Key takeaways: 

•    The 2024 ICH M12 Guideline successfully harmonized drug-drug interaction (DDI) study expectations across the industry, but gaps remain in current best practices and model systems that may be addressed through adoption of new complex in vitro models (CIVMs).

 •    Traditional in vitro systems lack the sensitivity and longevity required to model the induction of non-CYP3A4 pathways and accurately measure the unbound intrinsic clearance (CL_int,u) of low-turnover compounds.

 •    Underperforming models can result in conservative risk assessments leading to unnecessary clinical DDI studies. Persistent gaps remain in translating in vitro data to clinical risk, particularly for inconsistent CYP induction and low-turnover clearance predictions, where conventional hepatocyte monocultures lack stability, sensitivity and dynamic range. 

•    The extended drug metabolizing enzyme (DME) stability for accurate CL_int,u estimation and sensitive, robust nuclear receptor pathway response—including increased CYP2C dynamic range—of TruVivo^® provide the high-fidelity data needed for more accurate PBPK modeling and improved decision quality and confidence.

Introduction 

The publication of the 2024 ICH M12 Guideline marked a meaningful step forward in how global regulatory agencies—FDA, EMA, and PMDA—align their expectations for drug-drug interaction (DDI) study requirements. By establishing a unified, risk-based framework for evaluating pharmacokinetic-based DDIs mediated by metabolic enzymes and drug transporters, ICH M12 reduces the regional inconsistencies that had long complicated drug development.¹ But harmonization of the rules is only part of the challenge. A rigorous industry-led appraisal by the DDI Discussion Group in the International Consortium for Innovation and Quality (IQ Consortium)¹ makes clear that significant scientific and technological gaps remain, and that addressing them will require model systems with higher fidelity to in vivo outcomes than most standard in vitro models can deliver. 

What ICH M12 Harmonizes—and What It Doesn't 

ICH M12 brings consistency to a number of procedural and operational aspects of small molecule DDI science: standardized criteria for metabolite assessment, refined scaling factors for time-dependent inhibitors, and formal recognition of endogenous biomarkers such as coproporphyrin I (CP-I) for OATP1B inhibition.¹  These advances reduce regulatory ambiguity and provide a clearer path for sponsors designing both in vitro and clinical DDI studies. What ICH M12 does not resolve are the scientific, translational, or operational limitations inherent in standard tools. Two gaps in particular stand out. 

The CYP Induction Gap 

CYP induction assessment under ICH M12 centers on the mRNA fold-change method, with CYP3A4 as the primary benchmark. While CYP2C enzymes—CYP2C8, CYP2C9, and especially CYP2C19—are clinically inducible, they routinely underperform in conventional monoculture hepatocyte systems.¹ 

The IQ Induction Working Group has documented that successful in vitro to in vivo extrapolation (IVIVE) for CYP2C enzymes demands alternative in vitro models because in standard sandwich-cultured hepatocytes, induction signals are inconsistent and often too small to quantify reliably. Researchers are left inferring CYP2C risk from CYP3A4 data, a workaround that introduces regulatory uncertainty and can trigger unnecessary clinical DDI studies. Further, since in vitro DDI studies inform clinical DDI study design, inaccurate results in vitro can lead to poor clinical DDI study design. Unreliable IVIVE of CYP induction increases the risk of unforeseen clinical DDI liabilities and downstream development risk. 

The Low-Turnover Compound Gap 

ICH M12 also increases scrutiny on low-turnover compounds and non-CYP metabolic pathways—including direct glucuronidation via UGT metabolism enzymes and oxidation by aldehyde oxidase. Metabolically stable compounds require extended incubation windows of 5+ days to generate more reliable clearance data. Conventional suspension assays, which lose metabolic activity within hours, cannot accurately characterize these low-turnover compounds.¹ The result is a persistent IVIVE gap: when compounds show low-turnover in suspension, researchers cannot calculate unbound intrinsic clearance (CL_int,u). This lack of hard parameter data creates uncertainty around downstream PK predictions, leaving sponsors to advance compounds into clinical studies with limited confidence in clearance data, increasing risk of trial failure. 

Model Insufficiency Increases Clinical Risk

In practice, both gaps share the same underlying problem: today’s standard tools do not provide an adequate solution for what ICH M12 now requires. The primary human hepatocyte sandwich culture model often lacks the resolution and dynamic range needed to quantify CYP2C induction, potentially triggering expensive, avoidable clinical studies. In parallel, suspension assays lack the longevity and phenotypic stability required to assess clearance of low-turnover compounds, limiting confidence in human clearance projections, PBPK modeling, and dose selection strategies. 

TruVivo^®: Bridging the Gap with Advanced Biology 

The TruVivo^® 2D+ hepatic system—integrating primary human hepatocytes with stromal and endothelial cells—is designed to address these limitations. By maintaining stable drug-metabolizing enzyme (DME; e.g., Phase I and II) and transporter activity for at least 14 days, TruVivo enables the extended incubation required for ICH M12–aligned studies, including both induction assessments and clearance characterization. The system also reduces donor-to-donor variability and improves the signal-to-noise ratio that has historically undermined CYP2C induction studies across hepatocyte donors in in vitro DDI studies. 

For CYP induction, data demonstrate that TruVivo delivers up to 20-fold greater dynamic range for CYP2C enzyme induction compared to standard hepatocyte sandwich cultures²—generating the quantitative mRNA fold-change data ICH M12 calls for, but that conventional systems routinely fail to produce. This directly addresses the IQ Consortium's call for alternative in vitro tools capable of capturing inconsistent induction signals without requiring researchers to infer risk from CYP3A4 results. 

For low-turnover compounds, data show that TruVivo's 14-day phenotypic stability enables more reliable clearance predictions for metabolically stable molecules that suspension-based assays cannot adequately characterize.³ This closes the longevity gap and enables more reliable human PK translation for metabolically stable compounds, supporting better-informed PBPK modeling and clinical study design.

Integrating Multi-Dimensional DDI Data 

The IQ Consortium's appraisal reinforces an important shift underway in DDI science: moving toward integrated, multi-dimensional data stories for regulatory submissions rather than isolated in vitro endpoints. High-quality mechanistic parameters derived from advanced hepatic models can be fed directly into PBPK modeling frameworks, improving the alignment between simulated and observed clinical outcomes. Studies have reported that TruVivo-derived parameters improve PBPK predictions compared to data from traditional static models, supporting more confident, defensible regulatory decisions before a clinical DDI study is ever initiated.⁴ As PBPK modeling becomes increasingly central to ICH M12 submissions, the quality of the underlying in vitro data is essential. 

High-Fidelity DDI for the ICH M12 Era 

ICH M12 represents a rigorous and well-reasoned framework, and it is the beginning of better DDI science, but not the endpoint. As the IQ Consortium's appraisal makes clear, the remaining challenges in the induction of non-CYP3A4 pathways, low-turnover compound assessment, and accurate PBPK modeling require biology-first solutions.¹ Following the checklist leads you to compliance; using better biology increases confidence.

TruVivo provides the metabolic capacity, phenotypic longevity, and quantitative resolution that ICH M12 implementation demands, helping DMPK and clinical pharmacology teams generate a more accurate and translationally relevant data package for regulatory submissions, while improving confidence in both DDI risk assessment and human clearance predictions. To learn more about how TruVivo supports ICH M12-aligned DDI studies, visit LNHLifeSciences.org/TruVivo.

References 

1. Umehara K, et al. Future directions in drug-drug interaction evaluations: Industry perspective on the ICH M12 guidance. Drug Metab Pharmacokinet. 2026;66:101512. https://doi.org/10.1016/j.dmpk.2025.101512 

2. Ramsden D, et al. Quantitative clinical risk assessment of CYP2C, UDP-glucuronosyltransferase, P-glycoprotein induction, and complex drug-drug interactions using TruVivo human hepatocyte triculture platform. Drug Metab Dispos. 2025;53:100052. https://doi.org/10.1016/j.dmd.2025.100052 

3. Kukla et al. Clearance prediction with three novel plated human hepatocyte models compared to conventional suspension assays: Assessment with 50 compounds and multiple donors. Drug Metab Dispos. 2025. https://doi.org/10.1016/j.dmd.2024.100032

4. Slavsky M, et al. Physiologically based pharmacokinetic modeling to assess perpetrator and victim cytochrome P450 2C induction risk. Pharmaceutics. 2025. https://doi.org/10.3390/pharmaceutics17081085