From lab to life in 24 Hours: i-screen demonstrates correlation between laboratory and human gut responses

Why one-size-fits-all gut microbiome studies often fall short

Dietary fibre interventions rarely produce identical microbiome shifts in everyone. Even when participants follow the same protocol, outcomes can vary widely -making it difficult to generate consistent evidence, select the optimal formulation, or determine which subgroup a product is most suitable for.

This variation is not a minor issue: research indicates that fibre consumption accounts for only a small fraction of gut microbiota variation, whereas most variation reflects differences between individuals (Rodriguez et al., 2024).

For manufacturers, this creates a practical bottleneck. Human intervention studies can be expensive and slow, and “average effects” may hide meaningful responses in subgroups - exactly the groups a targeted product aims to serve.

What the researchers tested: a dietary fibre mix in people and in the lab

To address the translation gap between laboratory microbiome studies and real-world human outcomes, the researchers designed a study that linked both settings as directly as possible.

They conducted a 12-week, double-blind, randomised, placebo-controlled, crossover intervention in 54 healthy volunteers (aged 45–70 years). The intervention used a fibre mix composed of acacia gum and carrot powder. Crucially, the in vitro work used faecal samples from the same individuals, allowing a like-for-like comparison between laboratory and human microbiome responses.

In the laboratory, the team used i-screen, an in vitro gut microbiota model designed to test how gut microbial communities respond to interventions under controlled conditions.

What they found: 24-hour i-screen results correlate with 8–12 week human outcomes

The key result is that microbiome shifts observed after 24 hours in i-screen aligned with the direction of change seen in the human study after 8 and 12 weeks of intervention. The publication reports statistically significant correlations between in vitro and in vivo changes in microbiota at these later time points.

The study also found significant overlap in the bacterial taxa that responded to the intervention in both settings. Examples highlighted include Bifidobacterium breve and Subdoligranulum species, beneficial microbes associated with gut health.

Importantly for formulation work, the authors noted that individual fibre components can stimulate different microbial responses—meaning mixtures can produce combined effects rather than behaving as a single “generic fibre” input. This strengthens confidence that a short in vitro fermentation readout can reflect longer-term patterns seen in humans.

Read our publication ‘Translating in vitro gut microbiota models to human context: compositional correlations under dietary fiber intervention.’

What makes i-screen different from other gut models

Unlike established gut simulation systems such as SHIME and TIM-2, which are valuable but low-throughput, i-screen was designed specifically for industry needs:

• High-throughput capacity to test dozens to hundreds of conditions simultaneously - different doses, combinations, and individual donor responses;
• Preservation of individual variation by maintaining each donor's unique microbial profile rather than pooling samples;
• Rapid mechanistic insights from 24-hour incubation showing which bacteria respond and how fibre combinations interact.

This combination enables pre-screening of participants prior to clinical trials, supporting smaller, more focused studies with possible higher success rates.

The platform leverages TNO's fecal Biobank, which houses microbiota samples with extensive metadata, including BMI, dietary intake patterns, and information on gut health. This allows targeted donor selection based on specific client needs, making experiments more relevant to intended consumer populations.

How an i-screen project works in practice

When a manufacturer approaches TNO, the process begins with understanding the product and the research question. The team determines whether samples require preprocessing based on their composition and then selects appropriate donors from the TNO Biobank. After conducting an up to 48-hour fermentation experiment, comprehensive bioinformatics analysis identifies which bacterial taxa respond and which metabolites are produced (commonly measured metabolites include short-chain fatty acids). Results are delivered in detailed reports and presentations that interpret the findings for commercial application.

TNO's role: bridging lab models and human evidence

TNO develops and applies in vitro and ex vivo platforms for gut health research, alongside human studies, to help translate microbiome insights into development decisions. The study was conducted in collaboration with the Centre for Human Drug Research (clinical trial), DSM Nutritional Products (scientific input), and funded through the Top Sector Agri & Food initiative.

As an independent applied research organization, TNO's role is to bridge academic science, industrial application, and public benefit, bringing together clinical infrastructure, ingredient expertise, and translational platform technology.

What's next: moving from correlation to prediction

This study supports laboratory-to-human translation by demonstrating a correlation between i-screen and in vivo outcomes using matched donor samples. A logical next step is prospective testing: assessing whether i-screen can help indicate responses before a person begins an intervention, rather than correlating outcomes retrospectively.

Further development can also focus on linking compositional changes to functional readouts, integrating host factors, and developing rapid diagnostic tools for pre-trial responder identification in commercial settings.

TNO is also developing remote clinical trial protocols in which participants receive study materials at home and submit data via communication portals. A recent study by de Jong et al. (2026) demonstrated the feasibility of remote clinical trials for personalised nutrition. In their randomised controlled trial, adults with overweight or obesity received study materials at home and submitted data via digital communication portals. This approach could reduce trial costs and increase accessibility, making validation studies more feasible for a wider range of products.

Broader context: supporting personalized nutrition strategies

This work aligns with European priorities for proactive health management and personalized nutrition. Most citizens fall short of recommended fibre intake levels, thereby increasing the risk of chronic disease. Products that demonstrably support beneficial gut bacteria can help bridge this gap, but only if the industry has tools to identify effective formulations.

Pre-screen your development pathway

If you are developing dietary fibres or fibre-containing products and want to pre-screen your development pathway, by comparing formulations, exploring responder patterns, or generating mechanistic insights, i-screen can support earlier evidence generation before larger clinical investment.