Therapeutic innovation & regulatory science最新文献

Background

Single-arm clinical trials (SAT) are common in drug and biologic submissions for rare or life-threatening conditions, especially when no therapeutic options exist. External control arms (ECAs) improve interpretation of SATs but pose methodological and regulatory challenges.

Objective

Through narrative reviews and expert input, we developed a framework for considerations that might influence regulatory use and likelihood of regulatory acceptance of an SAT, identifying non-oncology first indication approvals as an area of interest. We systematically analyzed FDA and EMA approvals using SATs as pivotal evidence. The framework guided outcome abstraction on regulatory responses.

Methods

We examined all non-oncology FDA and EMA drug and biologic approvals for first indications from 2019 to 2022 to identify those with SAT as pivotal safety or efficacy evidence. We abstracted outcomes, key study design features, regulator responses to SAT and (where applicable) ECA design, and product label content.

Results

Among 20 SAT-based FDA approvals and 17 SAT-based EMA approvals, most common indications were progressive rare diseases with high unmet need/limited therapeutic options and a natural history without spontaneous improvement. Of the types of comparators, most were natural history cohorts (45% FDA; 47% EMA) and baseline controls (40% FDA; 47% EMA). Common critiques were of non-contemporaneous ECAs, subjective endpoints, and baseline covariate imbalance between arms.

Conclusion

Based on recent FDA and EMA approvals, the likelihood of regulatory success for SATs with ECAs depends on many design, analytic, and data quality considerations. Our framework is useful in early drug development when considering SAT strategies for evidence generation.

As cancer has become better understood on the molecular level with the evolution of gene sequencing techniques, considerations for individualized therapy using predictive biomarkers (those associated with a treatment’s effect) have shifted to a new level. In the last decade or so, randomized “adaptive enrichment” clinical trials have become increasingly utilized to strike a balance between enrolling all patients with a given tumor type, versus enrolling only a subpopulation whose tumors are defined by a potential predictive biomarker related to the mechanism of action of the experimental therapy. In this review article, we review recent innovative design extensions and adaptations to adaptive enrichment designs proposed during the last few years in the clinical trial methodology literature, both from Bayesian and frequentist perspectives.

Despite regulatory changes designed to stimulate investment in therapies for rare diseases, many of these conditions lack government-approved treatments. Advanced regenerative medicines, which are therapies and clinical interventions aimed at healing or replacing damaged or defective human cells, tissues, and organs, offer great promise for addressing many rare diseases. A major challenge facing advanced regenerative medicines for rare diseases is securing financial support to assist in bringing a therapy to market. This paper describes the factors cited by pharmaceutical industry players globally for sponsoring the development of advanced regenerative medicines for rare diseases. The paper examines the motivations of 53 sponsors that meet the latter criteria. The motivations behind investments were broadly similar amongst sponsors and map closely onto regulatory requirements for clinical development and marketing authorization of advanced therapeutic products, including the presence of accelerated or attenuated pathways for regulatory approval, use for indications with high unmet medical needs, and/or that have advantages over existing therapies, and robust preclinical data. Other factors include availability of investment incentives and opportunities for off-label use in the post-approval stages.

Purpose: Postoperative adhesions can be prevented by the use of bioabsorbable anti-adhesion barriers. Although the occurrence of postoperative bowel obstruction is an important concern for patients, at the time of approval of anti-adhesion barriers, its effectiveness in preventing postoperative bowel obstruction had not been evaluated. We aimed to retrospectively evaluate the incidence of bowel obstruction after colectomy in patients with colon cancer using an insurance claims database.

Methods: This retrospective cohort study analyzed the data of colon cancer patients (between 2005 and 2017 from a national insurance claims database) who underwent colectomies to compare the proportion of individuals with postoperative bowel obstruction between the barrier and no barrier groups.

Results: Of the 587 patients who met the inclusion criteria, 308 and 279 patients were identified as the barrier and no barrier groups, respectively. The incidence of postoperative bowel obstruction was significantly lower in the barrier group (log-rank test, P = 0.0483). The cumulative incidence of postoperative bowel obstruction 37 months after the initial colectomy was 6.1% and 10.9% in the barrier and no barrier groups, respectively. Moreover, consistent results were obtained in the matched cohort.

Conclusion: In colectomies for patients with colon cancer, the use of anti-adhesion barriers could significantly reduce the incidence of postoperative bowel obstruction. Evaluations using insurance claims databases could provide important information on outcomes following implementation of medical devices.

Technology enabling drug serialisation technology was introduced by regulators to enhance security in pharmaceutical supply chain and protect drugs from infiltration by falsified and substandard medicines. The introduction of systems for serialisation required huge financial outlays manufacturers of pharmaceuticals. This study investigated the impact of serialisation on the operational efficiency and productivity in Irish pharmaceutical sites. A qualitative study was conducted with 11 manufacturing sites in Ireland. The participating companies operated a total of 114 pack-lines, representing approximately 65% of the automated packing lines in the country. The study found that serialisation had a negative effect on packaging production line OEE and line availability and on the individuals cost per unit of packaged pharmaceuticals. The research results estimated that the capital costs of serialisation were four times greater than those estimated by the regulators. There was a 4.1 cents average cost per pack for serialisation with high volume sites reporting an annual cost of serialisation of up to €4.5 m per annum and a 2.7% increase in the average cost of goods sold. A pattern whereby where many pharmaceutical manufacturers are transitioning from smaller batch production and moving toward larger batch production sizes in order to increases efficiencies was identified. The research also proposed the use of a serialisation depreciation factor as a method to determine the impact of serialisation on the cost of goods sold. This is the first study of its kind into the cost of serialisation from a manufacturer's viewpoint and studying the effects of serialisation on productivity, line availability and operational efficiency.

The growing complexity of biopharmaceutical sponsored trials has adverse impacts on increased burdens on participants, clinical sites, and sponsors, including greater difficulty recruiting and retaining participants, difficulty engaging sites to participate in trials, excessive cost of trials, and increased cycle times. The schedule of assessments (SoAs) is the origin of and blueprint for complexity that is often generated by copying and pasting from previous SoAs. We developed an approach, termed Lean Design, for redesigning the assessments in SoAs that generate data, the 'Data SoA.' It starts with a simple "ground zero" SoA. Any addition is challenged using several principles of trial design. We employed a system, the Faro Trial Designer Tool, to quantify the impacts of changes in an SoA to provide real-time feedback to the team and sponsor. We applied the approach in workshops with teams for six clinical trials in various stages of design and implementation. The approach resulted in recommendation for substantial potential savings in participant and site staff time, costs, and complexity of the trials. Application of this approach to very early stages of protocol design has the potential to reduce the complexity of biopharmaceutical sponsored trials and its consequences.

Background: Despite global efforts to improve paediatric clinical trials, significant delays continue in paediatric drug approvals. Collaboration between research networks is needed to address these delays. This paper is a first step to promote interoperability between paediatric networks from different jurisdictions by comparing drivers for, and content of, metrics about clinical trial conduct.

Methods: Three paediatric networks, Institute for Advanced Clinical Trials for Children, the Maternal Infant Child and Youth Research Network and conect4children, have each developed metrics to address delays and create efficiencies. We identified the methodology by which each network identified metrics, described the metrics of each network, and mapped consistency to come to consensus about core metrics that networks could share.

Results: Metric selection was driven by site quality improvement in one network (11 metrics), by network performance in one network (13 metrics), and by both in one network (five metrics). The domains of metrics were research capacity/capability, site identification/feasibility, trial start-up, and recruitment/enrolment. The network driven by site quality improvement did not have indicators for capacity/capability or identification/feasibility. Fifteen metrics for trial start up and conduct were identified. Metrics related to site approvals were found in all three networks. The themes for metrics can inform the development of 'shared' metrics.

Conclusion: We found disparity in drivers, methodology and metrics. Tackling this disparity will result in a unified approach to addressing delays in paediatric drug approvals. Collaborative work to define inter-operable metrics globally is outlined.

In psychiatry clinical trials, an instrument or questionnaire with rating scale is often used to access safety and efficacy of a test treatment under investigation. Statistical analysis based on the collected rating scale is then performed a determine whether there is an improvement in endpoint change from baseline mean scale. This approach needs on absolute change, however, may not actually reflect the performance of the test treatment under study because the change, which may be considered of clinically importance, may fall within the same category in terms of disease severity such as mild, moderate, and severe. In this case, it is suggested, in addition to absolute change approach, a categorical shift analysis be considered to determine whether the endpoint change from baseline has resulted in an improvement in categorical shift, in terms of disease severity shift e.g., from severe to mild or moderate. In this article, we explore the relationship between absolute change approach and categorical shift analysis based on rating scales for assessment of test treatment under study.

The ICH E17 guidelines (2014-2017) on Multiregional Clinical Trials (MRCT) was a joint effort by the regulators and industry to facilitate simultaneous global drug development and registration through taking a strategic approach for clinical trials. In other words, the objective was to reduce the time it takes to bringing medications to patients around the world through minimizing unnecessary duplication of local or regional studies, which may add the regulatory burden to cost and time of bringing new therapies to patients. Under the auspices of ICH, training materials were created and provided to various stakeholders. Despite the successful promotion of the benefits of ICH E17 MRCT guidelines across the different regions, the uptake of some concepts (e.g., pooling strategy) in the ICH E17 guidelines has been slow. This paper describes various factors which could affect the conduct of MRCT at a global level, including ambiguity in definition of "region" (in MRCT), new regulatory requirements to enroll a diverse patient population, the use of decentralized clinical trials, use of data sources other than randomized clinical trials (e.g., use of Real Word Data), and the impact of the COVID-19 pandemic on the conduct of MRCT.

Chimeric antigen receptor (CAR) T-cell therapy is a human gene therapy product where T cells from a patient are genetically modified to enable them to recognize desired target antigen(s) more effectively. In recent years, promising antitumor activity has been seen with autologous CAR T cells. Since 2017, six CAR T-cell therapies for the treatment of hematological malignancies have been approved by the Food and Drug Administration (FDA). Despite the rapid progress of CAR T-cell therapies, considerable statistical challenges still exist for this category of products across all phases of clinical development that need to be addressed. These include (but not limited to) dose finding strategy, implementation of the estimand framework, use of real-world data in contextualizing single-arm CAR T trials, analysis of safety data and long-term follow-up studies. This paper is the first step in summarizing and addressing these statistical hurdles based on the development of the six approved CAR T-cell products.