Bioequivalence Studies: Designing an Effective Sampling Schedule

In pharmacokinetic analysis during the drug development processes, a well-structured sampling schedule is essential for accurately assessing the absorption, distribution, metabolism, and excretion (ADME) properties of a drug. However, missing data points remain inevitable in clinical trials, potentially compromising the precise determination of PK parameters, reducing statistical power, and hindering solid bioavailability(BA)/bioequivalence (BE) conclusions. While regulatory agencies like the ICH, FDA, and EMA publish guidelines outlining minimum sample requirements and general principles, no universally accepted standard exists for the frequency and extent of blood sampling. This blog aims to guide researchers in developing effective sampling schedules that optimize data quality, mitigate missing data issues, and contribute to successful regulatory submissions.

The Role of Sampling Schedules

Sampling schedules in PK analysis are essential for obtaining key PK parameters such as peak concentration (Cmax), time to reach peak concentration (Tmax), half-life (t1/2), and area under the concentration-time curve (AUC). These strategically designed sample schedules, with well-defined time points are critical for ensuring the accuracy and reliability of clinical data, as well as providing the evidence necessary to assess the safety and efficacy of both new and generic products.

The frequency and duration of blood sampling directly impacts the integrity and reliability of PK data, as improper timed blood samples can result in missed critical data points, leading to inaccurate PK parameter estimates and statistical analysis, which in turn affect the interpretation of the study outcomes.

Moreover, an inadequate sampling schedule could threaten participant safety and raise concerns from regulatory agencies. For instance, the total blood volume collected should generally not exceed 550 ml over 8 weeks in healthy volunteers.

Key Considerations in Designing Sampling Schedules

When designing a sampling schedule for PK studies, several critical factors must be considered to ensure robust data collection.

1. ADME: Understanding the drug’s ADME properties is key, with special attention to any differences between healthy volunteers and patients, as they may process the drug differently and require tailored sampling strategies. PK parameters, such as the median Tmax and mean T1/2 are typically used to reflect the majority of the population. Sampling should be strategically placed around the Tmax to capture peak absorption, and the half-life informs the timing of sampling points needed to assess late-phase drug elimination (e.g. recommend covering at least 3-5 half-lives). For drugs with a very long half-life, truncated sampling schedule might be facilitated.
2. Study Population: Factors such as age, sex, health status, and genetic variations can significantly influence drug metabolism and response, necessitating a different sampling schedule to the specific population. For example, poor metabolizers of CYP2D6 are excluded from studies on oxycodone due to their susceptibility to higher concentrations, they may otherwise require a modified sampling schedule. Healthy volunteers can generally tolerate more extensive sample schedules than patients.
3. Baseline Samples: For studies involving endogenous compounds (e.g., hormones, vitamins), at least 3 equally spaced baseline samples should be collected to reflect any drug-induced changes in concentration. It is important to note that some hormones exhibit circadian rhythms, meaning additional baseline samples may be required to capture the natural fluctuation and to correct for post-dose drug levels.
4. Study Design/Objective: The choice between a crossover or parallel design can impact the number of timepoints required, with crossover studies needing fewer timepoints due to multiple periods. The study design of whether single or multiple doses, also influences the sampling schedule. For example, several pre-dose concentrations should be collected to confirm whether steady-state concentrations have been reached. A 6-7 half-lives rule is typically applied to determine the total number of days required for blood samples. Other blood samples may be collected only on Day 1 and PK Day. For special cases to assess intra-subject variability of either the test or reference products, blood samples may be collected on multiple PK days after steady state is reached.
5. Formulation and Route of Administration: intravenous injection, inhalation or nasal administration of immediate-release formulations typically require more frequent early sampling due to rapid absorption of drugs. In contrast, modified-release formulations (e.g., prolonged-release, delayed-release or multiphasic-release), may require a sparser sampling strategy, such as sampling every half hour around the peak absorption, since these formulations release the drug more gradually.
6. Schedule Feasibility: The total blood volume to be collected throughout the study should be manageable for participants. For studies requiring overnight sampling, consideration should be given to minimize discomfort. The frequency of blood draws should also be designed to reduce the risk of adverse effects such as bruising or dizziness. For out-patient samples, it is often practical to begin collection once the absorption phase is complete and sampling intervals are spaced by more than 6 hours.
7. Regulatory Guidelines: Agency-specific guidelines should always be considered. Specially, the latest released ICH M13A guideline recommends that sampling intervals should be spaced to ensure accurate estimations of all PK parameters. For instance, drugs with rapid absorption may require early time points (e.g., within 1-hour post-dose), while a sampling duration that covers at least 3 half-lives is typically recommended to ensure adequate characterization of the drug’s PK, and the duration of sampling should aim to capture at least 80% of the AUCinf. In the U.S., blood sampling through a catheter is not permitted at the clinic site; only direct venipuncture is allowed for sample collection.

By considering these factors, researchers can develop a robust sampling schedule that ensures accurate PK analysis and supports regulatory approval.

Common Challenges and Solutions

One of the primary challenges in PK studies is ensuring participant adherence to the sampling schedule, particularly for return visits. Other challenges, such as missing samples, deviating time of collection due to sampling difficulties, incorrect sample handling, or unreportable samples due to bioanalysis reasons, can lead to gaps in data, compromising the study’s integrity.

Solutions for Addressing Missing or Unreliable Data

To address issues of missing data, samples with inconclusive time points, and non-reportable values in data analysis, different approaches are applied depending on the timing and degree of the missing data.

When a sample is missed at a non-critical time point, the impacted data is typically treated as “missing” and excluded from the PK analysis, as if the sample had not been scheduled for collection. This approach is feasible when a robust blood sampling schedule has been designed. However, if the missing sample occurs at a critical time point, often defined by the expected drug’s label median Tmax or mean T1/2, the decision to include or exclude the impacted parameters requires further review by a PK expert, the study’s objectives and the known PK profile of the investigational drug.

Additionally, when multiple consecutive samples (typically three or more) are missing, without a robust schedule, the impacted parameters might be considered unreliable and should be excluded from the PK analysis to maintain the study validity.

Simulation Studies on Missing Data

The occurrence of missing data points is an inherent challenge in clinical trials. To address this, we conducted several simulations to explore the impact of missing one or multiple concentrations of data on the study assessments. The results were presented at ASCPT and AAPS conferences and are also available on our BioPharma Services blog.  

The Critical Role of Adaptive Sampling Schedules in Drug Development 

In drug development, the significance of a well-structured sampling schedule cannot be overstated. A carefully designed schedule is essential to accommodate variations in drug properties, study populations, and study designs. It is often necessary to adjust the sampling plan to optimize data quality and address challenges like missing data, ensuring the integrity of key PK parameters.

Furthermore, as regulatory expectations continue to evolve, researchers should stay informed and adaptable to the latest guidelines, especially the recently published ICH M13A guideline for immediate-release formulations (effective in July 2024) that discusses the sampling strategy. In short, an adaptable sampling schedule is not only vital for generating reliable data, but also advances the development of safe and effective treatments for patients.

Choosing BioPharma Services for your drug development project ensures a partnership with a globally recognized Contract Research Organization (CRO) specializing in early-phase clinical trials and human abuse potential studies. Our team of accomplished pharmacologists and bioanalytical scientists employs innovative strategies to meet the complex drug development needs of our clients. We offer a comprehensive suite of services, including Phase I/IIa clinical research, bioequivalence studies, bioanalysis, data management, and more, providing end-to-end support for your drug development program.

Our state-of-the-art facilities, such as our 150-bed capacity clinic in Toronto, Canada, are designed to efficiently conduct clinical trials while ensuring participant safety and data integrity. Partnering with BioPharma Services means collaborating with a dedicated team committed to bringing novel and affordable medicines to patients in need.

Written By:

Jacinda Kwok

Pharmacokinetic Scientist II

BioPharma Services, Inc., a HEALWELL AI and clinical trial services company, is a full-service Contract Clinical Research Organization (CRO) based in Toronto, Canada, specializing in Phase 1 clinical trials 1/2a, Human Abuse Liability(HAL) and Bioequivalence clinical trials for international pharmaceutical companies worldwide. BioPharma Services conducts clinical research operations from its Canadian facility, with access to healthy volunteers and special populations.