Pharmaceutical Medicine最新文献

With a large number of one-time administration cell and gene therapies expected to come to the market in the coming years, there is a renewed need to understand the existing and future challenges that such modalities bring about, especially as it relates to their assessment of value, pricing and access. Payer, health technology assessment (HTA) bodies and manufacturers alike are faced with a number of unprecedented challenges stemming from the fact that such therapies are 'one-time' and/or have curative intent, but often lack sufficient evidence to support such claims at the time of launch (i.e., during pricing and access negotiations). There are a number of different approaches to assessing economic value for cell and gene therapies across regions (e.g., US vs Europe), which ultimately lead to further disconnect in pricing and reimbursement outcomes across countries; yet, in many cases, affordability concerns relating to high upfront costs are raised by providers. To that end, cell and gene therapies have been frequently criticized by payers for their 'high sticker price' based on relatively limited evidence to support durability claims. New contracting solutions are increasingly being employed to overcome concerns specifically relating to the durability of clinical benefit, the comparative effectiveness of a therapy and affordability (i.e., the one-time high cost of therapy). Indeed, recent launches of cell and gene therapies have often leveraged outcome-based agreements, instalments, coverage with evidence generation, subscription models, stop-loss and payer reinsurance, etc. to mitigate concerns from payers and providers and drive access. In this paper, we aim to review challenges for cell and gene therapies from a pricing and access perspective and explore the growing role of innovative contracting solutions to overcome aforementioned challenges.

The randomised controlled trial (RCT) has been considered for a long time as the gold standard for evidence generation to support regulatory decision making for medicines. The randomisation procedure involves an ethical dilemma since it means leaving the treatment choice to chance. Although currently contested, the ethical justification for the RCT that has gained widespread acceptance is the notion of 'clinical equipoise'. This state exists when "there is no consensus within the expert clinical community about the comparative merits of the alternatives to be tested"; it is argued that this confers the ethical grounds for the conduct of an RCT. The prominent position of the RCT is being challenged by new therapeutic modalities for which this study design may be unsuitable. Moreover, alternative approaches to evidence generation represent another area where innovation may have implications for the relevance of the RCT. Against the backdrop of the debate around the equipoise principle and some recent therapeutic and data analytical innovations, the aim of this article is to explore the current standing of the RCT from a regulatory perspective.

Life science research and development (R&D) companies are all too aware of the importance of patient perspectives but also of the barriers to engaging directly with patients, not least compliance, complex technical and regulatory issues, and the need to meet multifaceted expectations. Medical research charities (MRCs), highly technical and professional organisations, work directly with patients; they represent an expert resource for the science of their field, for disease-related patient advocacy issues and to advise and assist R&D companies in devising meaningful trials. The Pistoia Alliance, a non-profit organisation facilitating life sciences R&D, gathered a number of UK MRCs focused on complex lifelong conditions. The group used workshops and an opinion questionnaire for a snapshot of how the charities believe their knowledge and patient experiences could contribute insights and efficiencies to commercial R&D. MRCs argued that for chronic conditions, the patient perspective is vital in facilitating and de-risking trials, promoting patient motivation, compliance and study viability. MRCs and the patients they represent want to see successful trials, and it is in everyone's interest that well considered studies can proceed. Today, with remote assessments, consumer wearables and digital health technologies, MRCs and patients are already collating substantial data sets that are relevant to quality-of-life benefits, regulatory and value assessments, all of great interest to biopharmaceutical companies. In turn, MRCs would benefit from the experience of biopharma in generating clinical data and implementing novel technologies.

Introduction: Artificial intelligence through machine learning uses algorithms and prior learnings to make predictions. Recently, there has been interest to include more artificial intelligence in pharmacovigilance of products already in the market and pharmaceuticals in development.

Objective: The aim of this study was to identify and describe the uses of artificial intelligence in pharmacovigilance through a systematic literature review.

Methods: Embase and MEDLINE database searches were conducted for articles published from January 1, 2015 to July 9, 2021 using search terms such as 'pharmacovigilance,' 'patient safety,' 'artificial intelligence,' and 'machine learning' in the title or abstract. Scientific articles that contained information on the use of artificial intelligence in all modalities of patient safety or pharmacovigilance were reviewed and synthesized using a pre-specified data extraction template. Articles with incomplete information and letters to editor, notes, and commentaries were excluded.

Results: Sixty-six articles were identified for evaluation. Most relevant articles on artificial intelligence focused on machine learning, and it was used in patient safety in the identification of adverse drug events (ADEs) and adverse drug reactions (ADRs) (57.6%), processing safety reports (21.2%), extraction of drug-drug interactions (7.6%), identification of populations at high risk for drug toxicity or guidance for personalized care (7.6%), prediction of side effects (3.0%), simulation of clinical trials (1.5%), and integration of prediction uncertainties into diagnostic classifiers to increase patient safety (1.5%). Artificial intelligence has been used to identify safety signals through automated processes and training with machine learning models; however, the findings may not be generalizable given that there were different types of data included in each source.

Conclusion: Artificial intelligence allows for the processing and analysis of large amounts of data and can be applied to various disease states. The automation and machine learning models can optimize pharmacovigilance processes and provide a more efficient way to analyze information relevant to safety, although more research is needed to identify if this optimization has an impact on the quality of safety analyses. It is expected that its use will increase in the near future, particularly with its role in the prediction of side effects and ADRs.

Background: The Gulf Centralised Committee for Drug Registration (GCC-DR), as part of the Gulf Health Council (GHC), enables the consolidated registration of pharmaceutical products throughout the member states of the Gulf Cooperation Council.

Objectives: The objectives of this study were to provide an update of the performance of the GCC-DR centralised procedure; evaluate the review times for new products submitted to the GCC Centralised Registration between January 2015 and December 2020; assess the impact of applying facilitated regulatory pathways and implementing a reliance strategy; identify the strengths and weaknesses of the centralised review process; and propose strategies that could enhance the GCC regulatory review process leading to improved access to medicines for patients.

Methods: A standardised data collection template enabled the structured documentation of information collected by the Senior Regulatory Affairs and Regulatory Affairs Specialists from the Executive Board of the Health Ministers Council for GCC States to determine the GHC structure, resources, review models and milestones and timelines. The total number of applications approved was provided together with the average yearly timelines for new active substances and generics from January 2015 to December 2020 including both scientific assessment time from the agency as well as applicant response time to questions raised. Actual approval times for each product were calculated from the date of submission to the date of approval.

Results: The fewest (58) new products were approved in 2019 and the most (200) in 2020. The average review times for new medicines were the longest (838 calendar days) in 2015 and the shortest (321 calendar days) in 2019. Important changes recently implemented include an increase in the number of GCC-DR meetings, adoption of a standardised electronic common technical document and GCC regulatory review template, removal of authorisation dependence on pricing agreements and introduction of a reliance strategy. Additional recommendations include Executive Committee mandates for dossier review, target times for dossier validation, scientific review and Expert Committee recommendation and training for quality decision making.

Conclusions: GCC procedures and decision-making processes have been positively influenced by a variety of expert reviewers, unified guidelines and the implementation of a reliance strategy. Certain barriers must still be overcome to enhance the quality of the review, and to shorten regulatory review times without compromising the scientific robustness of the review.

Background: Comparator selection is an important consideration in the design of observational research studies that evaluate potential associations between drug therapies and adverse event risks. It can affect the validity of observational study results, and potentially impact data interpretation, regulatory decision making, and patient medication access.

Objective: The aim of this study was to assess the impact of comparator selection bias using two real-world case studies evaluating an increased rate of acute myocardial infarction (AMI).

Methods: Data from the Truven Health Analytics MarketScan^® electronic medical claims database were used to conduct two retrospective observational cohort studies, utilizing a cohort new-user design, comparing AMI risk between testosterone replacement therapy (TRT) and phosphodiesterase-5 inhibitors (PDE5is) in men treated for hypogonadism, and triptans versus other prescribed acute treatments for migraine in adults. All patients were enrolled continuously in a health plan (no enrollment gap > 31 consecutive days) for ≥ 1 year before index. Baseline period was defined as 365 days prior to index. Exposure was defined by prescription and outcome of interest was defined as occurrence of AMI. Using Cox proportional hazard models, primary analysis for the TRT cohort compared AMI risk between propensity score (PS)-matched TRT-treated and untreated patients; secondary analysis evaluated risk between PS-matched TRT-treated and PDE5i-treated patients. For the triptan cohort, primary analysis compared AMI/ischemic stroke risk between PS-matched triptan-treated and opiate-treated patients; secondary analysis evaluated risk between PS-matched triptan-treated and nonsteroidal anti-inflammatory drug (NSAID)-treated patients and PS-matched non-prescription-treated migraine patients and general patients.

Results: No significant association between TRT and AMI was observed among TRT-treated (N = 198,528, mean age 52.4 ± 11.4 years) versus PDE5i-treated men (N = 198,528, mean age 52.3 ± 11.5 years) overall (adjusted hazard ratio [aHR] 1.01; 95% CI 0.95-1.07; p = 0.80). Among patients with prior cardiovascular disease (CVD), risk of AMI was significantly increased for TRT-treated versus PDE5i-treated patients (aHR 1.13; 95% CI 1.03-1.25). The triptan study included three comparisons (triptans [N = 436,642] vs prescription NSAIDs [N = 334,152], opiates [N = 55,234], and untreated migraine [N = 1,168,212]), and a positive control (untreated vs general non-migraine patients [N = 11,735,009]). Analyses of MI risk in migraine patients prescribed triptans versus NSAIDs/opiates had mixed results: the point estimate ranged from 0.33 to 0.84 depending on chosen study window.

Conclusions: Cardiovascular outcomes were not worse in hypogonadism patients with TRT versus PDE5i; however, a potential association with AMI was

Causality assessment of safety signals observed with medicinal products is a foundational element of pharmacovigilance and regulatory practice, typically performed by a global introspection process. We have developed a novel, structured methodological framework to support the global introspection process for safety signal causality assessment. This Signal Assessment Guide (SAGe) tool was developed by AstraZeneca and is used internally, both to assess safety signal strength and to inform causality decisions related to safety signals. The term 'safety signal' refers to information arising from one or multiple sources, which suggests a new potentially causal association, or a new aspect of a known association, between an intervention and an adverse event. The key concept underlying the SAGe tool is that safety signal data can be reliably sorted into one of three categories: aggregate safety data, plausibility data, and case-level data. When applying the tool, an evidence grade score (Levels A, B, C, and D) is transparently assigned to the available data in each category. This information can then be summarised and presented for formal decision making regarding causality for safety signals. By using a transparent method to categorise the grade of evidence for causal association, with an option to additionally derive a quantitative strength of safety signal score, the SAGe tool can support the global introspection process for causality decisions, contributing to the quality of safety information for medicinal products provided to healthcare professionals and patients. Our anecdotal experience of using the SAGe tool at AstraZeneca is that it has resulted in more efficient and robust conversations regarding the strength of safety signals and the causality question. Wider use of the SAGe tool may bring increased levels of transparency and consistency to the evaluation of safety signals.

In the last decade there has been a significant increase in the literature discussing the use of benefit-risk methods in medical product (including devices) development. Government agencies, medical product industry groups, academia, and collaborative consortia have extensively discussed the advantages of structured benefit-risk assessments. However, the abundance of information has not resulted in a consistent way to utilize these findings in medical product development. Guidelines and papers on methods, even though well structured, have not led to a firm consensus on a clear and consistent approach. This paper summarizes the global landscape of benefit-risk considerations for product- or program-level decisions from available literature and regulatory guidance, providing the perspectives of three stakeholder groups-regulators, collaborative groups and consortia, and patients. The paper identifies key themes, potential impact on benefit-risk assessments, and significant future trends.

Background: Legislative requirements for Marketing Authorisation Holders (MAHs) to maintain a Pharmacovigilance System Master File (PSMF) were introduced in the European Union (EU) in 2010, operationalised in 2012 and subsequently introduced in other territories. There are no internationally agreed standards for the PSMF and country/regional requirements vary, leaving room for interpretation. This creates complexities for MAHs in implementing and maintaining multiple PSMFs.

Objectives: The approaches taken towards the creation and maintenance of PSMFs in a global environment were investigated using a survey in order to gain a better understanding of the impact of the PSMF for MAHs.

Methods: A structured benchmarking survey was conducted during September and October of 2019 and the responses were analysed. A questionnaire with open-ended questions was designed to elicit detailed information on PSMF management and provide insights into company experiences. Companies affiliated to the EU Federation of Pharmaceutical Industries and Associations (EFPIA) and industry stakeholders with experience of PSMFs were contacted ensuring a broad representation including small, medium and large pharmaceutical companies, contract organisations/consultants and research-driven and generic organisations.

Results: Thirty companies responded; of these, 29 provided information relating to their PSMF practices. Respondents acknowledged that the PSMF is a valuable document that has helped to create greater awareness of pharmacovigilance within companies. Complex and varying international requirements were recognised as burdensome, especially in the context of consistent development and maintenance of multiple PSMFs. The respondents indicated that companies use the EU PSMF to manage requirements in other territories. Similar areas for standardisation were identified across respondents.

Conclusion: The survey results highlight both the value of the PSMF and the challenges in maintaining it. Building on these responses, the paper offers pragmatic solutions to the challenges faced by MAHs and proposes a continued dialogue with key stakeholders in industry and national regulatory authorities about PSMF globalisation, harmonisation and simplification of requirements.