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Patient-Centred Clinical-Study Endpoints Derived Using Digital Health Technologies
Date de clôture : 23 avr. 2025  
- 284 jours

 Innovation
 Soins de santé
 Recherche
 Intelligence artificielle

ExpectedOutcome:

The action under this topic must contribute to all of the following outcomes:

  • organisations and institutions involved in the development of therapies for the treatment and management of chronic disease have access to a unifying framework and consensus-based recommendations for:
    • using a combination of patient preference information (PPI), clinical outcome assessments (COAs), and digital health technology (DHT)-derived measures to demonstrate the importance to patients of what is being measured by DHT-derived clinical-study endpoints;
    • determining, from the patient perspective, what constitutes a minimal clinically important difference (MCID) in a patient-centred, DHT-derived clinical-study endpoint.
  • new methods for analysing PPI and COA data collected using DHT and for combining data from PPI, COA, and DHT-derived measures are available to researchers;
  • a consistent framework for engagement regarding the development and use of patient-centred, DHT-derived clinical-study endpoints is available to industry and stakeholders;
  • acceptance of the use of PPI, COAs, and patient-centred DHT-derived measures in addition to or in combination with traditional clinical-study endpoints to provide a robust view of the benefits of a therapy to patients;
  • acceptance of the use of patient-centred DHT-derived measures for clinical-study endpoints as reliable evidence for the evaluation of the clinical and economic benefit of therapeutic medicinal products and medical technologies among stakeholders including, but not limited to, patient groups, regulatory bodies, and health technology assessment (HTA) bodies (including the EU Member State Coordination Group on HTA), indicated by a qualification opinion, endorsement, adoption or other approval by each relevant stakeholder group;
  • patient-centred, DHT-derived endpoints are implemented along with traditional clinical-study endpoints in clinical studies of therapies to treat chronic diseases, and data from DHT-derived clinical-study endpoints are used in regulatory and reimbursement decision-making.
Scope:

Three types of patient-centred information related to how a patient feels and functions contribute to the evaluation of outcomes of a therapy:

  • patient preference information (PPI);
  • clinical outcome assessments (COAs) (including patient-reported outcome (PRO) measures);
  • digital health technology-derived (DHT-derived) measures.

Each of these types of measures can be used to understand patient-centred benefits of therapies (i.e., meaningful improvements in how a patient feels or functions).

DHT-derived measures can capture patient-centred information about disease symptoms, physical, cognitive, and emotional functions, and experience with therapy. They can measure the status of a patient’s health in ways that may be related to, but often differ from, COAs. For example, DHTs may measure activity intensity but not specific activities. Likewise, DHT-derived measures may detect changes in patient-centred outcomes - such as function - earlier than a patient may notice such a change. For patient-centred DHT-derived measures (i.e., DHT-derived measures that capture how a patient feels and functions) to be useful as endpoints in clinical studies, they must not only be technically validated, but also demonstrate that they measure functions, activities, symptoms, and other impacts of disease and treatment that are important to patients and measure changes in these outcomes that are meaningful to patients.

PPI, COAs, and DHT-derived measures are different, but complementary, types of patient-centred data. Because these measures are complementary, using these measures in combination will provide a more robust view of the benefits of therapies measured using DHT-derived endpoints from the patient perspective. Combining these complementary measures is necessary to demonstrate the utility of using DHT-derived measures as clinical study endpoints that reflect the value of treatment benefits to patients. Specifically, using these measures in combination may contribute to determining what constitutes a minimal clinically important difference (MCID) in patient-centred DHT-derived endpoints from the patient perspective in clinical studies of therapies to treat chronic diseases. For the purpose of this project, a chronic disease is defined as a long-term health condition that may not have a cure.

However, despite recent increases in the use of PPI, COAs, and patient-centred DHT-derived measures, there is no unifying framework for understanding the relationships among these measures, nor how they can be used in combination to demonstrate meaningful, patient-centred benefits of therapies for chronic diseases in clinical studies.

Therefore, uncertainties exist regarding the utility of these measures either alone or in tandem, and the meaningfulness to patients of patient-centred DHT-derived measures when used as clinical study endpoints in the development of therapeutic products (including, but not limited to, pharmaceutical products, combination products, and therapeutic devices) for the treatment of chronic diseases.

The topic aims to develop a unified framework and consensus-based recommendations for using multiple types of patient-centred information to support the use of DHT-derived endpoints to demonstrate therapeutic benefit. This will ensure that therapies addressing patients’ needs are approved for use and reimbursed at levels that reflect the value of the therapies to patients.

To fulfil this aim, the action funded under this topic must:

1. Develop a framework for using PPI, COAs, and DHT-derived measures in combination for the development, acceptance and implementation of patient-centred DHT-derived clinical-study endpoints in clinical studies of potential treatments for chronic diseases.

The framework will be designed to ensure that PPI, COAs, and patient-centred DHT-derived measures used in combination will be accepted as reliable evidence to support the use of DHT-derived clinical study endpoints in the evaluation of the clinical and economic benefit of therapeutic drugs and technologies.

The framework must:

  • include recommendations for using the three types of patient-centred data in addition to or in combination with traditional clinical-study endpoints to provide evidence of the patient-centred benefits of therapeutic drugs and technologies;
  • describe the potential relationships among COAs, patient-centred DHT-derived endpoints and other common types of clinical study endpoints;
  • identify and address issues related to how and under which circumstances data from PPI and COAs can be used to determine what constitutes a MCID in a patient-centred DHT-derived clinical-study endpoint from the patient perspective;
  • identify and address issues related to whether and how data from PPI, COAs, and patient-centred DHT-derived measures can be pooled, including the need for new techniques (including, but not limited to, artificial intelligence, machine learning, and large language models) to jointly analyse pooled data from the different types of measures;
  • address issues related to diversity in patient populations (e.g., disease type, disease stage, health literacy, cultural factors, etc.) on the use and results of PPI, COAs, and DHT-derived measures and the ethical and equity implications of patient diversity on the interpretation and utility of patient-centred measures of therapeutic benefit.

2. Develop recommendations for:

  • using quantitative PPI to better understand COA data by demonstrating the relative importance of domains, items, and scores (and changes therein) within a COA instrument and relative to other commonly used endpoints (including endpoints included in relevant core outcomes sets) in clinical studies within the same therapeutic area;
  • understanding the relationships between COA data and patient-centred DHT-derived endpoints in diverse therapeutic areas;
  • using DHTs (e.g., apps, smart personal devices, smart drug-delivery devices, therapeutic medical technologies, etc.) to collect PPI and COA data;
  • using quantitative PPI, COAs, and patient-centred DHT-derived measures in combination to demonstrate the importance to patients of what is being measured by DHTs and determining what constitutes a MCID in a patient-centred, DHT-derived clinical-study endpoint.

3. Conduct at least four use cases to provide evidence to support the framework and recommendations.

Each use case should address one or more recommendations and all recommendations should be supported by one or more case studies. Applicants should specify the methodology to be applied in each use case and identify how each use case will inform the framework and recommendations. The set of use cases should:

  • include a range of digital measurement domains (e.g., physical activity, sleep, cognition, fatigue, or others) and address differences between passive and interactive DHTs;
  • include a range of patient ages (e.g., paediatric, adolescent, younger adults, and older adults);
  • address issues related to diversity in patient populations (e.g., disease type, disease stage, health literacy, cultural factors, underserved patient populations);
  • address issues related to combining and/or jointly analysing PPI, COA, and/or DHT-derived data using new techniques (including, but not limited to, artificial intelligence, machine learning, and large language models);
  • be conducted in partnership with academic medical centres and focus on all of the following areas:
    • paediatric radiation oncology;
    • lung cancer;
    • non-motor and motor symptoms in Parkinson’s disease;
    • obesity.

All use cases must be conducted in a way that is consistent with generally accepted international treatment guidelines in the relevant disease area.

The precise scope of the use cases will be developed by the full consortium during the preparation of the full proposal at the second stage. Case studies should not involve the de novo development of novel COAs, DHTs, or DHT-derived measures.

4. Include robust input from relevant stakeholders. Applicants are expected to specify how relevant stakeholders will be engaged and identify the type of stakeholder required and their expected role in the project. Accordingly, applicants are expected to:

  • engage patients, parents or carers of juvenile patients, and patient organisations as active partners in all aspects of the project to ensure that interaction between patients and research is active, meaningful, and collaborative across all stages of the research process. In this way, research decision making is guided by patients' contributions as partners, recognising their specific experiences, values, and expertise;
  • develop the framework and recommendations in consultation with stakeholders, including patient organisations, regulators, health technology assessment (HTA) bodies, and medical organisations to ensure consensus about what is required to demonstrate the patient-centred benefits of a therapy;
  • develop a regulatory strategy and interaction plan for evidence generation to support the regulatory qualification of the framework and recommendations and engage with regulators in a timely manner (e.g., national competent authorities, EMA Innovation Task Force, qualification advice).

5. Complement and coordinate with other initiatives including:

  • ongoing and completed European projects (and their successor organisations), and initiatives related to patient engagement and use of digital measurement technologies. Such projects may include, but are not limited to, IMI/IHI projects PRO-active, H2O, PREFER and the PREFER Expert Network, SISAQOL-IMI, IDEA-FAST, MOBILISE-D, IMPROVE, PaLaDin as well as EUnetHTA 21;
  • existing frameworks and guidance documents related to patient-focused drug development such as those from FDA and EMA;
  • existing frameworks and guidance documents related to the development and deployment of digital clinical measures such as those from the Digital Medicine Society.
Expected Impact:

The action under this topic is expected to achieve the following impacts:

  • greater benefit to patients from improved health care by ensuring that DHT-derived measures of how a patient feels and functions are accepted as patient-centred clinical-study endpoints;
  • patients having improved access to innovations that meet their needs through the development of new and improved evidence-based methodologies for a more comprehensive assessment of the added value of innovative therapeutic drugs and technologies;
  • better informed decision-making at all levels of the health care system (authorities, organisations) to facilitate cost-effective allocation of health resources, continuing innovation, and better health outcomes;
  • greater understanding of the relationship between multiple patient-centred measurements including PPI, COAs, and DHT-derived measures and how these measures, when considered together, can provide greater insight into the patient perspective;
  • reduced uncertainty regarding the PPI and COA data required to demonstrate the patient-relevance of DHT-derived clinical-study endpoints, and that needed to determine what constitutes a MCID in a patient-centred DHT-derived clinical-study endpoint for use in the development of pharmaceutical products, diagnostics, combination products, and therapeutic devices;
  • improved and more efficient engagement between industry and stakeholders in the evaluation of technologies developed using patient-centred DHT-derived endpoints in clinical studies;
  • increased speed and efficiency in the development and evaluation of innovative therapeutic technologies.


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