scholarly journals Assessing the legal duty to use or disclose interim data for ongoing clinical trials

2019 ◽  
Vol 6 (1) ◽  
pp. 51-84
Author(s):  
Lisa Eckstein
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Large Scale ◽  
Clinical Trial Data ◽  
New Drugs ◽  
Therapeutic Interventions ◽  
Scientific Integrity ◽  
Randomized Controlled Clinical Trials ◽  
Legal Obligations ◽  
Legal Duty

Abstract Randomized controlled clinical trials, leading to large-scale meta-analyses, are considered the gold standard for research evaluating new drugs and other therapeutic interventions. To promote scientific integrity and prevent the adoption of potentially fallacious early trends, emerging information is commonly shielded from sponsors, investigators, and other clinical trial actors, including through the use of independent Data and Safety Monitoring Boards (DSMBs). Once established, a DSMB is usually the only body to have access to unblinded information until trial completion or the crossing of pre-specified, and often highly stringent, stopping boundaries. Yet, in certain circumstances, clinical trial actors have legal obligations to trial participants and others to use or disclose emerging information. This paper canvasses potential legal obligations to use or disclose emerging clinical trial data, including through tort law and securities laws. The analysis is supplemented by a comprehensive search of US cases in which courts have adjudicated upon such allegations. Notably, available cases demonstrate widespread judicial deference to clinical trial practices designed to shield clinical trial actors from emerging information. As a result, despite a theoretical possibility of legal obligations of use or disclosure, it appears that these will rarely be enforceable.

Clinical Trial Data Management Software: A Review of the Technical Features

2019 ◽  
Vol 14 (3) ◽  
pp. 160-172 ◽  
Author(s):  
Aynaz Nourani ◽  
Haleh Ayatollahi ◽  
Masoud Solaymani Dodaran
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Data Management ◽  
Clinical Data ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Data Management System ◽  
Management Systems ◽  
Data Management Systems ◽  
Technical Features

Background:Data management is an important, complex and multidimensional process in clinical trials. The execution of this process is very difficult and expensive without the use of information technology. A clinical data management system is software that is vastly used for managing the data generated in clinical trials. The objective of this study was to review the technical features of clinical trial data management systems.Methods:Related articles were identified by searching databases, such as Web of Science, Scopus, Science Direct, ProQuest, Ovid and PubMed. All of the research papers related to clinical data management systems which were published between 2007 and 2017 (n=19) were included in the study.Results:Most of the clinical data management systems were web-based systems developed based on the needs of a specific clinical trial in the shortest possible time. The SQL Server and MySQL databases were used in the development of the systems. These systems did not fully support the process of clinical data management. In addition, most of the systems lacked flexibility and extensibility for system development.Conclusion:It seems that most of the systems used in the research centers were weak in terms of supporting the process of data management and managing clinical trial's workflow. Therefore, more attention should be paid to design a more complete, usable, and high quality data management system for clinical trials. More studies are suggested to identify the features of the successful systems used in clinical trials.

scholarly journals Practical and conceptual issues of clinical trial registration for Brazilian researchers

2015 ◽  
Vol 134 (1) ◽  
pp. 28-33 ◽  
Author(s):  
Carolina Gomes Freitas ◽  
Thomas Fernando Coelho Pesavento ◽  
Maurício Reis Pedrosa ◽  
Rachel Riera ◽  
Maria Regina Torloni
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
International Committee ◽  
New Drugs ◽  
Trial Registration ◽  
Clinical Trial Registry ◽  
Clinical Trial Registration ◽  
Registration Process ◽  
Trial History ◽  
Definition Of

CONTEXT AND OBJECTIVE: Clinical trial registration is a prerequisite for publication in respected scientific journals. Recent Brazilian regulations also require registration of some clinical trials in the Brazilian Clinical Trials Registry (ReBEC) but there is little information available about practical issues involved in the registration process. This article discusses the importance of clinical trial registration and the practical issues involved in this process. DESIGN AND SETTING: Descriptive study conducted by researchers within a postgraduate program at a public university in São Paulo, Brazil. METHODS: Information was obtained from clinical trial registry platforms, article reference lists and websites (last search: September 2014) on the following topics: definition of a clinical trial, history, purpose and importance of registry platforms, the information that should be registered and the registration process. RESULTS: Clinical trial registration aims to avoid publication bias and is required by Brazilian journals indexed in LILACS and SciELO and by journals affiliated to the International Committee of Medical Journal Editors (ICMJE). Recent Brazilian regulations require that all clinical trials (phases I to IV) involving new drugs to be marketed in this country must be registered in ReBEC. The pros and cons of using different clinical trial registration platforms are discussed. CONCLUSIONS: Clinical trial registration is important and various mechanisms to enforce its implementation now exist. Researchers should take into account national regulations and publication requirements when choosing the platform on which they will register their trial.

scholarly journals Canadian Recommendations for Clinical Trials of Pharmacologic Interventions in Rheumatoid Arthritis: Inclusion Criteria and Study Design: Table 1.

2011 ◽  
Vol 38 (10) ◽  
pp. 2095-2104 ◽  
Author(s):  
JACOB KARSH ◽  
EDWARD C. KEYSTONE ◽  
BOULOS HARAOUI ◽  
J. CARTER THORNE ◽  
JANET E. POPE ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Disease Activity ◽  
Study Design ◽  
New Drugs ◽  
Nominal Group ◽  
Consensus Method ◽  
Inclusion Criteria ◽  
Design Features

Objective.Current clinical trial designs for pharmacologic interventions in rheumatoid arthritis (RA) do not reflect the innovations in RA diagnosis, treatment, and care in countries where new drugs are most often used. The objective of this project was to recommend revised entry criteria and other study design features for RA clinical trials.Methods.Recommendations were developed using a modified nominal group consensus method. Canadian Rheumatology Research Consortium (CRRC) members were polled to rank the greatest challenges to clinical trial recruitment in their practices. Initial recommendations were developed by an expert panel of rheumatology trialists and other experts. A scoping study methodology was then used to examine the evidence available to support or refute each initial recommendation. The potential influence of CRRC recommendations on primary outcomes in future trials was examined. Recommendations were finalized using a consensus process.Results.Recommendations for clinical trial inclusion criteria addressed measures of disease activity [Disease Activity Score 28 using erythrocyte sedimentation rate (DAS28-ESR) > 3.2 PLUS ≥ 3 tender joints using 28-joint count (TJC28) PLUS ≥ 3 swollen joint (SJC28) OR C-reactive protein (CRP) or ESR > upper limit of normal PLUS ≥ 3 TJC28 PLUS ≥ 3 SJC28], functional classification, disease classification and duration, and concomitant RA treatments. Additional recommendations regarding study design addressed rescue strategies and longterm extension.Conclusion.There is an urgent need to modify clinical trial inclusion criteria and other study design features to better reflect the current characteristics of people living with RA in the countries where the new drugs will be used.

scholarly journals Awareness and Opinions of Research Professionals on India's New Drug and Clinical Trials Regulations: Protocol for a Cross-Sectional Web-Based Survey Study

10.2196/14744 ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. e14744
Author(s):  
Vishal Vennu ◽  
Saurabh Dahiya
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
New Drugs ◽  
Survey Study ◽  
Multiple Sources ◽  
Cross Sectional ◽  
Web Based ◽  
Google Docs ◽  
New Drug ◽  
Research Professionals

Background Although several studies have been conducted and several articles have been published on India's new clinical trial regulations, very few have examined the views of investigators and ethics board members regarding modifications to the previous regulations. Overall, they have neglected to find out the opinions of other relevant professionals, such as research assistants, coordinators, associates, and managers. To our knowledge, no study has yet investigated the awareness and opinions of Indian research professionals on the new 2019 regulations. Objective This study aims to describe the awareness and opinions of Indian research professionals on the new drug and clinical trial regulations. Methods In this cross-sectional, Web-based study, we will conduct an open survey for various Indian research professionals. These professionals will be selected randomly using multiple sources. The survey questionnaires, which have already been validated, were developed using the form function in Google docs. A Web link was generated for participants to take the survey. Descriptive statistics will be shown as means and standard deviations for constant variables, whereas certain variables will instead be shown as numbers and percentages. Results The survey was opened in July 2019. Enrollment has already started and will be completed in three months. The results calculations are expected to begin in October 2019. Conclusions The results of the survey are expected to represent the views of research professionals on the new regulations that will support the development of clinical research and the pharmaceutical industry in India. These regulations are expected to help advance clinical trials, help with the approval of new drugs, and enhance ethical norms in the country. International Registered Report Identifier (IRRID) PRR1-10.2196/14744

scholarly journals Clinical Trial Regulations In India : Past, Present and Future

JMS SKIMS ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 5-17
Author(s):  
Haroon Rashid
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Disease Burden ◽  
International Standards ◽  
New Drugs ◽  
Safety And Efficacy ◽  
Long Time ◽  
Regulatory Bodies ◽  
Guidance Documents ◽  
Human Use

Clinical trials are the only way of establishing the safety and efficacy of any new drug before its introduction in the market for human use. Clinical trials (with safeguards) are necessary for introduction of new drugs for a country like India, considering its disease burden and emergence of new variants of disease.The regulatory bodies need to frame guidelines and regulatory approval processes on a par with international standards. Many of the new laws, guidance documents, notifications and initiatives for regulating pharmaceutical industry were in the charts for quite a long time. Indian regulatory authorities have started looking into speedy implementation and providing support in terms ofnecessary infrastructure and investment. JMS 2017; 20(1):5-17

Mining Clinical Trial Data

2011 ◽  
pp. 31-47
Author(s):  
Jose Ma. J. Alvir ◽  
Javier Cabrera
Keyword(s):  
Data Mining ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Trial Data ◽  
Treated Group ◽  
Trial Data ◽  
Controlled Trials ◽  
Clinical Trails ◽  
Important Objective

Mining clinical trails is becoming an important tool for extracting information that might help design better clinical trials. One important objective is to identify characteristics of a subset of cases that responds substantially differently than the rest. For example, what are the characteristics of placebo respondents? Who have the best or worst response to a particular treatment? Are there subsets among the treated group who perform particularly well? In this chapter we give an overview of the processes of conducting clinical trials and the places where data mining might be of interest. We also introduce an algorithm for constructing data mining trees that are very useful for answering the above questions by detecting interesting features of the data. We illustrate the ARF method with an analysis of data from four placebo-controlled trials of ziprasidone in schizophrenia.

scholarly journals The impact of patient-reported outcome (PRO) data from clinical trials: a systematic review and critical analysis

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Samantha Cruz Rivera ◽  
Derek G. Kyte ◽  
Olalekan Lee Aiyegbusi ◽  
Anita L. Slade ◽  
Christel McMullan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Case Studies ◽  
Real World ◽  
Clinical Trial Data ◽  
Research Impact ◽  
Trial Data ◽  
Patient Reported ◽  
The Impact

Abstract Background Patient-reported outcomes (PROs) are commonly collected in clinical trials and should provide impactful evidence on the effect of interventions on patient symptoms and quality of life. However, it is unclear how PRO impact is currently realised in practice. In addition, the different types of impact associated with PRO trial results, their barriers and facilitators, and appropriate impact metrics are not well defined. Therefore, our objectives were: i) to determine the range of potential impacts from PRO clinical trial data, ii) identify potential PRO impact metrics and iii) identify barriers/facilitators to maximising PRO impact; and iv) to examine real-world evidence of PRO trial data impact based on Research Excellence Framework (REF) impact case studies. Methods Two independent investigators searched MEDLINE, EMBASE, CINAHL+, HMIC databases from inception until December 2018. Articles were eligible if they discussed research impact in the context of PRO clinical trial data. In addition, the REF 2014 database was systematically searched. REF impact case studies were included if they incorporated PRO data in a clinical trial. Results Thirty-nine publications of eleven thousand four hundred eighty screened met the inclusion criteria. Nine types of PRO trial impact were identified; the most frequent of which centred around PRO data informing clinical decision-making. The included publications identified several barriers and facilitators around PRO trial design, conduct, analysis and report that can hinder or promote the impact of PRO trial data. Sixty-nine out of two hundred nine screened REF 2014 case studies were included. 12 (17%) REF case studies led to demonstrable impact including changes to international guidelines; national guidelines; influencing cost-effectiveness analysis; and influencing drug approvals. Conclusions PRO trial data may potentially lead to a range of benefits for patients and society, which can be measured through appropriate impact metrics. However, in practice there is relatively limited evidence demonstrating directly attributable and indirect real world PRO-related research impact. In part, this is due to the wider challenges of measuring the impact of research and PRO-specific issues around design, conduct, analysis and reporting. Adherence to guidelines and multi-stakeholder collaboration is essential to maximise the use of PRO trial data, facilitate impact and minimise research waste. Trial registration Systematic Review registration PROSPERO CRD42017067799.

scholarly journals 2166

2017 ◽  
Vol 1 (S1) ◽  
pp. 12-12
Author(s):  
Jianyin Shao ◽  
Ram Gouripeddi ◽  
Julio C. Facelli
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Power Distribution ◽  
Large Scale ◽  
Search Space ◽  
Free Text ◽  
Eligibility Criteria ◽  
Clinical Notes ◽  
Semantic Concepts ◽  
Mimic Iii

OBJECTIVES/SPECIFIC AIMS: This poster presents a detailed characterization of the distribution of semantic concepts used in the text describing eligibility criteria of clinical trials reported to ClincalTrials.gov and patient notes from MIMIC-III. The final goal of this study is to find a minimal set of semantic concepts that can describe clinical trials and patients for efficient computational matching of clinical trial descriptions to potential participants at large scale. METHODS/STUDY POPULATION: We downloaded the free text describing the eligibility criteria of all clinical trials reported to ClinicalTrials.gov as of July 28, 2015, ~195,000 trials and ~2,000,000 clinical notes from MIMIC-III. Using MetaMap 2014 we extracted UMLS concepts (CUIs) from the collected text. We calculated the frequency of presence of the semantic concepts in the texts describing the clinical trials eligibility criteria and patient notes. RESULTS/ANTICIPATED RESULTS: The results show a classical power distribution, Y=210X(−2.043), R2=0.9599, for clinical trial eligibility criteria and Y=513X(−2.684), R2=0.9477 for MIMIC patient notes, where Y represents the number of documents in which a concept appears and X is the cardinal order the concept ordered from more to less frequent. From this distribution, it is possible to realize that from the over, 100,000 concepts in UMLS, there are only ~60,000 and 50,000 concepts that appear in less than 10 clinical trial eligibility descriptions and MIMIC-III patient clinical notes, respectively. This indicates that it would be possible to describe clinical trials and patient notes with a relatively small number of concepts, making the search space for matching patients to clinical trials a relatively small sub-space of the overall UMLS search space. DISCUSSION/SIGNIFICANCE OF IMPACT: Our results showing that the concepts used to describe clinical trial eligibility criteria and patient clinical notes follow a power distribution can lead to tractable computational approaches to automatically match patients to clinical trials at large scale by considerably reducing the search space. While automatic patient matching is not the panacea for improving clinical trial recruitment, better low cost computational preselection processes can allow the limited human resources assigned to patient recruitment to be redirected to the most promising targets for recruitment.

Metastatic colorectal cancer (mCRC) patterns of care: Implications for clinical trial design

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 4079-4079 ◽  
Author(s):  
C. S. Denlinger ◽  
M. A. Collins ◽  
Y. Wong ◽  
S. Litwin ◽  
N. J. Meropol
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Clinical Trials ◽  
Trial Design ◽  
Clinical Trial Design ◽  
New Drugs ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Treatment Change ◽  
Therapy Regimen

4079 Background: New approaches have expanded options for patients (pts) with mCRC. To characterize current practice paradigms that might bear on clinical trial design, we analyzed decision-making and treatment patterns in pts treated at a Comprehensive Cancer Center since the introduction of cetuximab (CET), and bevacizumab (BV). Methods: A retrospective review of all pts diagnosed with mCRC between 3/1/04 and 8/28/06 treated at Fox Chase Cancer Center. Results: 160 pts were treated, with 157 pts receiving at least one therapy regimen by 10 attending oncologists. There were 350 changes in therapy with 246 (70%) including continuation of at least one prior drug (92 BV, 111 fluoropyrimidines, 43 other). The most common reasons for treatment change were toxicity (33%), progressive disease (PD) (29%), treatment breaks (15%), and metastasectomy (11%) ( Table ). PD was a more common cause for treatment discontinuation in later phases of treatment (18% initial regimen vs. 36% subsequent regimens, p=0.0002). 24% of pts treated with oxaliplatin (OX) discontinued due to neuropathy. Hypersensitivity caused discontinuation in 5% of pts with OX and 7% of pts with CET. Resection of metastases was undertaken in 38% of pts. 43% of these pts received neoadjuvant therapy, and 56% received adjuvant therapy. 30% of pts have died, 29% remain on active treatment, 28% are on a treatment break, 3% are on hospice, and 11% are lost to follow-up. Conclusions: PD is no longer the primary reason for change of therapy in pts with mCRC. Metastasectomy is common and OX neuropathy is often treatment-limiting. These findings have important implications for endpoint selection and design of clinical trials in mCRC. Future clinical trials in mCRC must recognize treatment complexities and capture key components of decision-making that may result in prolonged survival. Furthermore, treatment breaks represent a potential window for the evaluation of new drugs. [Table: see text] No significant financial relationships to disclose.

The rate of tumor growth, g, as a biomarker for overall survival (OS) in prostate cancer (PC) in clinical trials as well as in real-world data from the Veterans Administration Medical Centers (VAMCs).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 5074-5074
Author(s):  
Harshraj Leuva ◽  
Mengxi Zhou ◽  
Julia Wilkerson ◽  
Keith Sigel ◽  
Ta-Chueh Hsu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Trial ◽  
Overall Survival ◽  
Clinical Trials ◽  
Tumor Growth ◽  
Real World ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Real World Data ◽  
World Data

5074 Background: Novel assessments of efficacy are needed to improve determination of treatment outcomes in clinical trials and in real-world settings. Methods: Cancer treatments usually lead to concurrent regression and growth of the drug-sensitive and drug-resistant fractions of a tumor, respectively. We have exploited novel methods of analysis that assess these two simultaneous processes and have estimated rates of tumor growth ( g) and regression ( d) in over 30,000 patients (pts) with diverse tumors. Results: In prostate cancer (PC) we have analyzed both clinical trial and real-world data from Veterans. Using clinical trial data from 6819 pts enrolled in 15 treatment arms we have established separately and by combining all the data that g correlates highly (p<0.0001) with overall survival (OS) – slower g associated with better OS. In PC, abiraterone (ABI) and docetaxel (DOC) are superior to placebo, prednisone and mitoxantrone. ABI (median g =0.0017) is superior to DOC ( g=0.0021) in first line (p=0.0013); and ABI in 2nd line ( g=0.0034) is inferior to ABI in 1st line ( g=0.0017; p<0.0001). Finally, using combined clinical trial data as a benchmark we could assess the efficacy of novel therapies in as few as 30-40 patients. Amongst 7457 Veterans, the median g on a taxane ( g=0.0022) was similar to that from clinical trials ( g=0.0012). Although only 258 Veterans received cabazitaxel (CAB), g values for CAB ( g=0.0018) and DOC ( g=0.0023) were indistinguishable (p=0.3) consistent with their identical mechanism of action. Finally, outcomes with DOC in African American (AA) ( g=0.00212) and Caucasian ( g=0.00205) Veterans were indistinguishable (p=0.9) and comparable across all VAMCs. Conclusions: The rate of tumor growth, g, is an excellent biomarker for OS both in clinical trials and in real-world settings. g allows comparisons between trials and for large trial data sets to be used as benchmarks of efficacy. Real-world outcomes in the VAMCs are similar to those in clinical trials. In the egalitarian VAMCs DOC efficacy in PC is comparable in AA and Caucasian Veterans -- indicating inferior outcomes reported in AAs are likely due to differential health care access, not differences in biology.

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