Therapeutic innovation & regulatory science最新文献

Background: Digital therapeutics (DTx) have attracted attention as the substitutes or add-ons to conventional pharmacotherapy and the number of DTx products authorized with the regulatory reviews of the clinical evidence is increasing. Insomnia is one of the major targets of the DTx due to the benefit from cognitive behavioral interventions and several products have been launched in the market with regulatory reviews. However, common features of the products and the clinical evidence required by each regulatory agency have not been investigated.

Methods: In this study, we identified the DTx products with the primary indication of insomnia authorized with regulatory reviews of clinical evidence by literature and website searches, and investigated the common features of the products and of the study designs for the pivotal clinical trials.

Results: The total of 6 DTx products were identified. The components of cognitive behavioral therapy for insomnia (CBT-I) were identified as common features of the products. All the pivotal clinical trials were randomized, parallel-group, blind studies against insomnia patients. No products have been authorized in multiple countries regardless of the similarity of the features of the products and of the study designs for the pivotal clinical trials.

Conclusions: Our study revealed that the components of CBT-I and gold standard design in pivotal clinical trials were adopted in all the DTx products for insomnia authorized with reviews of clinical evidence. At the same time, our findings suggest the needs of internationally harmonized regulatory review and authorization system to facilitate the early patient access to the promising DTx products.

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.

The phenomenon of delta inflation, in which design treatment effects tend to exceed observed treatment effects, has been documented in several therapeutic areas. Delta inflation has often been attributed to investigators' optimism bias, or an unwarranted belief in the efficacy of new treatments. In contrast, we argue that delta inflation may be a natural consequence of clinical equipoise, that is, genuine uncertainty about the relative benefits of treatments before a trial is initiated. We review alternative methodologies that can offer more direct evidence about investigators' beliefs, including Bayesian priors and forecasting analysis. The available evidence for optimism bias appears to be mixed, and can be assessed only where uncertainty is expressed explicitly at the trial design stage.

The expanding availability of real-world data (RWD) has led to an increase in both the interest and possibilities for using this information in postmarketing safety analyses and signal management. While there is enormous potential value from the safety insights generated through RWD, the analysis preparation, execution, and communication required to reliably deliver the evidence can be time consuming. Since the safety signal assessment process is a regulated and timebound process, any supporting RWD analyses require a rapid turnaround of well-designed and informative results. To address this challenge, a TransCelerate BioPharma working group was formed and developed a framework to help teams responsible for safety signal assessment overcome the challenges of working with RWD rapidly to deliver analyses within regulatory timelines. Here, a previously performed safety assessment was evaluated within the context of the developed framework to illustrate how the framework may be adopted in practice.

The results of observational studies using real-world data, known as real-world evidence, have gradually started to be used in drug development and decision-making by policymakers. A good quality management system-a comprehensive system of process, data, and documentation to ensure quality-is important in obtaining real-world evidence. A risk-based approach is a common quality management system used in interventional studies. We used a quality management system and risk-based approach in an observational study on a designated intractable disease. Our multidisciplinary team assessed the risks of the real-world data study comprehensively and systematically. When using real-world data and evidence to support regulatory decisions, both the quality of the database and the validity of the outcome are important. We followed the seven steps of the risk-based approach for both database selection and research planning. We scored the risk of two candidate databases and chose the Japanese National Database of designated intractable diseases for this study. We also conducted a quantitative assessment of risks associated with research planning. After prioritizing the risks, we revised the research plan and outcomes to reflect the risk-based approach. We concluded that implementing a risk-based approach is feasible for an observational study using real-world data. Evaluating both database selection and research planning is important. A risk-based approach can be essential to obtain robust real-world evidence.

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.

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.