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Regulatory and health technology assessment advice on postlicensing and postlaunch evidence generation is a foundation for lifecycle data collection for medicines.

ABSTRACT: The understanding of the benefit risk profile, and relative effectiveness of a new medicinal product, are initially established in a circumscribed patient population through clinical trials. There may be uncertainties associated with the new medicinal product that cannot be, or do not need to be resolved before launch. Postlicensing or postlaunch evidence generation (PLEG) is a term for evidence generated after the licensure or launch of a medicinal product to address these remaining uncertainties. PLEG is thus part of the continuum of evidence development for a medicinal product, complementing earlier evidence, facilitating further elucidation of a product's benefit/risk profile, value proposition, and/or exploring broader aspects of disease management and provision of healthcare. PLEG plays a role in regulatory decision making, not only in the European Union but also in other jurisdictions including the USA and Japan. PLEG is also relevant for downstream decision-making by health technology assessment bodies and payers. PLEG comprises studies of different designs, based on data collected in observational or experimental settings. Experience to date in the European Union has indicated a need for improvements in PLEG. Improvements in design and research efficiency of PLEG could be addressed through more systematic pursuance of Scientific Advice on PLEG with single or multiple decision makers. To date, limited information has been available on the rationale, process or timing for seeking PLEG advice from regulators or health technology assessment bodies. This article sets out to address these issues and to encourage further uptake of PLEG advice.

SUBMITTER: Moseley J

PROVIDER: S-EPMC7256124 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Regulatory and health technology assessment advice on postlicensing and postlaunch evidence generation is a foundation for lifecycle data collection for medicines.

Moseley Jane J Vamvakas Spiros S Berntgen Michael M Cave Alison A Kurz Xavier X Arlett Peter P Acha Virginia V Bennett Simon S Cohet Catherine C Corriol-Rohou Solange S Du Four Emma E Lamoril Christelle C Langeneckert Anja A Koban Maren M Pasté Muriel M Sandler Susan S Van Baelen Karin K Cangini Agnese A García Sonia S Obach Mercè M Gimenez Garcia Emmanuel E Varela Lema Leonor L Jauhonen Hanna-Mari HM Rannanheimo Piia P Morrison Deborah D Van De Casteele Marc M Strömgren Anna A Viberg Anders A Makady Amr A Guilhaume Chantal C

British journal of clinical pharmacology 20200424 6

The understanding of the benefit risk profile, and relative effectiveness of a new medicinal product, are initially established in a circumscribed patient population through clinical trials. There may be uncertainties associated with the new medicinal product that cannot be, or do not need to be resolved before launch. Postlicensing or postlaunch evidence generation (PLEG) is a term for evidence generated after the licensure or launch of a medicinal product to address these remaining uncertainti ...[more]

PMID: 32162368

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Project description:Introduction: Although pharmaceutical companies, regulatory authorities, and health technology assessment (HTA) agencies have been increasingly using decision-making frameworks, it is not certain whether these enable better quality decision making. This could be addressed by formally evaluating the quality of decision-making process within those organizations. The aim of this literature review was to identify current techniques (tools, questionnaires, surveys, and studies) for measuring the quality of the decision-making process across the three stakeholders. Methods: Using MEDLINE, Web of Knowledge, and other Internet-based search engines, a literature review was performed to systematically identify techniques for assessing quality of decision making in medicines development, regulatory review, and HTA. A structured search was applied using key words and a secondary review was carried out. In addition, the measurement properties of each technique were assessed and compared. Ten Quality Decision-Making Practices (QDMPs) developed previously were then used as a framework for the evaluation of techniques identified in the review. Due to the variation in studies identified, meta-analysis was inappropriate. Results: This review identified 13 techniques, where 7 were developed specifically to assess decision making in medicines' development, regulatory review, or HTA; 2 examined corporate decision making, and 4 general decision making. Regarding how closely each technique conformed to the 10 QDMPs, the 13 techniques assessed a median of 6 QDMPs, with a mode of 3 QDMPs. Only 2 techniques evaluated all 10 QDMPs, namely the Organizational IQ and the Quality of Decision Making Orientation Scheme (QoDoS), of which only one technique, QoDoS could be applied to assess decision making of both individuals and organizations, and it possessed generalizability to capture issues relevant to companies as well as regulatory authorities. Conclusion: This review confirmed a general paucity of research in this area, particularly regarding the development and systematic application of techniques for evaluating quality decision making, with no consensus around a gold standard. This review has identified QoDoS as the most promising available technique for assessing decision making in the lifecycle of medicines and the next steps would be to further test its validity, sensitivity, and reliability.

Project description:EUPATI Belgium (EUPATI.be) is an informal gathering of local partners who are interested in improving patient involvement in healthcare innovation and medicines research and development. EUPATI.be brings together various stakeholders from different areas related to healthcare including patients, academia and industry. In doing so, we create an innovative collaborative approach where actors from different backgrounds work toward improving patient involvement in medical research, and putting the patient at the center of the Belgian healthcare system. Previously, we performed in-depth interviews with a small group of stakeholders on patient involvement. Here, we elaborate on our previous findings by using a nation-wide survey to inquire into Belgian stakeholders' perception on patient involvement. To this end, an electronic survey was available in French, Dutch and English, and accessible for 11 months. Twelve questions were asked, including 11 multiple choice questions and 1 open question. The latter was thematically analyzed according to the framework method. A total of 117 responses were registered and descriptive statistics were performed. The majority of respondents could be categorized into patient, academia and industry, whereas policy makers, payers, and healthcare professionals were underrepresented. We identified several barriers that hamper patient involvement, which were sometimes more reported by specific stakeholder groups. Next, we found that various stakeholders still consider patient involvement as a passive role, i.e., medical subject in a clinical trial. Respondents also reported that the role of the various stakeholders needed more clarification; this was also confirmed by the level of trust amongst the various stakeholders. Existing and the wish for more collaboration with the various stakeholders was reported by almost all respondents. Based on this survey, we can define the potential of involving patients in the medical research and development in the Belgian landscape. Our results will help to understand and tackle the various barriers that currently hamper patient involvement, whilst highlighting the need for a collaborative landscape from the multi-stakeholder perspective.

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Dataset Information

Regulatory and health technology assessment advice on postlicensing and postlaunch evidence generation is a foundation for lifecycle data collection for medicines.

Publications

Regulatory and health technology assessment advice on postlicensing and postlaunch evidence generation is a foundation for lifecycle data collection for medicines.

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