The co-administration of oral drug products with food can lead to marked alterations in bioavailability (BA) and plasma concentrations when compared to the fasted state. This food-mediated variability in drug exposure can impact drug product safety and efficacy, carrying important implications across drug development, regulatory evaluation, and clinical practice.

Drug products displaying significant differences in plasma concentrations when taken with food require a strict dosing regimen, which can undermine patient compliance and efficacy. Drug developers wishing to avoid such a restrictive ‘food label’ may need to develop an ‘enabling’ and typically more complex formulation strategy. As such regulatory agencies require sponsors to assess the effect of food on drug BA early in development to guide labeling and formulation strategies.

Given that over 40% of drugs approved by the FDA or the EMA exhibit significant food effects (O’Shea 2019), research efforts have increasingly focused on elucidating the mechanistic basis of these food-drug interactions and improving the ability to predict their occurrence.

In this blog post, you’ll see how physiologically based biopharmaceutics modeling (PBBM) can help elucidate the mechanisms driving food effects and support regulatory decision making.

How can PBBM streamline food effect assessment?

Physiologically based pharmacokinetic (PBPK) modeling is a well-established tool in drug development and is widely used to evaluate drug-drug interactions (DDIs), reduce the need for certain clinical trials, and inform regulatory labeling decisions. More recently, the implementation of PBPK for biopharmaceutics applications, that is, PBBM, has been used to enhance drug product quality through a more accurate and comprehensive understanding of drug-body interactions and their influence on in vivo performance (Mackie 2024). As confidence grows in the ability of PBBMs to accurately characterize the biopharmaceutical properties and absorption of orally administered drugs, a natural question emerges: Can these models be increasingly used to predict and assess food effects in a clinical context?

Emerging evidence says yes. A growing number of publications have demonstrated PBBMs can replicate clinical food-effect data with a reasonable degree of accuracy (Pepin 2024 and Nakayama 2024). These studies focus on physiological mechanisms differentiating the fed versus the fasted states, such as the delay in gastric emptying, increased concentrations of bile salts, and differences in fluid volume and pH, and how they influence BA of a given drug product through modulation of in vivo release and absorption. Simulations rely on mechanistic inputs such as drug product solubility, dissolution, permeability, and metabolism. These properties can be determined using in vitro measurements, or in some cases based on predictions derived from quantitative structure–property relationships (QSPR) using machine learning software, such as ADMET Predictor®.

A powerful aspect of this approach is the ability to simulate the impact of different meal types—such as high-fat, standard, or low-calorie meals—each introducing distinct changes in gastrointestinal physiology. Using PBBM for these scenarios provides valuable insights into the likelihood, magnitude, and mechanisms of food effects, well before clinical trials begin. Also, by

revealing the impact of administration and dosing strategies on drug product performance, PBBM can be used to educate key stakeholders and inform prescribing information on drug labels.

A proposed workflow suggests how PBBM could be integrated into clinical development to streamline food-effect evaluations, especially when considering drugs from different biopharmaceutics classification system (BCS) classes (Kollipara 2024). This modeling-based approach not only enhances mechanistic understanding but also offers a path to reduce development timelines and optimize clinical study design.

Can PBBM support regulatory assessment of food impact in bioequivalence studies?

Yes—and recent regulatory initiatives are actively reinforcing its potential.

PBBM is increasingly being recognized as a valuable tool for assessing the impact of food on BA and bioequivalence (BE), particularly within the context of generic drug development. This growing acceptance was the focus of a dedicated session during the FDA Center for Research on Complex Generics’ workshop, “Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches” (Babiskin 2023).

The experts from regulatory agencies, academia, and industry presented successful case studies and discussed how PBBM and PBPK models can be applied to simulate and predict food effects in BE studies. The consensus was clear: PBPK/PBBM offers a mechanistic, science-driven framework that can complement or, in some cases, reduce the need for dedicated fed-state clinical trials.

The regulatory utility of PBBM is reinforced by the publication of formal guidances from both the FDA and the EMA. These guidelines acknowledge the model’s capacity to account for key physiological variables—such as gastrointestinal transit, pH, bile salt secretion, and enzyme activity—which are all influenced by food intake and critically affect drug absorption.

While the potential is strong, the workshop also highlighted ongoing challenges, such as the need for robust model validation and standardized best practices for regulatory submissions.

What should you consider when selecting a reliable PBBM/PBPK platform for food effect modeling?

When considering software platforms for food-effect assessments, it’s critical to evaluate how reliable predictions will be. There are a few questions to answer during your selection process that should help you identify a PBBM/PBPK platform you will be confident in and trust.

• Has the platform been shown to offer accurate food-effect assessments in the past? GastroPlus has been validated in thousands of peer-reviewed publications over the years across all discovery/development applications, with hundreds focused on food effect predictions for different drug types and formulations—proof of the trust it has earned from pharmaceutical innovators and global regulators.
• Is the platform commercial or open source? Commercial software platforms like GastroPlus issue regular updates, provide training, and offer technical assistance for users. Open-source options typically cannot provide robust support when challenges arise.
• How current are the models and data used in the platform? Scientific knowledge is constantly growing, and to leverage it in modeling one must be using software that regularly integrates new findings. GastroPlus has active collaborations with industry partners, academic researchers, and regulatory-science groups, which feed new data and insights into the software and provide the most up-to-date and rigorously validated PBPK/PBBM capabilities for confident food assessments.

In conclusion, understanding the impact of food on drug absorption is critical to ensure the safety, efficacy, and success of pharmaceutical products. By leveraging tools like GastroPlus coupled with a foundational knowledge of key drug product characteristics, researchers can anticipate and address food-drug interactions during drug development, ultimately improving drug design and regulatory outcomes.

If you’re looking for more insights into how PBPK models can streamline food effect assessments and optimize drug development, our team of experts is here to help. Discuss your project needs with our experts.

References:

Babiskin A, Wu F, Mousa Y, Tan ML, Tsakalozou E, Walenga RL, Yoon M, Raney SG, Polli JE, Schwendeman A, Krishnan V, Fang L, Zhao L. Regulatory utility of mechanistic modeling to support alternative bioequivalence approaches: A workshop overview. CPT Pharmacometrics Syst Pharmacol. 2023 May;12(5):619-623.

Kollipara S, Martins FS, Sanghavi M, Santos GML, Saini A, Ahmed T. Role of Physiologically Based Biopharmaceutics Modeling (PBBM) in Fed Bioequivalence Study Waivers: Regulatory Outlook, Case Studies and Future Perspectives. J Pharm Sci. 2024 Feb;113(2):345-358.

Mackie C, Arora S, Seo P, Moody R, Rege B, Pepin X, Heimbach T, Tannergren C, Mitra A, Suarez-Sharp S, Borges LN, Kijima S, Kotzagiorgis E, Malamatari M, Veerasingham S, Polli JE, Rullo G. Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report. Mol Pharm. 2024 May 6;21(5):2065-2080.

Nakayama S, Lukacova V, Tanabe S, Watanabe A, Mullin J, Suarez-Sharp S, Shimizu T. Physiologically Based Pharmacokinetic Absorption Model for Pexidartinib to Evaluate the Impact of Meal Contents and Intake Timing on Drug Exposure. Clin Pharmacol Drug Dev. 2024 Apr;13(4):440-448. doi: 10.1002/cpdd.1385.

O’Shea, J. P., Holm, R., O’Driscoll, C. M., & Griffin, B. T. (2019). Food for thought: Formulating away the food effect – a PEARRL review. Journal of Pharmacy and Pharmacology, 71(4), 510–535. https://doi.org/10.1111/jphp.12957

Pepin XJH, Hynes SM, Zahir H, Walker D, Semmens LQ, Suarez-Sharp S. Understanding the mechanisms of food effect on omaveloxolone pharmacokinetics through physiologically based biopharmaceutics modeling. CPT Pharmacometrics Syst Pharmacol. 2024 Oct;13(10):1771-1783. doi: 10.1002/psp4.13221.