The concept of 'one size fits all' - one treatment for patients with a particular disease, seems to be outdated. The advent of precision medicine has prompted profound changes in clinical research and it allows researchers to predict more accurately, the prevention and treatment strategies for a specific disease population. Novel study designs are, therefore, essential to establish safe and effective personalized medicine. Basket, umbrella and platform trial designs (collectively referred to as master protocols) are biomarker enrichment designs that allow for testing more than one hypotheses within a protocol, thus accelerating drug development. These trial designs tailor intervention strategies based on patient's risk factor(s) that can help predict whether they will respond to a specific treatment. Basket trials evaluate therapy for various diseases that share a common molecular alteration, while umbrella trials evaluate multiple targeted therapies for a single disease that is stratified into subgroups based on different molecular alterations/ risk factors. These designs are complex and their major limitations stem from the fact that it would be inappropriate to completely replace histological typing with molecular profiling alone. However, in the upcoming decades, these trial designs are likely to gain popularity and improve the efficiency of clinical research. This article briefly overviews the characteristics of master protocol designs with examples of completed and ongoing clinical trials utilizing these study designs.
BACKGROUND:Several studies reported that abnormal behavior was noted in pediatric patients receiving several drugs, including neuraminidase inhibitors (NIs). However, the information on drugs associated with abnormal behavior in a real-world setting remains limited. The purpose of this study was to clarify the drugs associated with abnormal behavior using a spontaneous reporting system database.METHODS:We performed a retrospective pharmacovigilance disproportionality analysis using the Japanese Adverse Drug Event Report database. Adverse event reports submitted to the Pharmaceuticals and Medical Devices Agency were analyzed, and the reporting odds ratio at 95% confidence interval were calculated.RESULTS:A total of 1,144 reports of abnormal behavior were identified. The signals were detected through the association of 4 neuraminidase inhibitors (oseltamivir, zanamivir, laninamivir, and peramivir) with the abnormal behaviour. These signals were stronger for oseltamivir than other neuraminidase inhibitors. The signals were also detected for acetaminophen and montelukast.CONCLUSION:Our results should be able to raise physicians' awareness of drugs associated with abnormal behavior, but further investigation of these medications is warranted.
BACKGROUND:It has been recognized that patients should be involved in the design of clinical trials. However, there is a lack of agreement on what patient-centricity means.METHODS:In this article, a Patient Motivation Pyramid based on Maslow's theory of human motivation is introduced as a tool to identify patient needs. This pyramid is used to make a comprehensive overview of options to implement a patient-centric trial design. The Pyramid with the described options can help to identify patient-centric activities suitable for given drug development. The current article further describes the potential benefits of patient-centric trial designs with an emphasis on early clinical development. Especially in early clinical development, during which trials have many assessments per patient, and the safety and clinical efficacy are uncertain, patient-centric trial design can improve feasibility. Finally, we present three case examples on patient-centric trial design. The first example is seeking patient input on the trial design for a First-in-Human trial which includes patients with Immune Thrombocytopenic Purpura. The second example is the use of a video-link for home dosing. The final example is the use of digital medicine in a decentralized trial in heart failure patients.RESULTS:A comprehensive overview of patients' needs can be accomplished by building a Patient Motivation Pyramid as a tool. Patient input can lead to improved endpoints, improved feasibility, better recruitment, less dropout, less protocol amendments, and higher patient satisfaction. The use of digital medicine can lead to a trial design with much less visits to the clinical research center in early clinical development and in a later development phase, even to a complete virtual trial.CONCLUSION:We recommend using the Patient Motivation Pyramid as a structural approach for identifying elements of patient-centricity. Secondly, we recommend starting using patient-centric approaches in an early phase of the medicine's lifecycle.
Characterized by small, highly heterogeneous patient populations, rare disease trials magnify the challenges often encountered in traditional clinical trials. In recent years, there have been increased efforts by stakeholders to improve drug development in rare diseases through novel approaches to clinical trial designs and statistical analyses. We highlight and discuss some of the current and emerging approaches aimed at overcoming challenges in rare disease clinical trials, with a focus on the ultimate stakeholder, the patient.
BACKGROUND:We assessed the extent to which urinary and fecal excretion of 14C-labeled drug material in animal ADME studies was predictive of human ADME studies. We compared observed plasma elimination half-lives for total drug-related radioactivity in humans to pre-study predictions, and we estimated the impact of any major differences on human dosimetry calculations.METHODS:We included 34 human ADME studies with doses of 14C above 0.1 MBq. We calculated ratios of dosimetry input parameters (percentage fecal excretion in humans versus animals; observed half-life in humans versus predicted pre-study) and output parameters (effective dose post-study versus pre-study) and assessed their relationship.RESULTS:A quantitative correlation assessment did not show a statistically significant correlation between the ratios of percentages of 14C excreted in feces and the ratios of dosimetry outcomes in the entire dataset, but a statistically significant correlation was found when assessing the studies that were based on ICRP 60/62 (n=19 studies; P=0.0028). There also appeared to be a correlation between the plasma half-life ratios and the ratios of dosimetry results. A quantitative correlation assessment showed that there was a statistically significant correlation between these ratios (P<0.0001).CONCLUSION:In all cases where the plasma elimination half-life for 14C in humans was found to be longer than the predicted value, the radiation burden was still within ICRP Category IIa. Containment of the actual radiation burden below the limit of 1.00 mSv appeared to be determined partly also by our choice to limit 14C doses to 3.7 MBq.
