Microbiota refers to the community of microorganisms, including bacteria, viruses, fungi, and archaea, that reside in a specific environment, such as the gastrointestinal (GI) tract, skin, or oral cavity (1). Microbial communities differ across body sites. For example, the composition of the GI microbiota is distinct from that of the skin, vagina, or respiratory tract (1, 2). Each niche exhibits its balance of commensal, symbiotic, and occasionally pathogenic microorganisms. Emerging evidence indicates that imbalances in these site-specific microbial ecosystems, commonly called dysbiosis, can influence human health and disease (2). In the GI tract, dysbiosis has been associated with inflammatory disorders, metabolic disturbances, and impaired immune function (3). Shifts in the vaginal microbiota may predispose individuals to bacterial vaginosis (4), and imbalances in skin microbiota have been linked to dermatological conditions such as atopic dermatitis (5).

The pivotal role of microbiota in human health has drawn attention from not only researchers but also regulatory authorities. The European Food Safety Authority (EFSA) evaluates the scientific evidence supporting health claims for food ingredients and dietary supplements under EU regulations, including those related to gut microbiota (6). Health Canada requires scientific evidence to substantiate claims about ‘prebiotics’ and ‘probiotics’ (7). Although not specified for ‘prebiotics’ or ‘probiotics’, the Food and Drug Administration (FDA) expects structure/function claims to be supported by robust data (8). Each regulatory body employs its own framework, but all demand evidence demonstrating microbial modulation and/or relevant health outcomes.

Growing awareness of the impact of microbiota on metabolic, immunological, and overall physiological health underscores the importance of careful clinical trial design for microbiota-targeting products. Variables in the clinical trial design, such as placebo choice, sampling methodology, baseline microbial composition, and outcome measures, can greatly influence results (9,​​​​​​​ 10). Addressing these factors with rigour helps ensure that observed effects reflect genuine intervention outcomes. To develop credible products and meet regulatory authorities’ expectations for microbiota-focused health claims, researchers and industry stakeholders must adopt robust clinical trial protocols that incorporate best practices for measuring and interpreting microbiota endpoints. With these foundational concepts in mind, it is crucial to consider why measuring microbiota endpoints is essential in clinical trials and how these measures can validate a product’s effectiveness.

Understanding the “Why?”

A central rationale for measuring microbiota in clinical trials is to confirm that a product modulates microbial communities in a way that leads to improved health outcomes. Many dietary supplements and natural health products are designed to influence the composition or activity of specific microorganisms. Demonstrating this effect is a crucial first step in establishing the product’s mechanism of action. It is equally important to correlate any observed shifts in the microbiota with tangible clinical or functional benefits, such as improved digestive health or enhanced immune responses.

Recent guidelines underscore the need for this dual demonstration of microbiota modulation and health impact (9). For instance, for prebiotic products, the International Scientific Association for Probiotics and Prebiotics (ISAPP) and Global Prebiotic Association (GPA) require that products claiming a “prebiotic” effect show evidence of microbial utilization and a corresponding benefit to the host (11, 12). Other trade and scientific associations are also working on “prebiotic” definitions.

By documenting how a product alters the microbiota and verifying that these alterations confer meaningful health advantages, researchers can align with regulatory expectations. This approach helps ensure that claims about beneficial microbes rest on a solid scientific foundation rather than on indirect or speculative associations. Clarifying the rationale for microbiota-focused research sets the stage for determining the study design, participant selection, and analytical methods required to generate reliable, clinically meaningful data.

Study Design & Methodological Considerations

A robust clinical trial to investigate microbiota modulations should align the study’s aims with the type of claims the product is intended to support. A key consideration is whether microbiota endpoints should serve as primary or secondary outcomes. For example, a prebiotic claim typically requires demonstrating that a specific substrate is selectively utilized by certain microbes, coupled with evidence that this shift confers a health benefit (9). Probiotic claims similarly hinge on showing that a live microorganism reaches its target in sufficient numbers to influence health outcomes (9). Therefore, in studies centered on gut health involving prebiotics or probiotics, microbiota measures may justifiably occupy the role of primary outcomes. In other trials, researchers may choose to collect microbiota data as an exploratory measure alongside a clinical endpoint (for example, glycemic control), thus clarifying potential mechanisms of action. Clarifying these objectives at the outset helps determine the most appropriate populations, sampling methods, and analytic approaches.

Establishing a well-defined baseline is important, given that individual variations in microbiota composition can create pronounced differences in response. If the goal is to detect changes in specific bacterial groups or metabolic pathways, it may be prudent to consider participant characteristics such as age, sex, body mass index, diet, medication use, etc. (9). This can be done by stratification and/or including these characteristics as covariates in the statistical analyses. In this way, variability between participants can be reduced or accounted for, increasing the likelihood of detecting a true effect. It should also be noted that overly strict inclusion and exclusion criteria may complicate recruitment, so a balance must be struck between scientific rigor and practical feasibility.

The selection of an appropriate placebo is likewise critical: commonly used materials like maltodextrin (13), silica (14), or potato starch (15) can inadvertently influence microbial populations, particularly if consumed at higher doses. Reviewing available data or performing pilot testing can help confirm that a chosen placebo exerts minimal effects.

Finally, emerging artificial intelligence and machine learning techniques offer new opportunities for study optimization. These methods may help assess baseline microbiota profiles to predict responses to placebo and refine participant stratification, thus reducing inter-participant variations and allowing detection of subtle shifts in microbial composition (16). They may also help illuminate correlations between specific microbial patterns and clinical outcomes to enhance product claims in a data-driven manner (17). For instance, an interventional clinical trial was conducted on Bifidobacterium longum BB536 in 24 adults who tended to be constipated, and the researchers applied a machine learning approach to identify responders (i.e., those with an increased bowel movement frequency after B. longum BB536 supplementation) using pre-supplementation fecal microbiome and metabolome data (18). The responder prediction by machine learning aligned with trial observations, highlighting the potential of fecal metabologenomic data for predicting probiotic efficacy and enabling personalized interventions (18).

After establishing a clear study framework, attention must turn to the practical details of sampling and data collection, which can significantly influence the accuracy of microbiota assessments.

Sampling & Data Collection

Given the influence of external factors on microbiota composition, perhaps multiple baseline samples are needed to capture meaningful changes, particularly in studies focused on the gut. Collecting several fecal samples over a few days before initiating the product consumption may account for day-to-day fluctuations and provide a more accurate representation of the participant’s usual microbial state. In addition, specifying a consistent time of day for sample collection can reduce variability arising from diurnal changes in microbial populations and metabolites, which were observed in several studies (19, 20).

Sampling methods should be tailored to each body site under investigation.

• Fecal collection commonly involves either fresh stool samples or preservative kits that stabilize DNA at room temperature. Homogenized fresh samples allow measurement of DNA, short-chain fatty acids, other metabolites, and proteins but require rapid processing and cold storage. Preservative kits offer greater logistical convenience, though the microbiota profiled may not be representative due to no homogenization, and metabolite- and protein-based analyses are limited. Neither fresh nor preserved stool samples are representative of colon mucosal microbiota, hence new methods utilizing ingestible devices have been developed to sample intestinal fluid with precision (21). Nonetheless, they could be relatively more expensive and might be exposed to downstream contamination if not processed properly.
• In studies focusing on the vaginal (22), skin (23), or oral cavity (24) microbiota, standardized techniques and clear instructions for participants and clinical staff are important to ensure reproducibility and sample integrity.

Storage and transport protocols have a direct impact on data quality. Fresh samples are often frozen at -80°C, whereas swabs may be placed in specialized media or preservative solutions. In all cases, consistent labeling, immediate cooling (if applicable), and appropriate shipping methods help preserve microbial DNA and metabolites. Any deviation from standard procedures can introduce variability that obscures the true effect of a product.

Once samples are collected, the choice of analytic methods should align with the research question. Some trials target specific bacterial groups or species relevant to the hypothesized mechanism of action, such as bifidobacteria or lactobacilli. Others adopt a broader sequencing-based approach to capture global shifts in composition and diversity. Metabolite analysis, such as measuring short-chain fatty acids or other microbial byproducts, can offer additional insights into functional changes. Preliminary testing of a product targeting gut microbiota using in vitro simulated digestive systems, like the SHIME (Simulator of the Human Intestinal Microbial Ecosystem) (25), may provide insights on microbial responses before moving to clinical testing. Once appropriate samples are gathered and analyzed, transparent reporting of protocols and results is essential for reproducibility and regulatory alignment.

Standardized Reporting in Microbiota Research

Ensuring consistent and transparent reporting of study protocols and findings is a crucial step in advancing microbiota research. Clear descriptions of the population, product dosing instruction, sample handling, and analytical methods allow for better interpretation of results and facilitate comparisons across different studies. Registering trials in a recognized public database, such as ClinicalTrials.gov, strengthens the credibility of the research by documenting objectives, methodologies, and outcomes in a publicly accessible format. This practice also aligns with ethical standards of research transparency and helps prevent issues related to selective outcome reporting.

The S.T.O.R.M.S. (Strengthening The Organization and Reporting of Microbiome Studies) checklist offers a practical tool for standardizing how microbiota research is presented (26). It outlines essential details to report in each section of a manuscript, including participant recruitment, sample collection, data analysis, and interpretation of results. By following these guidelines, authors can enhance the reproducibility of their work, provide clarity for peer reviewers, and support future meta-analyses. In this way, standardized reporting practices not only promote scientific rigor but also contribute to a more coherent body of evidence on products targeting microbiota modulations.

Well-designed clinical trials are essential for advancing the understanding of how microbiota-targeting products impact health. Methodological rigor helps ensure observed effects stem from the product rather than confounding factors, such as baseline variability or external influences. Identifying claim-based endpoints, selecting an appropriate placebo, and carefully defining inclusion and exclusion criteria can strengthen the validity of study findings. Furthermore, standardized reporting practices enhance the reliability of microbiota research.

The abovementioned best practices will help researchers generate robust, reproducible data that meets the stringent requirements from agencies like the EFSA, FDA, and Health Canada. This not only streamlines the regulatory review process but also reinforces market credibility by providing clear, evidence-based support for product claims. This is critical for gaining the confidence of healthcare professionals and consumers.

A future opportunity for microbiota-targeting strategies lies in personalized intervention approaches, which may be enabled using machine learning and/or artificial intelligence that predict responsiveness to an intervention. Continued collaboration among researchers, clinicians, and regulators will be key to unlocking the full potential of microbiota-targeting strategies.