Why PK Sampling Optimization Matters: Guide for Getting the Timing Right

Rachel Rozakis, PharmD, Senior Clinical Pharmacologist and Allie Story, PharmD Candidate, Clinical Pharmacology, Modeling and Simulation Intern

Understanding PK Sampling: What is a PK Sample? 

Pharmacokinetic (PK) sampling is a critical component of clinical trial design in drug development, enabling accurate characterization of a drug’s absorption, distribution, metabolism, and elimination (ADME) profile. Therefore, samples must be adequately collected to cover key phases such as absorption peak, distribution, and elimination to characterize the full PK profile. Sample optimization enables accurate estimation of key PK parameters such as maximum concentration (Cmax), time to reach maximum concentration (Tmax), terminal elimination half-life (t_1/2), and area under the concentration versus time curve (AUC). While PK assessments can be performed using various biological matrices – including cerebrospinal fluid (CSF), urine, or tissue biopsies—blood remains the most commonly used matrix due to its accessibility and representation of systemic concentration of a drug; thus, the focus of this blog is PK sampling of blood (which can include assessment of PK in plasma or serum).  

PK sampling strategies often evolve over the course of drug development. In Phase I healthy volunteer studies, sampling is typically extensive to allow detailed characterization of the drug’s PK profile at single and multiple doses in an inpatient, well controlled setting. In contrast, phase 2 and 3 studies usually involve sparser sampling (1-2 samples per specified visits), with a greater focus on safety and efficacy; however, PK data remain valuable in these stages. For example, this data may be useful to assess exposure in the target patient population, inform population PK (popPK) modeling including covariate analyses, or evaluate drug behavior in special populations such as those with hepatic or renal impairment if standalone organ impairment studies have not been done.    

Designing an effective PK sampling schedule requires careful consideration of many factors, including the drug’s ADME properties, route of administration, study design and population, and analysis type. A properly designed PK sampling schedule facilitates a comprehensive understanding of a drug’s PK, which is essential for regulatory submissions and ultimately informs the prescribing information included in the drug label.  

FDA Available Guidance on PK Sampling Schedule

The FDA recommends that sponsors collect blood rather than urine or tissue for drug concentration analysis in bioavailability (BA) studies submitted as part of investigational new drug applications (INDs), new drug applications (NDAs), or NDA supplements. Drug or metabolite concentrations should generally be measured in serum or plasma, unless whole blood is more appropriate due to assay sensitivity limitations. Blood samples should be collected at timepoints that adequately characterize the drug’s absorption, distribution, and elimination phases. Typically, 12 to 18 samples (including a pre-dose sample) per subject, per dose are recommended, with sampling continued for at least three terminal elimination half-lives. For multiple-dose studies, sampling must occur at steady-state across the dose interval and include the beginning and the end of the interval. To allow accurate estimation of Cmax and the terminal elimination rate constant (λ_z), at least three samples should be taken during the terminal log-linear phase. Sponsors are also advised to record both the actual clock time and the elapsed time from drug administration when each sample is drawn¹.  

For food-effect (FE) studies conducted under INDs and NDAs, samples should be collected in an appropriate biological matrix (e.g., plasma) during both fasted and fed periods. The sampling schedule should cover at least three to five elimination half-lives (typically 12-18 samples per subject, per period) to ensure the full concentration-time profile is characterized. If food significantly impacts drug absorption, different sampling time points may be required for the fasted and fed states to accurately capture PK differences.² 

While regulatory agencies like the FDA publish guidelines outlining minimum sample requirements and general principles, no universally accepted standard exists for the frequency and extent of blood sampling and there are many nuances to consider when selecting PK sampling timepoints for different drugs. These considerations will be explored in the following section.   

Factors Influencing PK Sampling Schedules 

Several factors influence the design of PK sampling schedules, including the investigational drug’s PK properties, the route of administration, study design, type of analysis being performed, and the study population. The following considerations ensure that the sampling strategy adequately captures the ADME profile of the drug.  

• Drug Characteristics: Understanding the drug’s ADME properties is key. Absorption rate (immediate vs. sustained release), distribution kinetics (rapid vs. slow tissue distribution), elimination half-life, and route of elimination (renal vs. hepatic) may all impact sampling frequency. For instance, rapidly absorbed drugs require more frequent early sampling to capture Cmax and Tmax, while drugs with long half-lives require extended sampling durations to adequately characterize the terminal elimination phase. 

• Route of Administration: Each route of administration (oral, IV, subcutaneous, intramuscular, inhalation, topical, etc.) has distinct absorption and distribution profiles. For example, oral drugs require consideration of absorption variability and potential for food and/or formulation effects whereas IV drugs have immediate systemic exposure, requiring frequent early sampling to capture rapid distribution and early decline. Sample collection during infusion and inhalation require accurate sample collection relative to the end of dosing. Subcutaneous administration involves slower, more prolonged absorption than IV or intramuscular, requiring more spaced-out early timepoints to capture the extended absorption window. Nonsystemic routes of administration such as topical may have highly variable PK profiles; therefore, sampling should capture prolonged absorption and elimination phases (the elimination may be dependent on the absorption rate).   

• Study Design: The study design defines how and when drug administration occurs and what comparisons are needed. In crossover studies, where the same participants receive multiple treatments in different periods, timepoints are typically identical across periods, allowing for fewer time points and more consistent sampling. In contrast, parallel designs involve separate groups for each treatment, often requiring larger sample sizes and more timepoints. The sampling schedule is also influenced by the dosing frequency in the study (single versus multiple dose [e.g., QD vs BID vs TID]). Single-dose studies aim to capture the entire concentration-time profile from absorption to elimination, requiring frequent earlier sampling and extended timepoints. Multiple-dose studies, on the other hand, require sampling across dosing intervals, including pre-dose and post-dose timepoints, and often include a full PK profile at steady state to assess drug accumulation and time-dependent changes. Patient studies (phase 2/3) are generally conducted as outpatient studies; therefore, sampling times are designed to align with participant visits. 

• Analysis Type: The use of non-compartmental analysis (NCA), compartmental analysis, or popPK for PK analysis also influences sampling strategy. In popPK studies, the sampling schedule should be optimized to allow estimation of PK parameters and covariate effects with a defined degree of precision. When fewer samples are collected per subject, the timing of each sample becomes increasingly important—particularly during the absorption phase—and sponsors are encouraged to plan PK sampling schedules prospectively to ensure that the resulting model is maximally informative.³ It is also imperative to collect the dosing and sampling times accurately.  

• Study Population: Factors such as age, sex, and health status can significantly influence drug metabolism and response, requiring a different sampling schedule to the specific population. For example, healthy volunteers can generally tolerate more extensive sampling schedules than patients. Pediatrics, elderly, or special populations (e.g., renal or hepatic impairment) may influence sampling windows necessitating tailored approaches.  

Careful consideration of these factors enables the development of a well-optimized sampling schedule that supports accurate and reliable PK parameter estimation. 

Pediatric Pharmacokinetics: Pediatric PK Sampling Schedules

Blood sample collection in pediatric studies presents unique challenges due to the limited total blood volume in children, which restricts both the volume and frequency of sampling that can be safely performed. Additional logistical issues, such as coordinating sampling around feeding or sleep schedules, and the need for parental consent and presence further complicate the process. To address these challenges, specialized strategies can be employed to optimize the timing and feasibility of PK sample collection while minimizing burden on the patient. These include the use of micro-volume assays, dried blood spots (DBS), and sparse sampling techniques. 

Dried blood spot sampling offers the advantage of requiring as little as 5-10 µL of blood, reducing invasiveness and often improving sample stability. When used in conjunction with population PK (popPK) modeling, DBS can support reliable PK studies in pediatric populations. PopPK approaches are used to analyze data from multiple subjects simultaneously, allowing patients to contribute a limited number of samples taken at varying time points. This method offers several benefits: 

• Sampling times do not need to be uniform across patients. 

• The burden of study samples can be distributed among many patients. 

• Optimal sampling times can be identified to improve estimation of key PK parameters. 

• Sparse sampling allows for flexible study designs, which facilitate better coordination with clinical care.   

In addition to DBS and popPK modeling, opportunistic and scavenged sampling, where PK samples are aligned with routine clinical blood draws or the use of leftover clinical samples, can further reduce the need for additional blood samples. However, these methods require careful validation to ensure they provide equivalent estimation of PK parameters when compared to preplanned time points. While obtaining PK samples in children is inherently more complex, advances in modeling techniques and thoughtful study designs address many obstacles in pediatric PK study design.^4,5,6,7  

Blood Sampling Pitfalls and Risks of Inadequate PK Sampling 

Pitfalls in PK blood sampling include not taking samples over a complete dosing interval, missing the Tmax due to insufficient sampling around the expected peak, and ending sampling too early to properly characterize the drug’s elimination phase. These gaps can lead to inaccurate estimation of key PK parameters such as Cmax, Tmax, half-life, and AUC.  

Missing critical timepoints can lead to biased or incomplete PK models, unreliable data interpretation, and poor understanding of a drug’s behavior in the body. Consequences may include increased variability in study results, flawed dose selection, and misinformed clinical study design decisions. Additionally, inadequate sampling may result in extended study timelines, higher costs, and increased burden on study participants. Importantly, insufficient PK data can delay regulatory approval and limit the strength of evidence needed to support dosing recommendations and product labeling.  

Understanding the drug’s PK characteristics, particularly in first-in-human (FIH) studies, can be challenging due to the lack of prior human data. This uncertainty increases the risk of missing critical timepoints. In such cases, the PK sampling schedule may need to be determined by leveraging nonclinical (animal) PK data. PK sampling schedules can also be adjusted during studies based on interim review of PK data to ensure adequate characterization of the drug’s PK profile.  

Conclusion 

Optimal PK sampling is a vital aspect of clinical study design that ensures accurate characterization of a drug’s ADME profile. Thoughtfully planned sampling schedules tailored to the drug’s properties, study design, analysis method, and patient population are essential for generating high-quality PK data. Characterization of multiple-dose PK is particularly important, as it more closely reflects the drug’s behavior under typical clinical use – most drugs are administered more than once or chronically, making steady-state or repeated-dose data critical for informing dosing recommendations and labeling. Additionally, PK sampling in specific populations, such as pediatrics, presents unique challenges, where practical constraints on obtaining blood samples at an ideal volume and frequency require careful planning.  

For additional, related content: 
Leveraging Modeling & Simulation for Pediatric Drug Development 

What is Pharmacokinetics and ADME 

To receive tailored guidance on optimizing PK sampling strategies, click here to connect with one of our many PK experts. 

Endnotes

1. U.S. Food and Drug Administration, Center for Drug Evaluation and Research (CDER), Bioavailability Studies Submitted in NDAs or INDs — General Considerations: Guidance for Industry (Silver Spring, MD: U.S. Department of Health and Human Services, April 2022), available at https://www.fda.gov/media/121311/download. 

2.  U.S. Food and Drug Administration, Center for Drug Evaluation and Research (CDER), Assessing the Effects of Food on Drugs in INDs and NDAs: Clinical Pharmacology Considerations: Guidance for Industry (Silver Spring, MD: U.S. Department of Health and Human Services, February 2024), https://www.fda.gov/regulatory-information/search-fda-guidance-documents/assessing-effects-food-drugs-inds-and-ndas-clinical-pharmacology-considerations 

3. U.S. Food and Drug Administration, Center for Drug Evaluation and Research (CDER) and Center for Biologics Evaluation and Research (CBER), Population Pharmacokinetics: Guidance for Industry (Silver Spring, MD: U.S. Department of Health and Human Services, February 2022), https://www.fda.gov/media/128793/download 

4. U.S. Food and Drug Administration, Center for Drug Evaluation and Research (CDER), General Clinical Pharmacology Considerations for Pediatric Studies of Drugs, Including Biological Products: Guidance for Industry, draft guidance (Silver Spring, MD: U.S. Department of Health and Human Services, September 2022), https://www.fda.gov/media/90358/download 

5. Michael J. Rieder, “Facilitating Pharmacokinetic Studies in Children: A New Use of Dried Blood Spots,” Archives of Disease in Childhood 95, no. 6 (2010): 484–485, https://pubmed.ncbi.nlm.nih.gov/20501544/ 

6. Charlotte I. S. Barker et al., “Pharmacokinetic Studies in Children: Recommendations for Practice and Research,” Archives of Disease in Childhood 103, no. 7 (2018): 695–702, https://pmc.ncbi.nlm.nih.gov/articles/PMC6047150/ 

7. Stéphanie Leroux et al., “Pharmacokinetic Studies in Neonates: The Utility of an Opportunistic Sampling Design,” Clinical Pharmacokinetics 54, no. 12 (2015): 1273–1285, https://pubmed.ncbi.nlm.nih.gov/26063050/ 

About the Authors 

Rachel Rozakis, PharmD, Senior Clinical Pharmacologist at Allucent has extensive experience in clinical pharmacology and scientific communications. She brings a strong track record of cross-functional contributions across therapeutic areas including neurology, cardiology, dermatology, and oncology. Rachel has played a key role in authoring and contributing to a wide range of regulatory and clinical documents, such as Investigational New Drug (IND) applications, New Drug Application (NDA) submissions, clinical study reports (CSRs), study protocols, and QT summary reports. Her scientific writing expertise supports regulatory strategy and drives the development of high-quality documentation essential for drug development and approval. 

Allie Story, Clinical Pharmacology, Modeling and Simulation Intern at Allucent is a PharmD candidate at the University of North Carolina Eshelman School of Pharmacy. She brings over four years of experience in pharmaceutical manufacturing and research and development, with a focus on oncology and cell and gene therapy. At Allucent, Allie contributes to clinical pharmacology consulting projects through technical writing and scientific support, applying her background in drug development to help advance innovative therapies.