Download the PDF poster here.

Background

ARTEMIA is a phase III trial comparing OSE2101, a cancer vaccine, to docetaxel in HLA-A2-positive patients with metastatic NSCLC and secondary resistance to Immune Checkpoint Inhibitor (ICI), with overall survival (OS) as primary endpoint. To consider additional outcomes in a single analysis, an exploratory endpoint estimating the Net Treatment Benefit (NTB) of OSE2101 versus docetaxel is planned. Hereby we report the preferred outcomes and their priority order appraised by the investigators for the NTB analysis.

Methods

The elicitation software One2Treat Voice captured which outcomes were prioritized by the investigators, their relative importance and meaningful thresholds. Investigator could choose up to 5 out of 7 outcomes selected from the study’s main endpoints: OS, Progression-Free survival (PFS), QLQ-C30 Global Quality of Life (QoL), physical QoL, role QoL, side-effect burden QoL, and serious adverse events (SAEs) occurrence. The software used an adaptive algorithm to present simulated pairs, distinguishing between two treatments without disclosing investigational products. For each pair, investigators selected which patient had the better overall situation. Preferences were inferred and aggregated to inform the design of the NTB analysis. Participation was voluntary and anonymized.

Results

From March 17 to 24, 2025, investigators (N=29) completed the questionnaire in an average of 9 minutes [min: 4, max: 24]. Five outcomes were selected by investigators, with overall survival (OS) preferred by 72% of investigators, followed by Global QoL, PFS, side effects burden, and SAEs. The corresponding thresholds were 3 months for OS, 6 months for PFS, and 1-level improvement for QoL and side effects.

Conclusions

The One2Treat Voice software enabled rapid collection of investigator preferences in the OSE ARTEMIA trial for relevant outcomes, their prioritization, and the corresponding thresholds. This approach ensures that the planned Net Treatment Benefit analysis is fully aligned with clinical practice and actively involves investigators in the trial design process.

Clinical trial identification

NCT06472245.

Legal entity responsible for the study

OSE Immunotherapeutics SA.

Louvain-la-Neuve, Belgium — 4^th September 2025 

One2Treat SA, a fast-growing technology company transforming how the patient voice is integrated into clinical development, announced today the successful completion of a planned seed extension to accelerate its software platform development.

In parallel, One2Treat has relocated to a larger office in Louvain-la-Neuve to support its continued growth.

Shareholder confidence accelerates One2Treat’s investment in software platform development.

The conclusion of One2Treat’s planned seed extension funding round marks a key milestone in the company’s growth. This investment follows the successful deployment of the One2Treat Insights^® module across multiple live projects and the recent release of the One2Treat Voice^® module. It reflects the confidence of initial shareholders in One2Treat’s unique approach to answer the growing needs of the biopharma industry to both increase productivity and better reflect what matters to patients and clinicians.

The funding supports the continued development and scaling of One2Treat’s cloud-based software platform. This platform integrates diverse patient-focused outcomes into a single, comprehensive assessment of treatment effects, enabling a clearer understanding of the Net Treatment Benefit. The platform answers strategic needs for clinical development decisions, but also supports the overall medical value of a new treatment during regulatory discussions, HTA and commercialization.

“Based on multiple recent successes, our shareholders were keen to accelerate the investment in our platform development.  In addition, we offered every employee the opportunity to become a shareholder, and all chose to take part, highlighting a deep, shared commitment to our mission of putting patient voices at the center of clinical research.”

— Sébastien Coppe, CEO, One2Treat

Move to larger office supports One2Treat’s planned team expansion

Alongside the capital increase, One2Treat has moved to a new office in Louvain-la-Neuve, a dynamic academic and tech ecosystem just outside Brussels.

“The new space provides a larger, more modern and collaborative environment for the expanding team, fostering innovation and facilitating closer partnerships with key academic and industry stakeholders.”

• Marc Buyse, Founder One2Treat

-END-

About One2Treat

One2Treat is dedicated to transforming the way biopharmaceutical companies design, analyze and interpret randomized clinical trials, and how the overall medical value of a treatment may be communicated. Through its innovative software platform and patient-centered methodologies, One2Treat helps sponsors incorporate the patient’s voice into early trial design, endpoint selection, and treatment value assessment. By aligning clinical evidence generation with patients and clinicians’ needs, One2Treat supports more meaningful clinical trials, efficient decision making and enhanced regulatory discussions, leading to faster market access.

For more information about One2Treat and its innovative approach to clinical trial design and market access, please visit: www.one2treat.com.

Media Contact

Tom Mann 

Clinical Solutions Engagement Lead, One2Treat

Tom.Mann@one2treat.com

Original interview with ARCP for Clinical Trials Day 2025 available here. Author: Mathilde Tournay

My clinical research power is…

…bridging the gap between statistical rigor and clinical development. As a biostatistician, I bring deep expertise in data and complex statistical methods together with a solid understanding of science and medicine to ensure that clinical evidence is not just methodologically sound but also meaningful. My goal is to transform data into actionable insights that truly support better decisions for patients and clinicians alike.

The greatest challenge I see to clinical research right now is…

…designing trials that can manage growing complexity while staying focused on patient needs. As trials evolve to include more data, endpoints, and subgroups, it becomes harder to reflect the diverse preferences of the people they’re meant to serve. Too often, key outcomes are chosen without patient input, leading to evidence that misses the mark on real-life impact.

The greatest opportunity I see for clinical research in the near future is…

 …embedding patient preferences very early into the design of trials—starting with how outcomes are selected and prioritized. Tools that enable this shift will drive more meaningful evidence generation, reduce trial inefficiencies, and accelerate the delivery of treatments that patients truly value. We must do better at integrating patient priorities from the outset and making full use of the data we collect to ensure research reflects what matters most to those living with the condition.

Original content written for Discover Pharma, available here. Author: Pascal Piedbois.

As oncology research continues to evolve, the focus is increasingly shifting from traditional endpoints to patient-centered outcomes. Ahead of ASCO 2025, Pascal Piedbois, discusses how methodologies like Generalized Pairwise Comparisons (GPC) are transforming clinical trials to better reflect the realities of patient care. In this insightful Q&A, he shares his expectations for ASCO, explains the practical impact of GPC, and outlines how One2Treat is helping sponsors build more meaningful and efficient oncology studies.

What are you most looking forward to at ASCO 2025, and how do you see it shaping the future of oncology research?

I am most looking forward to seeing the latest advancements in personalized medicine and immunotherapy. But more than that, I expect ASCO 2025 to highlight a growing emphasis on comprehensive approaches that could revolutionize oncology research strategy. Approaches that not only aim to extend life but also respect patient priorities and preferences. The future of oncology lies in combining clinical efficacy with a deeper understanding of what matters most to patients. That mindset is starting to shape how we design trials, evaluate benefits, and ultimately guide treatment decisions.

As One2Treat attends ASCO, are there any particular scientific trends or sessions you’re especially excited about?

I’d like to attend sessions that go beyond the science of new treatments to address how we design research that truly reflects patient needs. There is growing interest in understanding patient preferences and in translating those insights into concrete changes in trial design, whether it’s how we define meaningful benefit, how we prioritize outcomes, or how we engage patients early in the protocol development process. ASCO is increasingly becoming a forum not just for drug innovation, but for rethinking how we include the patient voice in the way evidence is generated.

Traditional oncology trials often focus on tumor shrinkage and survival metrics. Why do you believe it’s time for a shift toward more patient-centric approaches like Generalized Pairwise Comparisons (GPC)?

As medical oncologists, we rely on endpoints like tumor response and overall survival for good reason. They’re critical indicators of efficacy. But patients experience treatment through a broader lens: side effects, daily functioning, and long-term quality of life are often just as impactful as how long they live. What’s needed isn’t a replacement of our traditional endpoints, but an evolution, one that allows us to assess treatment benefit more holistically.

Generalized Pairwise Comparisons (GPC) supports that evolution. It respects the hierarchy of what matters most in oncology — often survival first — while also making room for additional outcomes that reflect the reality of patient experience. It’s a way to enrich our evidence without compromising scientific rigor.

Can you explain, in simple terms, how GPC works and what makes it more reflective of patient priorities like safety and quality of life?

GPC, or Generalized Pairwise Comparisons is a statistical method that allows us to compare treatments across several outcomes, in a way that mirrors clinical decision-making.

At its core, GPC works by forming all possible pairs between patients in the treatment group and those in the control group. For example, if there are 10 patients in each group, we evaluate 100 unique comparisons. For each pair, we assess who had the better outcome based on a ranked list of priorities — typically starting with survival, followed by quality of life, side effects, and so on. If one patient clearly does better on the most important outcome, that pair is counted accordingly. If not, we move down the list.

What makes GPC powerful is that it doesn’t force us to choose a single primary endpoint, it allows us to integrate several outcomes, based on their clinical relevance. The result is a single, interpretable measure called Net Treatment Benefit (NTB), which is simply the net difference between the probability that a random patient in the treatment group has a better outcome than a random patient in the control group, and the probability of the opposite occurring. This kind of quantitative analysis gives a more complete picture of treatment impact, one that aligns with how patients and clinicians weigh trade-offs in real life.

How receptive are regulators and sponsors to using GPC in real-world trials — and what progress have you seen?

I think that regulators are increasingly receptive to methodologies like GPC, especially when they help capture clinical benefit in a way that reflects the totality of patient experience. What matters most to agencies like the EMA or FDA isn’t whether a method is novel, but whether it is clearly pre-specified, well-justified, and clinically interpretable. GPC has already been included in several regulatory submissions, often as a key secondary or exploratory analysis, and fits well within current initiatives focused on patient-centric evidence generation — such as FDA’s Project Patient Voice or Project Optimus.

On the sponsor side, we’ve seen growing adoption, particularly in trials where traditional endpoints alone may not tell the full story — for example, in rare diseases or complex oncology settings. What’s shifting is the mindset: the question is no longer whether we should consider patient-centered methodologies, but how we can implement them in a rigorous, operationally feasible way. GPC offers a structured framework to do just that.

What are some of the key challenges to adopting alternative trial methodologies in oncology?

One of the biggest challenges is cultural. As clinicians and researchers, we’re trained to think in terms of traditional endpoints — overall survival, progression-free survival, objective response — and those remain essential. But broadening our view to include prioritized, multi-dimensional outcomes requires a shift in mindset. It means rethinking what we consider “primary” and accepting that benefit can’t always be reduced to a single number or curve.

Another key challenge lies in the practical setup. For methods like GPC to work, we need to define a clear hierarchy of outcomes, and that’s not always straightforward. It requires early, structured input from both clinicians and patients to understand which outcomes truly matter and in what order. These preferences need to be captured before the trial begins, and doing so in a consistent, rigorous way across sites and stakeholders takes time, planning, and the right tools.

Finally, there’s an educational gap. Many clinicians are unfamiliar with these approaches, and sponsors may hesitate to deviate from conventional designs unless there’s a clear regulatory or strategic incentive. Overcoming that inertia takes time, but it starts with building confidence in methods that are both scientifically rigorous and clinically meaningful.

How does One2Treat help companies overcome those barriers — technically, scientifically, or culturally?

At One2Treat, we support sponsors in making early strategic decisions that place patient and clinician priorities at the center of trial design. A recurring challenge is identifying which outcomes to measure and how to prioritize them. To address this, we’ve developed One2Treat Voice, a software solution that facilitates the structured collection of preferences from key opinion leaders, investigators and patient advocates, enabling prioritization that’s evidence-based and operationally feasible.

This is part of a broader suite of tools we’re building to support modern trial design. One2Treat Insights helps sponsors to leverage the totality of evidence from prior trials to inform endpoint selection and data interpretation, while One2Treat Design enables simulation-based planning and sample size calculation to complement methodological guidance. Alongside these tools, we provide scientific and strategic advice to ensure that trial designs incorporate a more comprehensive and clinically relevant estimation of the Net Treatment Benefit, helping ensure that trial outcomes better reflect patient priorities, making the resulting evidence more clinically meaningful.

Beyond trial interpretation, NTB can also inform early R&D go/no go decisions by quantifying benefit-risk trade-offs across multiple outcomes, helping teams prioritize compounds with the most patient-relevant impact. In HTA contexts, NTB offers a transparent, interpretable metric that aligns with payer expectations for comprehensive value assessment.

Our goal is to make the adoption of patient-centered methodologies not just possible, but practical, by combining robust tools with the right scientific framework early in the trial design stage.

Could you share any case studies or examples where GPC made a significant impact on trial outcomes or interpretation?

GPC has already been used to provide a much richer understanding of treatment effects, particularly in complex clinical scenarios where relying on a single primary endpoint would have fallen short. In these situations, where multiple clinical outcomes may play a decisive role, GPC enables estimating a quantitative benefit risk balance to support decision-making.

This was exactly the challenge addressed in the SHAPERS trial for older patients with rectal cancer. The investigators needed to evaluate whether a shorter, less intensive treatment could offer a better overall balance of benefit and harm compared to total neoadjuvant therapy. Rather than using a traditional non-inferiority design, which would have required a large sample size to detect equivalence based on a single endpoint, the team leveraged GPC to estimate a Net Treatment Benefit based on multiple prioritized outcomes: survival, tumor progression, neuropathy, and toxicity. This approach allowed the trial to test for superiority, not just equivalence, while also ensuring that the primary analysis reflected trade-offs meaningful to patients. It offered a more efficient, clinically relevant framework that traditional endpoints alone could not provide

Another compelling use of GPC comes from re-analyses of existing trials. In a JAMA Oncology study, Péron et al. showed that the Net Treatment Benefit provided clearer, more intuitive insight than hazard ratios, especially when survival curves crossed or treatment effects emerged late. By reframing the question as “What’s my chance of living meaningfully longer with treatment?”, GPC helped uncover clinically relevant benefits that standard analyses often obscure. This approach allows us to extract more patient-relevant evidence from data we already have.

Finally, we’re now exploring how GPC can support dose selection in Phase II clinical trials, in alignment with FDA’s Project Optimus. By comparing multiple doses not just on efficacy but also on tolerability and quality of life, NTB offers quantitative evidence towards the most balanced treatment to support discussions with regulatory bodies.

Where do you see the biggest opportunities for improving oncology trials over the next five years?

We have a tremendous opportunity to rethink how we define and measure success in oncology trials. Over the next five years, I believe the biggest impact will come from integrating patient-centered methodologies into earlier stages of trial design, not just as an afterthought, but as a core design principle. By embedding structured patient and clinician input into endpoint selection and benefit-risk balance evaluation, we can generate evidence that is not only scientifically rigorous but also clinically meaningful.

Another key area is the smarter use of prior clinical trial data. Leveraging evidence through quantitative frameworks like NTB allow us to leverage prior evidence to inform endpoint prioritization, reduce sample size requirements, and design trials that are more focused and efficient. Taken together, these strategies can accelerate development while ensuring that trials answer the questions that matter most to patients and clinicians alike.

If you could change one thing about how oncology trials are currently designed or evaluated, what would it be?

I would change the way we think about what constitutes “meaningful benefit.” Too often, trial designs are anchored to endpoints that may not always reflect all that matters to patients. If I could change one thing, it would be to make the explicit prioritization of outcomes — guided by both clinical insight and patient perspective — a standard part of trial design.

This means going beyond survival curves and response rates to also consider factors like symptom burden, treatment-related toxicity, and quality of life outcomes. It also means valuing methods that allow for the integration of these outcomes in a structured, interpretable way, such as GPC. Redefining what constitutes benefit is essential if we want oncology clinical trials to keep pace with the growing emphasis on patient centricity. It’s not enough to demonstrate efficacy, we need to ensure that evidence reflects the outcomes patients value and the trade-offs they are actually willing to make.

Original content written for DIA available here. Author: Samuel Salvaggio

Patient-centricity has become a focal point in the evolution of clinical trials, emphasizing outcomes meaningful to patients. The challenge lies in balancing rigorous scientific evaluation with incorporating patient experiences and preferences.

Current approaches to evaluating treatment efficacy often fail to capture the complexity of patient needs, particularly in conditions with diverse symptomatic or functional impacts. Conventional statistical analyses typically assess outcomes in isolation, neglecting their interactions and the multidimensional nature of treatment effects. This narrow focus can overlook clinically relevant improvements in symptoms, function, or tolerability, leading to an incomplete understanding of a treatment’s true benefits and risks.

Balancing the demands of scientific rigor with the reality of how patients experience illness is now a central challenge in trial design—one that requires solutions capable of integrating clinical relevance with lived experience. Today, market authorizations for new treatments are based on demonstrating superiority on a single clinical outcome. This paradigm can disregard the constellation of diverse effects a treatment may produce and the multidimensional needs and preferences of patients. As a result, it often fails to capture the complexity of patient experiences and overlooks important interactions and broader implications of treatment effects that matter greatly to those living with illness.

As clinical research moves toward greater patient-centricity, trials must evolve to reflect outcomes genuinely meaningful to those they seek to help.

The Net Treatment Benefit (NTB), a robust statistical measure derived from the Generalized Pairwise Comparisons (GPC) methodology, addresses this challenge. NTB integrates multiple prioritized outcomes into a single, interpretable metric, comprehensively reflecting treatment impacts. By aligning trial designs more closely with patient preferences and clinical realities, NTB enhances clinical relevance, optimizes trial efficiency, and ensures that trials truly reflect patient needs and priorities. Adopting such innovative methodologies will drive the next generation of clinical trials toward greater alignment with patient realities and preferences.

Towards Patient-Centric Clinical Trials

In recent years, regulatory agencies have been increasingly encouraging such approaches. The US Food and Drug Administration (FDA) has underscored the importance of incorporating patient perspectives into the drug development process, notably through its Patient-Focused Drug Development (PFDD) guidance series. The European Medicines Agency (EMA) has similarly called for the integration of patient perspectives in benefit-risk assessments and clinical trial designs. These documents encourage sponsors to systematically capture and integrate patient input when defining clinical outcomes, recognizing that patients may prioritize aspects of treatment beyond traditional clinical endpoints.

However, moving from intention to implementation remains a major challenge. Despite clear guidance, most trials continue to fall back on conventional endpoints, in part because there is no standard method to translate patient preferences into structured, regulatory-grade evidence. Sponsors are often left asking:

• Which outcomes should we prioritize?
• How do we quantify their relevance?
• And how can we analyze them together in a way that remains statistically sound and acceptable to regulators?

Introducing the Net Treatment Benefit

The Net Treatment Benefit (NTB) offers a scientifically grounded and patient-centered way to evaluate treatment effects. Developed over more than a decade of academic research and rooted in the Generalized Pairwise Comparisons (GPC) framework, NTB provides a robust and validated alternative to single-endpoint analyses. It allows multiple outcomes—of any type, including efficacy, safety, and patient-reported measures—to be integrated into a single, interpretable hierarchical composite endpoint.

Rather than analyzing outcomes marginally, NTB considers them jointly, respecting both their clinical importance and the order in which they matter. This makes it particularly well suited for trials that aim to reflect patient preferences and experiences. It is both statistically rigorous and adaptable to the complexity of modern clinical research.

Applications in Cardiovascular and Rare Disease and Regulatory Considerations

The practicality and real-world relevance of the Net Treatment Benefit have been demonstrated across several therapeutic areas, most notably in oncology, cardiovascular disease, and rare disorders, three settings where conventional approaches often fall short.

In the cardiovascular domain, NTB played a pivotal role in the approval of two treatments for transthyretin amyloid cardiomyopathy, a progressive and life-threatening condition. In both of these phase 3 trials, the NTB methodology was used as the prespecified primary analysis, prioritizing survival over hospitalization. This allowed the trials to more effectively capture the composite clinical benefit of treatment—not just prolonging life, but reducing the frequency of hospital stays, which are highly relevant to patients and healthcare systems alike. Importantly, numerous trial designs incorporating this methodology are now widely accepted by regulators, establishing NTB as a standard approach that meets evidentiary requirements for market authorization while providing a more patient-relevant assessment of treatment effects. Reflecting this growing acceptance, a search of the NIH-affiliated website ClinicalTrials.gov in May 2025 identified 24 phase 3 industry-sponsored trials in cardiometabolic diseases and obesity that employed the methodology for their primary endpoint.

Similarly, in the rare disease space, NTB has offered important insights where traditional methods have fallen short. For example, in Pompe disease—a progressive neuromuscular disorder—the phase 3 COMET trial originally failed to meet its primary endpoint using a conventional, single-outcome analysis focused on forced vital capacity. However, a subsequent GPC-based analysis, which integrated additional functional outcomes such as the six-minute walk test, revealed a statistically significant advantage for the experimental therapy. This reanalysis captured a broader picture of benefit, better aligned with patient experiences and expectations. In rare diseases, where trials are often constrained by small sample sizes and symptom heterogeneity, NTB provides a valuable way to maximize information gained from each participant while highlighting clinically meaningful effects.

Together, these examples illustrate how NTB can strengthen the case for therapeutic benefit by offering a more complete, patient-centered assessment—one that is not only methodologically sound but also compatible with regulatory expectations.

From Principles to Practice

As clinical research embraces patient-centricity, trial methodologies must evolve to meet the moment. Relying on univariate primary endpoints is no longer sufficient in a landscape where patients demand, and regulators support, a fuller picture of the benefits and risks of treatment. The NTB can offer a statistically robust, flexible, patient-aligned solution—one capable of integrating what matters most to patients into a single, interpretable assessment.

With case studies in different therapeutic areas, including cardiovascular and rare diseases, and demonstrated acceptability by regulators, NTB moves beyond theory into practical impact. It not only strengthens the scientific integrity of trials but also ensures that the evidence generated is truly reflective of patient priorities.

Realizing the full potential of NTB requires active collaboration across stakeholders to determine which clinical outcomes should be prioritized and incorporated into the primary endpoint. Patients, investigators, and clinicians should be engaged as early as possible to capture the preferences of this diverse group of stakeholders. Embracing this shift toward patient-centered outcome prioritization can offer sponsors a strategic advantage, while regulators and HTA bodies can play a key role by clarifying how such composite endpoints will be evaluated, supporting broader adoption in clinical development. Finally, sponsors must embrace this shift—not just as a compliance obligation but as a strategic advantage. Trials designed with NTB can be faster, leaner, and more aligned with payer expectations, increasing the likelihood of both regulatory success and patient impact.

As the expectations of patients, regulators, and health systems evolve, so must our tools. Methodologies like NTB represent a necessary step forward—transforming patient-centricity from a guiding principle into a measurable standard in clinical trial design.

Louvain-la-Neuve, Belgium — June 17th, 2025 

One2Treat SA, a fast-growing tech company incorporating the patient voice in all strategic decisions about treatment assessments in Pharma R&D, today announced the launch of the One2Treat Voice app, a new module of their software platform. 

This new milestone supports One2Treat’s commitment to developing its software platform to better express the overall medical value of a treatment.  One2Treat Voice is an innovative software designed to identify and prioritize the clinical outcomes that matter most from a patient or a clinician perspective. It enables the trial sponsor to incorporate the patient voice in the definition of endpoints in clinical trials, but also to support more holistic and clinically meaningful treatment assessments based on randomized clinical trials.  

This strategic development supports One2Treat’s mission to transform how clinical trials are designed and how treatment value is assessed, anchoring every decision in the perspective of what matters most for patients. 

“This past year has shown that patient-centricity and scientific rigor not only coexist but strengthen each other in clinical developments. With strong traction from our partners and the release of One2Treat Voice, we are accelerating a shift in the industry toward clinical development that is more relevant – and transparent – to what matters most to patients, clinicians, regulators and pharma sponsors.” 

Marc Buyse – One2Treat Founder 

Launch of One2Treat Voice: capturing stakeholder priorities to guide endpoint selection 

One2Treat has officially launched One2Treat Voice, a software module designed to capture and prioritize inputs from patients, clinicians, regulatory bodies and clinical trial sponsors. The result is a structured, data-driven prioritization of clinical outcomes, enabling the definition of multi-dimensional primary endpoints using the Net Treatment Benefit (NTB) methodology.  

“By embedding diverse stakeholder voices early in the protocol development process, One2Treat Voice helps sponsors design trials that are not only scientifically robust but also aligned with clinical development’s stakeholder values and expectations, while often allowing for significant sample size reductions.”  

Pascal Piedbois, Chief Medical Officer, One2Treat 

One2Treat Voice may also help physicians and patients express what matters most to them, leading to a clearer decision about the most appropriate approved treatment – based on past randomized clinical trial data. 

Expanding a cloud-based platform for multi-dimensional treatment assessment 

One2Treat Voice is part of a broader cloud-based platform that supports strategic decision-making throughout the clinical development process, from protocol design to data analysis. The platform empowers sponsors to assess the totality of the evidence and understand the overall medical value of a treatment. One2Treat’s platform is also used to support trial design, go/no-go decisions, dose selection, market access planning, and commercialization based on patient-and clinician-prioritized outcomes. 

“One2Treat Voice integrates quantitative and qualitative approaches to collect and prioritize patient preferences. Its adoption by pharma sponsors to collaborate with patient advocates, site investigators, and regulators highlights the industry’s commitment to more patient-focused drug development, by focusing treatment assessment on what matters most.” 
 

Sébastien Coppe, Chief Executive Officer, One2Treat 

About One2Treat 

One2Treat is a fast-growing tech company incorporating the patient voice in all strategic decisions about treatment assessments in Pharma R&D. One2Treat is dedicated to transforming the way biopharmaceutical companies design and evaluate clinical trials, and how the overall medical value of a treatment may be communicated, by integrating multiple meaningful dimensions in the treatment assessment 

For more information about One2Treat and its innovative approach to clinical development and market access, please visit: www.one2treat.com. 

Media Contact 

Tom Mann   

Clinical Solutions Engagement Lead, One2Treat 

Tom.Mann@one2treat.com 

www.one2treat.com 

Original content written for The Journal for Clinical Studies, available here. Author: Tom Mann

Introduction

Rare disease clinical trials face a confluence of challenges: limited patient populations, heterogeneity in disease progression, and often a lack of established outcome measures. Yet the stakes involved are exceptionally high. For the over 300 million people living with a rare disease worldwid[SS1] e (1), most of whom lack access to effective therapies, each trial represents a vital opportunity—not just to generate evidence, but to shape treatments that meaningfully improve the patients’ lives.

Traditional clinical trial designs, typically focusing on a single primary endpoint, are often ill-suited for this complex task. They frequently simplify the multidimensional reality of how patients, caregivers, and clinicians define meaningful treatment benefit into a single dimension. For instance, a therapy may slow disease progression but negatively impact quality of life; it may show modest improvement in the main endpoint yet substantially improve fine motor functions or reduce intolerable side effects. In rare diseases, where patient numbers are limited and the burden of participation is high, trials must do more than test hypotheses—they must produce data that reflects what matters most to those affected.

The Net Treatment Benefit (NTB) emerges as a patient-centric, statistically rigorous approach that allows for the prioritization and integration of multiple outcomes into a single, interpretable measure of treatment effects (2). When coupled with early engagement from patients, investigators, and key experts to define outcome hierarchies, NTB offers a practical path to trials that are both more efficient and more aligned with real-world needs.

The Challenge of Endpoint Selection in Rare Diseases

One of the most persistent bottlenecks in rare disease trial design is the selection of an appropriate primary endpoint. In common conditions, regulatory precedent and existing clinical guidelines typically point the way. In rare diseases, the path is often uncharted.

Consider Pompe disease or Duchenne muscular dystrophy. Patients, families, and clinicians may prioritize very different outcomes depending on the disease stage: respiratory function, ambulatory capacity, ability to feed independently, fatigue, or even cognitive symptoms in syndromic variants. Designing a trial around one of these clinical outcomes risks overlooking the others—and worse, dismissing a therapy that offers multidimensional benefit simply because it falls short on a single axis.

This issue becomes more acute when regulators require “hard” clinical outcomes, such as time to death or forced vital capacity, that may not be the most relevant for early- or mid-stage patients. Many rare diseases progress slowly or unpredictably, making it difficult to observe changes in a single outcome within the limited duration of a trial.

By forcing sponsors to choose one outcome as the sole measure of success, traditional designs risk misrepresenting the true value of an intervention. This not only complicates regulatory evaluation but can discourage further investment in promising therapies.

Why Net Treatment Benefit Is a Game-Changer

Net Treatment Benefit, grounded in the methodology of Generalized Pairwise Comparisons (GPC), offers a solution to these challenges. Rather than selecting a single endpoint, NTB enables trials to incorporate multiple outcomes—each assigned a position in a pre-defined hierarchy reflecting clinical and patient priorities.

In essence, NTB calculates the difference between the probability that a randomly selected patient in the treatment group does better across the prioritized outcomes than a randomly selected patient in the control group, and the reverse. This yields a single, interpretable statistic that reflects the totality of the evidence.

 The statistical advantages are compelling. By incorporating multiple relevant outcomes into the analysis simultaneously, NTB makes fuller use of the collected patient data, effectively capturing more comprehensive information about treatment effects. This is especially critical in rare disease trials, where small sample sizes are the norm. More efficient use of available data means improved power to detect clinically meaningful differences—potentially with fewer patients or shorter trial durations.

Specifically in the rare disease domain, a post-hoc analysis of the randomized, double-blind, phase 3 COMET trial, prioritizing the primary (forced vital capacity) and secondary outcome (6MWT), provided evidence of efficacy of avalglucosidase alfa therapy (n = 51) over alglucosidase alfa (n = 49) in Pompe disease, while the original analysis failed to significantly show superiority of treatment on the primary endpoint (3).

Prioritizing Outcomes with Stakeholder Input

What truly sets NTB apart is not just its statistical sophistication, but its ability to formalize clinical and patient preferences in the design phase of a trial.

In rare diseases, the need for such an approach is acute. Disease burden varies widely across individuals, and the diversity of symptom trajectories makes a one-size-fits-all endpoint inadequate. Engaging stakeholders early—patients, caregivers, site investigators, and treating clinicians—enables trial sponsors to co-create outcome hierarchies that reflect the lived experience of the disease.

 Structured preference elicitation methods, such as discrete choice experiments or ranking exercises, can yield clear insights into which outcomes matter most and in what order. However, these traditional approaches can be cumbersome, often requiring large numbers of respondents. Innovative methods are therefore needed to simplify the process and reduce the burden, especially in rare diseases with limited patient populations.

By building consensus around outcome prioritization upfront, sponsors not only create trials that are more meaningful—they reduce the risk of post-hoc disputes about relevance and increase the likelihood that trial data will resonate with regulators, payers, and clinicians.

Reducing the Burden on Patients and Families

Rare disease trial participants and their families often carry a disproportionate burden: frequent travel, complex assessments, and uncertainty around the value of their contribution. Any opportunity to streamline trials without compromising scientific integrity is not just a design consideration—it’s imperative.

NTB can reduce this burden in two important ways. First, by increasing statistical efficiency, NTB-based designs may require fewer patients to reliably detect whether a treatment is truly effective. Second, by allowing multiple outcomes to contribute to the primary analysis, NTB helps ensure that more of the collected data is meaningfully used, reducing waste and enhancing the value of each patient assessment.

Moreover, NTB allows the inclusion of clinically meaningful thresholds—minimum differences that matter to patients—in the analysis. This means that only differences considered meaningful are used to distinguish between outcomes, while smaller, less relevant differences are treated as neutral. This helps the analysis focus on what truly matters and adds another layer of patient-centricity, ensuring that the trial’s conclusions reflect not just differences, but meaningful ones.

Supporting Regulatory and HTA Pathways

 While the NTB has yet to become a standard primary analysis method in rare disease regulatory submissions, it is already well established and familiar to regulators in other therapeutic areas.

The ATTR-ACT trial for transthyretin amyloid cardiomyopathy used an NTB-like approach to prioritize time to death over time to hospitalization—highlighting how multidimensional benefit-risk profiles can be formalized in regulatory-grade evidence (4).  As regulatory agencies continue to emphasize patient-focused drug development (PFDD) (5), particularly for conditions where unmet need is high, there is a growing appetite for approaches that reflect the real-world complexity of treatment benefit.

Importantly, NTB is also well-suited for health technology assessments (HTAs). These bodies are increasingly requiring quantitative evidence of value beyond clinical efficacy—especially in Europe and Canada, where quality-adjusted life years (QALYs) and other composite measures are common. Because NTB summarizes multiple prioritized outcomes into a single interpretable measure, it aligns well with the demands of HTA dossiers and payer value frameworks.

In rare diseases, where treatments are often high-cost and subject to scrutiny, demonstrating comprehensive benefit-risks balance quantitatively is critical not only for approval but for access.

Fostering Adoption and Continuation of Development

An often-overlooked benefit of NTB in rare diseases is its potential to de-risk development decisions. When phase 2 trials are underpowered due to small sample sizes, NTB can detect more signal from limited data. Sponsors can make better-informed go/no-go decisions, reducing the likelihood of prematurely abandoning promising therapies or investing heavily in interventions with narrow appeal.

In turn, this supports better engagement with investors and partners. A clear, well-structured NTB analysis—grounded in patient and clinician priorities—can be a persuasive element in fundraising and partnership discussions. It also supports clinicians in understanding which patients are most likely to benefit, based on outcomes that mirror their own treatment goals.

Conclusion: Making Rare Disease Trials Work for Patients

For decades, rare disease trials have struggled under the weight of conventional clinical trial methodologies not designed for their constraints. The use of a single endpoint often obscures meaningful multidimensional benefits. It increases the likelihood of inconclusive results, slows development, and most importantly, can fail to serve the patients who volunteer their time, energy, and hopes.

Net Treatment Benefit, supported by robust stakeholder engagement in the selection and prioritization of outcomes, offers a viable, scalable, and scientifically rigorous solution. It allows for the integration of what matters most—survival, function, quality of life, and tolerability—into a single evaluative framework. And in doing so, it makes trials more efficient, more informative, and more aligned with real-world treatment decisions.

As the rare disease community continues to push for faster, more meaningful innovation, the integration of NTB into early trial design is not just a statistical refinement. It is a strategic imperative—one that places patients, not endpoints, at the center of progress.

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References:

• (1) Rare Diseases International – https://www.rarediseasesinternational.org/living-with-a-rare-disease
• (2) Buyse, M., Verbeeck, J., Saad, E.D., Backer, M.D., Deltuvaite-Thomas, V., & Molenberghs, G. (Eds.). (2025). Handbook of Generalized Pairwise Comparisons: Methods for Patient-Centric Analysis (1st ed.). Chapman and Hall/CRC https://doi.org/10.1201/9781003390855
• (3) Verbeeck, J., Dirani, M., Bauer, J. W., Hilgers, R. D., Molenberghs, G., & Nabbout, R. (2023). Composite endpoints, including patient reported outcomes, in rare diseases. Orphanet Journal of Rare Diseases, 18(1), 262.
• (4) Maurer, M. S., Schwartz, J. H., Gundapaneni, B., Elliott, P. M., Merlini, G., Waddington-Cruz, M., … & Rapezzi, C. (2018). Tafamidis treatment for patients with transthyretin amyloid cardiomyopathy. New England Journal of Medicine, 379(11), 1007-1016.
• FDA, Patient Focused Drug Development Series – https://www.fda.gov/drugs/development-approval-process-drugs/fda-patient-focused-drug-development-guidance-series-enhancing-incorporation-patients-voice-medical

Original content written by Tom Mann and published on Discover Pharma.

To mark Clinical Trials Day, Discover Pharma speaks with Tom Mann, clinical solutions engagement lead at One2Treat, about why patient voices must be central to protocol development, and how tools like Net Treatment Benefit are helping reshape modern trials.

What does Clinical Trials Day mean to your organisation, and how are you marking it this year?

Clinical Trials Day is a significant event for our organisation as it’s an opportunity to reaffirm our commitment to patient-centricity in medical research. This year, we’re placing a spotlight on incorporating patient perspectives from the earliest stages of trial planning. By engaging with patients and clinicians before protocol design, sponsors can create trials that align more closely with real-world experiences and outcomes. One2Treat’s approach focuses on including multiple patient-relevant outcomes in assessments to better reflect overall treatment effects.

How do you gather and incorporate patient insights into protocol design?

Recent regulatory guidance stresses the need to bring patient preferences into trial design from the outset. One of the best tools to do this is the Net Treatment Benefit (NTB), derived from the Generalized Pairwise Comparisons (GPC) statistical method. NTB captures the probability that a random patient on treatment will do better than one on control, based on a hierarchy of prioritized outcomes.

NTB is especially powerful because it allows tailoring of these outcome hierarchies based on different stakeholder views—patients, clinicians, caregivers. This gives advocacy groups and individuals a real voice in shaping endpoints.

We’ve also developed One2Treat Voice, a software tool that helps formalise this process. It guides users through comparative questions about patient profiles to identify which outcomes matter most and how they should be ranked.

What unmet need or therapeutic area do you think is ripe for a clinical trial breakthrough?

The biggest unmet need isn’t tied to a specific disease, but rather how trials are designed—particularly in areas where traditional primary endpoints don’t reflect patient experience. Think chronic pain, neurological conditions, and rare diseases. These require assessments that go beyond efficacy and include safety and quality of life.

Breakthroughs will come from tools that can holistically evaluate these dimensions, increase statistical power, and reduce sample sizes—making trials more efficient and meaningful.

What’s your biggest prediction for how clinical trials will change by 2030?

By 2030, the most impactful innovation will be the integration of patient voices into trial design. Tools that facilitate early engagement will become industry standards, improving relevance, accelerating timelines, and increasing trial success.

This patient-first mindset will define the next generation of clinical research and lead to treatments that are not only effective, but truly valued by those who use them.

If you could change one thing about the current trial ecosystem, what would it be?

We’d empower pharma companies with practical tools to engage patients and advocates much earlier in the process. When protocols are co-designed with both patients and clinicians, trials become more relevant and accessible—resulting in better recruitment, retention, and real-world impact.

One2Treat was born out of my frustration as a biostatistician with conventional approaches to clinical trial research. Over the years, I’ve witnessed the limitations of relying solely on a single primary criterion for evaluating new treatments. This narrow focus often overlooks valuable data and potential therapeutic benefits.

In many clinical trials, vast amounts of patient data are collected, yet the analysis tends to focus narrowly on one principal endpoint, with just a few secondary endpoints considered. This means that a significant portion of collected data does not influence regulatory decisions. Treatments that might have shown promise under a more comprehensive evaluation end up being disregarded.

One memorable example is the addition of oxaliplatin to 5-fluorouracil for metastatic colorectal cancer. Initially, the treatment failed to gain FDA approval when its primary endpoint, Overall Survival (OS), missed statistical significance. However, it exhibited significant benefits in progression-free survival. This discrepancy underscores the complexity of evaluating treatments solely on OS, especially when subsequent lines of therapy can influence survival outcomes. Oxaliplatin was ultimately approved a few years later and remains a standard of care today, reflecting its proven efficacy. Still, I often wondered how many patients could have benefited from this treatment within the few extra years it took to get approved.

Another case is the addition of erlotinib to gemcitabine for metastatic pancreatic cancer. This combination was approved based on reaching its primary endpoint, which demonstrated a mild yet statistically significant improvement in progression-free survival. However, this evaluation did not consider important factors such as toxicities and a decrease in quality of life, failing to capture the drug’s overall benefit-risk profile. Although erlotinib was approved, its use in this indication was extremely limited.

The need for a more inclusive and patient-focused trial design became even clearer when one of my relatives shared his challenging experiences participating in a clinical trial. This story sheds light on a widespread issue: participants frequently receive scant details about the trial’s purpose, the drug being tested, or the significance of their involvement, leaving them feeling overlooked. Such a mismatch between trial procedures and patient engagement highlights the urgent need for change. It emphasizes the necessity of a paradigm shift that would place patient insights and experiences at the heart of clinical research.

To bridge these gaps, I’ve dedicated myself to developing the Generalized Pairwise Comparisons (GPC) statistical method. This innovative approach enables the comprehensive analysis of treatment effects across multiple clinically relevant criteria, offering a fuller picture of a treatment’s potential benefits. One2Treat was founded to broaden the use of this methodology through the creation of software focused on comprehensive benefit-risk analysis. Our aim is to democratize access to advanced statistical analysis, making it accessible to a wide range of users irrespective of their programming or statistical expertise. By emphasizing simplicity and efficiency, One2Treat aims to make advanced statistical analysis a standard part of clinical research, empowering more informed treatment decisions.

One2Treat is dedicated to transforming clinical research by making trials more patient-centric and data-informed. By leveraging our software to consider a broader range of patient-relevant outcomes, we are not only improving the precision of clinical studies but also accelerating the path to market for promising treatments. As we move forward, One2Treat is committed to enhancing drug development processes, ensuring that every piece of patient data is valued, and every potential treatment is thoroughly assessed, incorporating all key patient’s needs. Join us in this mission to revolutionize clinical trials and improve patient care.

This blog was originally published by the Association of Clinical Research Professionals (ACRP).

Rare disease clinical trials face significant challenges. A study analyzing 199 discontinued rare disease trials found that insufficient patient accrual was the primary cause,¹ with up to 33% of trials failing due to this cause. With small patient populations, leveraging innovative statistical methodologies that can enhance statistical power is crucial. It enables the detection of treatment effects with a reduced sample size, making the study more feasible. Traditional clinical trials typically rely on a single primary endpoint, such as overall survival or disease progression. However, in rare diseases, multi-dimensional outcomes—including efficacy, safety, and quality of life—are often equally important. 

The Net Treatment Benefit (NTB), estimated from the Generalized Pairwise Comparisons (GPC) methodology, provides a promising solution by integrating multiple clinical outcomes into a single assessment, extracting more information from the data.² This innovative approach allows for more powerful, patient-focused analyses, thus enabling smaller, faster, and more cost-effective trials without sacrificing scientific rigor. 

The NTB is the difference between the probability that a random patient in the treatment group has a more favorable outcome than a random patient in the control group and the probability of the opposite occurring. By considering multiple endpoints within a single analysis, NTB provides a more comprehensive picture of a treatment’s overall benefit-risk profile. Unlike traditional methods, NTB enables prioritization of outcomes based on clinical importance and patient preferences, offering a more patient-focused approach to clinical trial analysis. 

Reducing Sample Size in Rare Disease Trials 

Since most clinical trials estimate treatment effects using a single outcome, they often require a large sample size to achieve statistical significance and demonstrate the treatment’s superiority. The NTB can improve statistical power by borrowing information from multiple outcomes, ranking them hierarchically, and allowing clinically meaningful thresholds to distinguish relevant differences. 

This is especially beneficial for rare diseases, where patient recruitment is challenging, and every patient is invaluable. A reduced sample size means trials can be conducted more quickly and efficiently, which minimizes costs and allows promising new therapies to reach patients sooner. In the context of rare diseases, where treatment options are often limited, any method that speeds up research while maintaining robust statistical evaluation is a major advancement. 

Specifically in the rare disease domain, a post-hoc analysis of the randomized, double-blind, Phase III COMET trial, prioritizing the primary (forced vital capacity) and secondary outcome (6MWT), provided evidence of efficacy of avalglucosidase alfa therapy (n = 51) over alglucosidase alfa (n = 49) in Pompe disease, while the original analysis failed to significantly show superiority of treatment on the primary endpoint.³

While no drug has been approved by regulatory bodies using the NTB for rare diseases, the methodology is widely used in other therapeutic areas and has been successfully included in regulatory submissions. Notably, it was used as the primary analysis in the Phase III ATTR-ACT trial, where the analysis prioritized time to death over time to hospitalization. Results demonstrated the efficacy of tafamidis (n = 264) over placebo (n = 177) and led to the drug approval for patients with transthyretin amyloid cardiomyopathy.⁴

Conclusion 

The Net Treatment Benefit represents a transformative step in clinical trial design, particularly for rare diseases where smaller sample sizes are more common due to the limited patient populations. By incorporating multiple outcomes into a single, more comprehensive estimation, the NTB enables more efficient, transparent, and patient-focused trials. Unlike traditional methodologies, which often rely on a single endpoint for regulatory approval, NTB provides a more holistic assessment of treatment effects. 

With growing regulatory support and clear advantages in reducing sample size, NTB has the potential to reshape the landscape of rare disease clinical trials, making them more feasible, cost-effective, and aligned with patient needs. As clinical research continues to evolve, adopting NTB-based approaches will be crucial in accelerating the development of new treatments and improving outcomes for patients with rare diseases. 

References 

1. Rees CA, Pica N, Monuteaux MC, Bourgeois FT. 2019. Noncompletion and nonpublication of trials studying rare diseases: a cross-sectional analysis. PLoS Medicine 16(11):e1002966.
2. Buyse M, Verbeeck J, Saad ED, Backer MD, Deltuvaite-Thomas V, Molenberghs G (Eds.). 2025. Handbook of Generalized Pairwise Comparisons: Methods for Patient-Centric Analysis (1st ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781003390855
3. Verbeeck J, Dirani M, Bauer JW, Hilgers RD, Molenberghs G, Nabbout R. 2023. Composite endpoints, including patient reported outcomes, in rare diseases. Orphanet Journal of Rare Diseases 18(1) :262.
4. Maurer MS, Schwartz JH, Gundapaneni B, Elliott PM, Merlini G, Waddington-Cruz M, … and Rapezzi C. 2018. Tafamidis treatment for patients with transthyretin amyloid cardiomyopathy. New England Journal of Medicine 379(11):1007–16.

Contributed by Tom Mann, Clinical Solutions Engagement Lead at One2Treat. Mann has more than 15 years of experience in technology start-ups and scale-ups in settings where he played a pivotal role in driving customer engagement, marketing initiatives, and strategic partnerships. At One2Treat, he helps develop solutions that integrate key patient-relevant outcomes into a single holistic treatment assessment, ensuring that the company’s approach remains both innovative and patient-focused. 

Original interview published in Outsourcing Pharma.

Could you give us an overview of your work? 

I have recently been promoted to Head of Solution Value at One2Treat, in this new role, I’m ensuring the development of our software solution and strategic services are fully aligned with our customer needs and company purpose.

The personal development and growth of each of the team members is also an important part of my role.

At One2Treat we develop methods and advanced software that enable a holistic evaluation of treatment effects by integrating all key patient-relevant outcomes into a single comprehensive assessment of the Net Treatment Benefit.

When did you realize you were interested in science- as a young child, teen or older? 

From a young age, I always had a thirst for understanding. For example, whenever a topic was discussed at school, I felt curious and would do my own research to learn more.

When growing up, I became more and more interested in math and chemistry.

I initially considered being a medical doctor or a pharmacist, as patient care was central to my aspirations. Ultimately, I decided to pursue mathematics, as it combined my analytical mindset with my interest in problem-solving. After earning my degree in mathematics, I further specialized with a master’s in statistics, where I discovered a passion for applying data to real-world challenges. This naturally led me to focus on biostatistics, a field that allowed me to merge my love for science with my goal of contributing to healthcare through data-driven insights.

Could you describe your personal journey bringing us to where you are now? 

At the end of high school, I joined university studying mathematics, with no clear idea at that moment about where it would lead me. I had classes with an inspiring professor who regularly used practical examples from his experience working in clinical trials at a pharma company.  

My future suddenly became clear… I wanted to work in clinical trials to fulfill my dreams as a child: “improving patients well-being by actively contributing to the development of better treatments”.

After graduating, I applied to a large pharma company (Bristol-Myers Squibb) where I worked as a biostatistician for 9 years. I continued my journey by moving to a CRO (IDDI), where I collaborated with different pharma companies, thus increasing my knowledge about different therapeutic areas and diseases. Within IDDI I had the opportunity to grow and transition to a Project Management role, allowing me to have a broader picture of drug development; not only statistics, but all the different steps (protocol and study design, randomization, data management, statistical analyses until full package submission).

In 2023, I took the opportunity to join One2Treat, an innovative technology start-up, focusing on software solutions that are driving advancements in patient-focused drug development.

My reasons for joining One2Treat were twofold. First, I was convinced by the methodology leveraging multiple dimensions in evaluating the treatment effect in randomized clinical trials. Secondly, I could be a key contributor in a young company with a blank page and an exciting focus.

What challenges did you face- as a woman or otherwise- along the way and what is the most valuable lesson you have learned? 

As a teenager, I was told by a teacher that I would never succeed in sciences. After failing a test, I sought clarification and was instead encouraged to change my goal. Perhaps it was because I was a girl—who knows? While this moment shook my self-confidence for years, it also became a turning point.

The most valuable lessons I’ve learned since then are to believe in yourself and your dreams, no matter the obstacles. If you trust in your abilities, you can achieve incredible things. And most importantly, never lose sight of your focus—it’s what guides you to success.

What ignites your passion in your current role? 

I am motivated by the tangible progress we’re making at One2Treat toward fully engaging patients in the drug development process. It’s inspiring to see the shift in the industry, where patients are becoming central to clinical trials. It is exciting that at One2Treat, we drive innovation by ensuring that clinical trials are increasingly patient-focused. Knowing that our efforts contribute to making treatments more accessible, relevant, and impactful for patients keeps me deeply committed to this work.

On a more personal level, I also find great satisfaction in tackling the challenge of balancing complex elements such as advanced software, effective people development, and high-quality services that bring value to our customers. Successfully integrating these components requires both strategic thinking and empathy. This dynamic aspect of my role constantly pushes me to grow and evolve, both professionally and personally.

What is your current work ethos/style? 

My current work ethos revolves around collaboration, adaptability, empathy, and strong analytical skills. I believe that fostering open communication and mutual respect within a team is key to aligning diverse perspectives and skills toward a shared goal, ensuring that everyone feels valued and heard. My background in mathematics and statistics equips me to approach challenges with a structured, problem-solving mindset, allowing me to find innovative and data-driven solutions.

Ultimately, my work style is defined by a balance of strategic focus, creative problem-solving, and a deep commitment to making a positive difference in everything I do.

Could you share some advice for young women starting to develop an interest in science or wanting to pursue a career like yours?

My advice for young women interested in science or pursuing a similar career is to embrace your curiosity and never be afraid to ask questions.

Believe in your abilities and trust that your perspective is valuable, even if you face doubts or challenges along the way… and you can be sure that you will! Science thrives on diverse viewpoints, and your own personal contributions will help shape the field in meaningful ways.