PK variability.

Description of Methods & Materials: A late-runner was defined as a study participant dosed four or more days apart from the cohort remainder. Across all healthy volunteer studies conducted at Fortrea 2013 to 2023, single ascending dose (SAD) trials and SAD components of single/multiple ascending dose (SAD/MAD) trials were most late-runner frequent and thus selected for this analysis. Large molecule trials, multi-site trials, and cohorts dosed in the fed state were excluded to limit PK variability sources. The resultant analysis sample included 22 studies comprising of 134 participant cohorts, 52 of which were cohorts with late-runners. PK parameters evaluated were AUC_0-tlast, AUC_0-∞ and C_max, where the geometric CV% served as the measure of variability.  Primary analysis: For each study, the geometric CV% was calculated for all study cohorts (cohorts with and without late-runner participants). These values, after log-transformation, were analyzed using a mixed effects analysis of variance (ANOVA), with a fixed effect for late-runner status (cohorts including late-runners versus cohorts without late-runners) and a random effect of study. Secondary analysis: The geometric CV% was calculated for cohorts with late-runners only, once with all participants included, and again after excluding late-runner participants. The corresponding values were then compared to assess the effect of late-runners on PK variability of that cohort.

Data & Results: The primary analysis revealed no significant difference in the geometric CV% of AUC_0-tlast (P-value = 0.6735), AUC_0-∞ (P-value = 0.5917) and C_max (P-value = 0.2195), when comparing cohorts with late-runners and those without, across all studies. The secondary analysis showed no consistent effect of late-runner inclusion on cohort PK variability compared to when calculated excluding late-runners, based on similar frequencies of increases and decreases in AUC_0-tlast, AUC_0-∞ and C_max variabilities.

Interpretation, Conclusion or Significance: Although late-runner participants are commonly avoided, incomplete panel enrollment cannot always be mitigated. This analysis demonstrated that resulting late-runner participants have no meaningful impact on the variability (CV%) of the PK parameters AUC_0-tlast, AUC_0-∞ and C_max. PK exposure data derived from late-runner participant studies are therefore valid to include in drug development decisions.

Disclosures:

Citations/References:

Additional Information/Authors: Additional Author:

Oren Cohen, M.D., F.I.D.S.A. (he/him/his)
Chief Medical Officer and President, Clinical Pharmacology Services, Fortrea
North Carolina, United States