From Intention to Execution

cross this series, we have explored how the female data deficit became embedded within drug development, why regulatory progress has not consistently translated into practice, and how behavioral and organizational dynamics continue to reinforce existing patterns. (See previous articles published in March, April, and June/July 2026.)

The industry is no longer lacking awareness of the problem. Guidance exists across regulators, expectations around inclusion have evolved, and the consequences of incomplete evidence are increasingly understood. The challenge looking forward is operationalizing inclusion consistently and measurably across drug development.

We also need greater focus on common women’s health conditions such as menopause, endometriosis, and polyendocrine metabolic ovarian syndrome (PMOS) to ensure that we truly understand them, that they have been studied through appropriately designed clinical studies (real-world evidence generation and clinical drug trials), and that the endpoints of these studies are meaningful and accepted by regulators. In women’s health, the problem is no longer whether we are running enough trials; it is whether those trials are capable of answering the questions that matter to women and their caregivers.

Closing the female data gap requires practical frameworks, measurable standards, and accountability mechanisms that support evidence generation across the full product lifecycle.

Importantly, it requires a shift from treating inclusion as a symbolic objective to treating it as a core component of evidence quality.

Endometriosis as a case study drives this point home. Despite affecting an estimated 10% of women globally, endometriosis illustrates a fundamental paradox in women’s health: the presence of numerous clinical trials without a commensurate depth of clinical understanding or therapeutic progress. Hundreds of endometriosis studies have been conducted, with large numbers of active and ongoing trials across global registries, suggesting at face value a healthy and active research ecosystem.

However, this volume masks a deeper structural issue: these trials are not generating the kind of evidence required to transform outcomes for women or understanding of the disease.

A significant limitation of the endometriosis evidence base is the historical lack of standardized, regulator-aligned clinical endpoints. Trials have used numerous different pain scales, quality-of-life instruments, and symptom measures, with no universal consensus regarding optimal outcome assessment. This heterogeneity reduces comparability between studies, complicates meta-analysis, and limits confidence in the generalizability of findings to the broader endometriosis population. While endometriosis trials provide clinically meaningful information, the absence of harmonized endpoints has constrained the development of a robust and consistent evidence base for regulatory and clinical decision-making.

A Practical Implementation Framework

To move from intention to impact, inclusion must be embedded throughout trial design, recruitment strategy, operational delivery, and evidence review processes.

This requires practical actions across three connected areas, with women at the core providing insights as part of patient and public involvement and engagement (PPIE) in trial design, recruitment and retention, and accountability and oversight.

These areas should not operate independently. Decisions made during protocol development directly influence recruitment feasibility, participant retention, evidence quality, and ultimately regulatory and clinical outcomes.

Inclusion From the Start

Inclusive trial design must be embedded in protocol development by including predefined endpoints (noting that these are not clearly defined in many women’s health conditions such as endometriosis), appropriate statistical powering strategies, and governance checkpoints that ensure inclusion remains visible throughout the program lifecycle.

Practical actions include:

• Pre-specifying gender-specific endpoints where clinically relevant
• Powering analyses appropriately to detect meaningful differences
• Building staged inclusion pathways for populations that are traditionally excluded
• Embedding flexible scheduling into protocols in order to optimize trial participation
• Requiring scientific justification for exclusion criteria
• Assigning accountability for inclusion at program-governance level.

Importantly, trial design must move beyond assumptions built around an “average patient” who, in practice, does not exist. Women experience important differences (compared to men) in pharmacokinetics, hormonal variation, comorbidity patterns, and adverse event profiles that can directly influence clinical outcomes. Certain women’s health conditions, such as endometriosis, are highly heterogenous in nature and so, even within the therapeutic area, the “average patient” may not exist.

Smarter methodologies may also help reduce operational concerns around inclusion. Staged inclusion models, physiologically based pharmacokinetic (PBPK) modeling, AI-supported simulation approaches, and hybrid trial designs can all support earlier identification of gender-specific safety and dosing considerations without significantly increasing study burden.

Designing Trials With Women’s Participation in Mind

Many barriers affecting women’s participation are operational, logistical, and behavioral, meaning that inclusion must be designed into the participant experience to overcome them.

Recruitment challenges have often been framed as participant issues rather than design limitations. However, trial designs frequently fail to reflect the realities of caregiving responsibilities, employment patterns, travel limitations, and chronic health burdens experienced by many women.

More practical recruitment and retention strategies include:

• Using the most appropriate referral pathways, including primary care networks
• Conducting feasibility searches using gender-specific metrics to identify suitable sites
• Reducing logistical barriers through childcare support, travel reimbursement, parking support, flexible appointments, and remote visits where feasible
• Incorporating decentralized or hybrid trial approaches
• Setting and monitoring recruitment targets by gender and life stage in real time
• Introducing corrective actions early when representation begins to drift.

Trust and relevance also remain critical. Partnerships with patient advocacy groups and community organizations can improve outreach, while public and patient involvement and engagement (PPIE) with women during protocol design and development of participant-facing materials can improve accessibility and trust.

Site capability is equally important. Investigators, principal investigators, and clinical staff should be trained in inclusive recruitment practices and unconscious bias awareness to help reduce disparities in enrollment and retention practices.

Monitoring participant experience continuously, rather than only at the time of enrollment, may also help identify where burden accumulates and where dropout risk increases. Feedback from female participants should inform future protocol and site improvements.

Ultimately, underenrollment should be viewed as a signal that trial design or delivery may not be functioning as intended.

What Gets Measured Gets Done

Accountability for inclusion has previously focused on broad participation metrics alone. However, representation without meaningful analysis does not necessarily improve evidence quality or clinical decision-making. More meaningful accountability frameworks will assess whether trials are capable of generating clinically actionable gender-specific evidence, and consider:

• Female participation relative to disease prevalence
• Whether gender-specific endpoints were prospectively defined
• Whether studies were statistically powered to detect relevant differences
• Retention rates across gender and life-stage groups
• Whether gender-specific evidence was sufficient to support product labeling and prescribing recommendations
• Post-marketing safety signals stratified by gender (whether gender-specific evidence was sufficient to support product labeling and prescribing recommendations)
• Time taken to identify gender-specific adverse reactions
• Downstream label updates or dosing changes.

Together, these measures shift the focus from participation alone towards quality evidence that drives decision-making across the product lifecycle.

Incentives must also align with the quality of the evidence. Development systems have traditionally rewarded speed, efficiency, and predictability, which can unintentionally discourage more inclusive approaches that are perceived as operationally complex.

Embedding inclusion metrics into program governance, regulatory review, and organizational performance measures can help rebalance these incentives. Feedback loops are important. Recruitment outcomes, retention patterns, protocol deviations, and evidence gaps should be reviewed continuously (“live”) rather than retrospectively.

Organizations that learn rapidly from previous trials will be better positioned to improve inclusion consistently over time.

The Role of Regulators

Over the past decade, guidance relating to gender-specific evidence generation has evolved significantly across agencies and organizations, including the US FDA and NIH, EMA, and ICH. However, variability in interpretation and implementation continues to create uncertainty around expectations in practice.

When regulatory expectations are perceived as optional, behavioral defaults tend to persist.

A more consistent regulatory approach would help shift inclusion from an aspirational objective towards a standard component of evidence generation. In many cases, clearer expectations and more predictable review signals may be as important as additional regulation itself.

Practical regulatory levers could include:

• Mandatory gender-specific analysis plans where clinically relevant
• Stronger justification requirements for exclusion criteria
• Clearer expectations for early-phase dose optimization
• Conditional evidence requirements linked to post-market commitments
• Harmonization of expectations across regions where possible.

Consistency matters because development teams optimize around what is most likely to succeed operationally and regulatorily. When regulatory agencies signal that gender-specific evidence is expected, reviewed consistently, and linked to decision-making, sponsors are more likely to embed inclusion earlier within development pathways.

Regulators globally must also acknowledge that evidence in women’s health conditions, such as endometriosis, is lacking and that research should be incentivized in this space to advance our knowledge and change clinical practice in such areas.

Making Inclusion Operational

Closing the female data gap does not require brand-new scientific frameworks. Many of these tools already exist. The challenge is applying them consistently, measuring their impact, and embedding accountability within development pathways.

Organizations that operationalize inclusion effectively will not only improve representation; they will generate more robust evidence, reduce downstream regulatory and safety risk, and improve real-world outcomes for patients.

The future of inclusive drug development will be determined not by awareness alone, but by execution.