Beyond Compliance: What ICH M15 Means for the Future of Drug Development

Drug development teams are being asked to make high-stakes decisions with tighter timelines, more targeted therapies, and smaller patient populations than ever before. In many cases, empirical data alone is no longer sufficient to answer the questions sponsors need to solve.

That reality is reshaping the role of Model-Informed Drug Development (MIDD) across the industry.

For years, modeling and simulation were often treated as supporting technical activities that operated alongside broader development strategy. Today, quantitative approaches are increasingly part of how organizations evaluate uncertainty, assess risk, and support program strategy and regulatory decisions across the development lifecycle.

The recently published ICH M15 general principles for model-informed drug development final guideline 2026 formalizes that shift.

Its significance extends beyond the framework itself. More importantly, the guidance encourages a more explicit discussion of how evidence is generated, integrated, interpreted, and ultimately trusted in development and regulatory decisions.

Historically, regulatory conversations often centered on whether a model was technically acceptable. Under ICH M15, the more important question becomes whether the evidence generated by the model is appropriate for the decision being made.

That distinction places quantitative science much closer to the center of development strategy.

As Eva Berglund, VP of Clinical Pharmacology and Regulatory Strategy at Certara, notes:

“The M15 guidance is fully integrating MIDD approaches into drug development strategy. What is requested, but also what becomes possible, changes significantly when MIDD is viewed as part of an integrated development strategy rather than standalone modeling activities.”

MIDD is becoming embedded across drug development

Quantitative approaches now support decisions across nearly every stage of development, including first-in-human study design, drug-drug interaction assessment, formulation bridging, evaluation in special populations, dose selection and justification, trial optimization, and benefit-risk assessment.

As therapies become more complex and timelines continue to compress, organizations are relying more heavily on predictive approaches to guide decisions earlier in development.

One of the most important implications of ICH M15 is the growing emphasis on integrated evidence strategies rather than isolated modeling exercises.

Organizations are steadily combining Physiologically Based Pharmacokinetic (PBPK) modeling, Population Pharmacokinetic/Pharmacodynamic (PK/PD) modeling, exposure-response analysis, translational modeling, Quantitative Systems Pharmacology (QSP), clinical trial simulation, and Model-Based Meta-Analysis (MBMA) to address development questions that no single methodology can address independently.

“I think it is very useful to really combine MIDD methods,” Berglund explains. “That generates the most powerful outcomes.”

For many organizations, the challenge is no longer technical capability alone. Success increasingly depends on how effectively teams align quantitative science, clinical strategy, regulatory planning, and evidence generation early enough to influence critical decisions.

Defining the right question matters

One of the most important aspects of ICH M15 is the emphasis placed on defining both the “question of interest” and the “context of use.”

At first glance, these may appear procedural. In practice, they fundamentally shape how model credibility is evaluated.

The guidance makes it clear that model credibility cannot be evaluated independently of the decision the model is intended to inform.

A model supporting exploratory translational work carries a very different evidentiary burden than one intended to replace a clinical study, support dose optimization, or inform labeling recommendations. Validation therefore becomes situational rather than universal.

This introduces a more nuanced approach to regulatory evaluation, where evidence is assessed relative to factors such as:

• model influence
• consequence of a wrong decision
• available supporting evidence
• uncertainty characterization
• intended regulatory impact

Historically, organizations often faced uncertainty regarding how emerging modeling approaches would be evaluated across agencies or review divisions. ICH M15 helps establish a more consistent framework for discussing model-informed evidence, uncertainty, and decision risk.

Regulatory engagement around MIDD is expanding

Another important signal behind the momentum of ICH M15 is the increasing formalization of regulatory engagement around Model-Informed Drug Development itself.

Over the past several years, FDA has expanded opportunities for sponsors to engage regulators earlier on quantitative strategies through initiatives such as the MIDD Paired Meeting Pilot Program. These interactions have enabled organizations to discuss context of use, evidence generation strategies, model credibility, and opportunities to integrate quantitative approaches earlier in development planning.

At the same time, global regulatory alignment around MIDD continues to evolve. Similar discussions are increasingly occurring across international agencies, including growing interest from EMA and other regulators in model-informed drug development guidance around structured approaches to model-informed evidence generation and regulatory decision-making.

Together, these developments reinforce that model-informed approaches are no longer viewed as isolated technical exercises, but as integrated components of modern development and regulatory strategy.

Transparency is becoming a regulatory strategy advantage

One of the strongest themes emerging from ICH M15 is the growing importance of transparency.

Regulatory confidence depends not only on technical rigor, but also on how clearly organizations communicate assumptions, limitations, uncertainty, validation strategy, evidentiary integration, and decision rationale.

This is particularly important for mechanistic approaches such as PBPK and QSP, where biological assumptions often extend beyond directly observable clinical data.

The guidance moves the conversation away from simplistic model classifications and toward something more meaningful: the justification behind those assessments and how uncertainty is being managed.

As Berglund explains:

“What is most important is your justification, your description of your case.”

“It’s not about the labels or rankings themselves,” Paul Diderichsen, VP of Quantitative Science Services, notes. “It’s really the transparency of the reasoning behind them.”

The broader implication is clear: uncertainty cannot always be eliminated, but it can be understood, characterized, and managed appropriately.

Organizations that establish structured evidence generation strategies early, rather than attempting to justify models retrospectively near submission, are likely to be in a much stronger position as regulatory expectations continue to evolve.

Mechanistic modeling is entering a different regulatory era

The expanding role of PBPK, QSP, and related approaches such as MBMA reflects a broader evolution in how development programs are being designed and evaluated.

A decade ago, mechanistic modeling discussions were still frequently met with skepticism outside of well-established applications such as drug-drug interactions. Acceptance often varied by region, therapeutic area, and reviewer familiarity.

That environment has changed considerably.

PBPK has steadily expanded into formulation bridging, pediatric extrapolation, pregnancy and lactation, organ impairment, special populations, and early development strategy. Under ICH M15, PBPK now has a clearer framework for demonstrating credibility and context of use in regulatory submissions. QSP is increasingly being applied across translational medicine, oncology, immunology, biomarker strategy, and complex dose optimization challenges where empirical approaches alone may not fully answer critical development questions.

At the same time, MBMA is helping organizations integrate data across studies to support comparative efficacy assessments, dose selection, benefit-risk evaluation, and portfolio strategy decisions earlier in the lifecycle.

Regulatory discussions are also becoming more sophisticated. Agencies are increasingly comfortable evaluating mechanistic assumptions, uncertainty characterization, evidentiary integration, verification and validation strategies, and model influence relative to development decisions.

Karen Rowland Yeo, SVP of Clinical and Regulatory Strategy at Certara, described PBPK as:

“a great fit for ICH M15.”

At the same time, ICH M15 makes one point increasingly clear: sophisticated models without clear context, transparency, or supporting evidence are unlikely to build regulatory confidence.

The future will likely depend less on standalone modeling exercises and more on integrated evidence strategies capable of supporting meaningful development decisions.

QSP is expanding across the development lifecycle

QSP is also entering a different stage of maturity across the industry.

What was once viewed primarily as an exploratory or research-focused discipline is now being applied more broadly to translational strategy, biomarker development, oncology, immunology, combination therapies, and clinical trial optimization.

As development programs become more biologically complex, QSP is proving especially valuable in situations where empirical approaches alone may not provide sufficient mechanistic insight.

Organizations are increasingly applying QSP to:

• support translational medicine strategies
• evaluate biomarkers
• optimize dosing approaches
• better understand disease and treatment dynamics across patient populations

Piet van der Graaf, SVP and Head of Quantitative Systems Pharmacology at Certara, summarized this evolution clearly:

“QSP can really be used across the R&D cycle.”

The growing role of QSP reflects a broader industry movement toward integrating mechanistic understanding earlier and more consistently across development programs.

In parallel with evolving regulatory expectations such as ICH M15, organizations are increasingly evaluating how multiple MIDD approaches can work together to support more informed and efficient development decisions.

The future of Model-Informed Drug Development

ICH M15 is often described as a guidance for modeling and simulation. Its broader significance may have less to do with modeling itself and more to do with how the industry approaches evidence generation.

The guidance reflects a growing recognition that modern drug development operates in environments where uncertainty cannot always be resolved through traditional empirical approaches.

That does not diminish the importance of clinical evidence. If anything, it reinforces the need to generate the right data and integrate evidence more strategically.

As development programs become more targeted and complex, organizations will need to ensure that evidence is fit for purpose and capable of supporting confident regulatory and development decisions.

In this environment, quantitative science becomes less about generating models and more about helping organizations make scientifically grounded decisions under increasingly complex conditions.

Organizations that benefit most from ICH M15 may not necessarily be those with the most sophisticated models, but those best able to integrate quantitative reasoning into development strategy early enough to influence critical decisions.

As regulatory expectations continue to evolve, the ability to connect quantitative evidence to development strategy will become increasingly important.

Evaluating operational readiness for ICH M15

As organizations operationalize ICH M15, many are evaluating how existing development frameworks align with evolving expectations around model credibility, transparency, and evidence integration.

Explore Certara’s free ICH M15 Interactive Scorecard to evaluate your organization’s preparedness, identify potential gaps, and understand where stronger model-informed development strategies may be needed.

You can also access the on-demand webinar featuring Certara experts discussing practical considerations for implementing ICH M15 across modern drug development programs.