Therapeutic innovation & regulatory science最新文献

Post-approval changes (PACs) to marketed products are routinely introduced to continuously enhance the product lifecycle management. However, bringing a chemistry, manufacturing and control (CMC) change through the global health authorities can be a complex and lengthy process taking up to several years, therefore negatively impacting supply continuity. In order to accelerate the review and approval of regulatory submissions and ensure continuous supply to patients, the World Health Organization (WHO) is strongly supporting the implementation of reliance among National Regulatory Authorities (NRAs). While some promising developments have been made with the use of reliance pathways for initial marketing authorizations, reliance is still not widely used for PACs. With the support of the European Medicines Agency (EMA) and WHO, Roche launched a reliance pilot based on EMA approval to file a supply critical variation for a monoclonal antibody. The variation constitutes major changes to the approved manufacturing process. Sameness of the product is ensured by submitting to all participants the same variation package as in the EU. The objectives of the pilot are to ensure continuous supply of this critical medicine by targeting global approval in 6.5 months, to promote regulatory convergence by waiving country specific requirements, and enhance greater transparency by sharing EMA Committee for Medicinal Products for Human Use (CHMP) final assessment report and Q&As to participating NRAs. Globally 48 NRAs have agreed to join the pilot. This article outlines the process of establishing the pilot project, including a planning phase and an engagement phase with the EMA, WHO and the participating NRAs.

Background: Clinical trials have become larger and more complex. Thus, eSource should be used to enhance efficiency. This study aimed to evaluate the impact of the multisite implementation of eSource direct data capture (DDC), which we define as eCRFs for direct data entry in this study, on efficiency by analyzing data from a single investigator-initiated clinical trial in oncology.

Methods: Operational data associated with the targeted study conducted in Japan was used to analyze time from data occurrence to data entry and data finalization, and number of visits to the site and time spent at the site by clinical research associates (CRAs). Additionally, simulations were performed on the change in hours at the clinical sites during the implementation of eSource DDC.

Results: No difference in time from data occurrence to data entry was observed between the DDC and the transcribed data fields. However, the DDC fields could be finalized 4 days earlier than the non-DDC fields. Additionally, although no difference was observed in the number of visits for source data verification (SDV) by CRAs, a comparison among sites that introduced eSource DDC and those that did not showed that the time spent at the site for SDV was reduced. Furthermore, the simulation results indicated that even a small amount of data to be collected or a small percentage of DDC-capable items may lead to greater efficiency when the number of subjects per site is significant.

Conclusions: The implementation of eSource DDC may enhance efficiency depending on the study framework and type and number of items to be collected.

Introduction: Qualification of medical product evaluation tools is underway in the United States, Europe, and Japan to reflect the advancements in the basic science of medical products. In Europe and the U.S., Guidance of Guidances (GoG) policies that clarify regulators'processes, tasks, and methods of sponsor involvement are adopted to issue tool guidance. However, in Japan, a non-GoG type policy focusing on supporting the research and development for tools without defining a tool guidance-making process has been adopted.

Methods: In this study, an analytical framework for the lifecycle of development tools was constructed, including pre- and post-tool qualification processes, to compare the two above-mentioned approaches. For this study, Japanese cases were selected as experimental cases, whereas Western cases served as controls. The progress of tool qualification and composition of deliverables were analyzed.

Results and conclusions: It was indicated that in the GoG type policy, in which processes are defined, and involvement methods are clarified, tool qualification can progress more smoothly than in a non-GoG type policy. This policy indicates that deliverables may have a consistent composition. Contrastingly, GoG-type policies alone present challenges in connecting upstream tools for R&D support.

Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials.

Background: The drug development industry's focus on cancer-related treatments continues to rise, with narrow patient populations and complex procedures increasing the complexity of oncology protocols at an accelerated rate compared to non-oncology drugs. Tufts Center for the Study of Drug Development utilized data from a study investigating the impact of protocol amendments to compare how oncology clinical trials differ from non-oncology and identify opportunities to optimize performance in oncology clinical trials.

Methods: Sixteen drug development industry companies contributed data from 950 protocols and 2,188 amendments to a study conducted in 2022 investigating protocol amendments. Analysis compared differences in amendment impact and causes between 249 oncology and 701 non-oncology protocols.

Results: Compared to non-oncology, oncology protocols had a significantly higher prevalence (72.1% and 91.1%, respectively) and number (3.0 and 4.0, respectively) of protocol amendments. Oncology protocols with amendments had significantly lower participant completion rates compared to oncology protocols without amendments, while no significant differences were found among non-oncology. During the COVID-19 pandemic, the study found an increased number of substantial amendments, lower completion rates, and higher dropout rates among oncology protocols compared to before the pandemic.

Conclusions: Efforts to prevent avoidable protocol amendments in the industry have not been effective in oncology, where increasingly complex designs are reflected in difficult to predict cycle times, barriers to recruitment and retention and an increase in protocol amendments.

Background: Appropriate exploratory efficacy data from Phase I trials are vital for subsequent phases. Owing to the uniqueness of brain tumors (BTs), use of different strategies to evaluate efficacy is warranted. We studied exploratory efficacy evaluation in Phase I trials involving BTs.

Methods: Using Clarivate's Cortellis^™, 42 Phase I trials of BT interventions conducted from 2020 to 2022 were analyzed for efficacy endpoints, which were set as primary endpoints (PEs) or secondary endpoints (SEs). Additionally, these metrics were compared in two subgroups: trials including only BTs (Group-A) and those including BTs among mixed solid tumors (Group-B).

Results: Selected studies included a median of 1.5 PEs (range, 1-6) and 5 SEs (range, 0-19). Efficacy endpoints were included as PEs and SEs in 2 (5%) and 31 (78%) trials, respectively. Among the latter 31 trials that included 94 efficacy endpoints, 24, 22, 20, 9, and 8 reflected overall response rate (ORR), progression-free survival (PFS), overall survival (OS), duration of response (DOR), and disease control rate (DCR), respectively. ORR for BT was determined using various methods; however, the Response Evaluation Criteria in Solid Tumors (RECIST) was used less frequently in Group-A than in Group-B (p = 0.0039).

Conclusions: Recent Phase I trials included efficacy endpoints as SEs, with ORR, PFS, or OS included in ~ 50% trials and DOR or DCR in ~ 25%. No established criteria exist for imaging evaluation of BTs. Phase I trials involving mixed solid tumor cohorts revealed challenges in designing methods to assess the exploratory efficacy of BTs.

In June 2021, FDA released a Draft Guidance on Sponsor Responsibilities for IND Safety Reporting and cited components of a recommended Safety Surveillance Plan (SSP). To meet the expectations of the 2021 FDA guidance, sponsors should document their plan for aggregate safety assessment. The Drug Information Association-American Statistical Association Interdisciplinary Safety Evaluation scientific working group has proposed an Aggregate Safety Assessment Plan (ASAP) that addresses this recommendation. The 2021 FDA guidance also discusses potential strategies for unblinded review of safety data from ongoing studies by an independent Assessment Entity, which could occur via planned periodic evaluations or "triggered" reviews based on blinded data assessments. The Assessment Entity reviewing unblinded data makes recommendations as to whether the threshold has been met for submission of an aggregate IND safety report. In this paper, we discuss how the ASAP supports IND aggregate safety reporting decisions, including elements to be included in a proposed SSP appendix to the ASAP. In addition, the authors advocate for the benefits of developing a charter (or specific section of the Data Monitoring Committee charter, if applicable) that describes the responsibilities and conduct of the Assessment Entity. With these components in place, study sponsors will meet the objective of having clearly defined processes for the monitoring of clinical trial safety data in aggregate and making IND safety reporting decisions.

Introduction: Pharmaceutical regulation on a global scale is a complex process, with regulatory bodies overseeing various aspects, including licensing, registration, manufacturing, marketing, and labeling. Among these, the USFDA plays a crucial role in upholding public health. The pharmaceutical industry contributes significantly to well-being by developing and distributing therapeutic agents. The journey of evaluating new pharmaceuticals involves meticulous examination through several phases, from safety and efficacy assessments to toxicity evaluation. Drug approval involves submitting New Drug Applications (NDAs) to regulatory agencies like the USFDA and EMA. However, disparities in durations contribute to the phenomenon known as "drug lag." This lag refers to delays in a pharmaceutical product's availability in one market compared to another. Addressing this issue is crucial, given its impact on patient access to treatments.

Method: This study aims to analyze the extent of drug lag, focusing on newly approved oncology targeted therapies in Saudi Arabia, the United States, and the European Union. Data for cancer treatments authorized by the USFDA, EMA, and SFDA from January 1, 1997, to December 31, 2022, were collected from regulatory agency websites. The data sources included authorization letters, prescription information, and evaluation documents. We conducted a comparative assessment of drug lag for approved oncology targeted therapies between Saudi Arabia, the US, and the EU.

Result: Our analysis identified 135 newly approved oncology-targeted drugs within the specified timeframe. Of these, 71 received approval in all three regions, while disparities were evident in others. The USFDA consistently had the highest number of approved drugs, with 98.5% of drugs initially approved there. In contrast, Saudi Arabia had the lowest number of approved drugs and a significantly longer median drug lag, indicating substantial delays in drug availability.

Conclusion: This study highlights the significance of mitigating drug lag to enhance global healthcare outcomes and patient access to innovative therapies. Further research and collaborative efforts are essential to bridging these disparities and promoting equitable healthcare worldwide.

Contamination of drug products and substances containing impurities is a significant concern in the pharmaceutical industry because it may impact the quality and safety of medicinal products. Special attention is required when mutagenic impurities are present in pharmaceuticals, as they may pose a risk of carcinogenicity to humans. Therefore, controlling potential mutagenic impurities in active pharmaceutical ingredients to an acceptable safety limit is mandatory to ensure patient safety. As per the International Council for Harmonization (ICH) M7 (R2)³ Guideline, mutagenic impurities are those compounds or materials that induce point mutations. In 2018, the sartan class of drugs was recalled due to the presence of N-nitrosamine impurities, which are potential mutagens. In addition to the primary impurities being detected, this class of products, especially losartan, irbesartan and valsartan, have been identified as having organic azido contaminants, which are again highly reactive toward DNA, leading to an increased risk of cancer. These azido impurities form during the preparation of the tetrazole moiety via the reaction of a nitrile intermediate with sodium azide. Given that this is a newly raised issue in the pharmaceutical world, it should be noteworthy to review the related literature. Thus, this review article critically accounts for (i) the toxicity of azido impurities and the proposed mechanism of mutagenicity, (ii) the regulatory perspective, and (iii) the sources and control strategies used during the preparation of drug substances and (iv) future perspectives.

Background: Diabetes, a chronic disease worldwide, may be associated with a poorer prognosis in patients with coronavirus disease 2019 (COVID-19). While some antihyperglycemic medications may be beneficial, others may increase the risk of adverse clinical outcomes of COVID-19. We aimed to analyze the effect of antihyperglycemic medications on COVID-19.

Methods: We searched the Web of Science, Cochrane Library, EMBASE, PubMed, and Scopus databases from December 2019 to June 2022 to identify literature related to patients with COVID-19 and type 2 diabetes mellitus (T2DM) treated with antihyperglycemic medications.

Results: 56 studies were included in the analysis. Metformin (OR 0.66; 95% CI 0.58-0.74; p < 0.05), Glucagon-like peptide-1 receptor agonist (GLP-1ra) (OR 0.73; 95% CI 0.59-0.91; p < 0.05), and sodium-dependent glucose transporters 2 inhibitor (SGLT 2i) (OR 0.77; 95% CI 0.69-0.87; p < 0.05) were associated with lower mortality risk, while insulin was associated with increased mortality risk (OR 1.40; 95% CI 1.26-1.55; p < 0.05). Meanwhile, metformin (OR 0.65; 95% CI 0.50-0.85; p < 0.05) and GLP-1ra (OR 0.84; 95% CI 0.76-0.94; p < 0.05) were significantly associated with decreased severe manifestation risk. What's more, metformin (OR 0.77; 95% CI 0.62-0.96; p < 0.05), GLP-1ra (OR 0.86; 95% CI 0.81-0.92; p < 0.05), and SGLT 2i (OR 0.87; 95% CI 0.79-0.97; p < 0.05) were also associated with a decreased risk of hospitalization, but insulin were associated with an increased risk of hospitalization (OR 1.31; 95% CI 1.12-1.52; p < 0.05). Nevertheless, the results of the subgroup analyses showed that the effects of different glucose-lowering agents on COVID-19 may be related to in-hospital use or out-hospital use, elderly or non-elderly patients use, and different geography.

Conclusion: Metformin, GLP-1ra, and SGLT 2i have shown a positive effect on clinical outcomes in COVID-19, particularly in non-elderly individuals. However, insulin use may pose a higher risk, especially in elderly patients, so need with caution. Meanwhile, DPP-4i, TZD, α-GLUi, and sulfonylureas appeared to have a neutral effect. These results need to be validated in future clinical studies.