Monday, December 15, 2014

What is the "Ideal" EDC System for a Clinical Data Manager?

Conducting a clinical study requires the collection of a large amount of data that can be entered, checked, confirmed and finally grouped together in a single database. Setting up a central database and electronic collection via the Internet called eCRF (electronic case report forms) meets these needs by combining technology, simplicity, privacy and data security.

According to a study by CenterWatch, if the market continues to adopt EDC and ePRO technologies, paper diaries will no longer exist in 10 years. Should paper diaries still be used to collect subject data in clinical trials? CROS NT's expert Clinical Data Management team discusses this issue and what the ideal EDC system is for data collection.

There are several challenges to using paper CRF:
  • Massive amount of paperwork
  • Tedious for Investigators - repetition, data transfer, consistency
  • Tedious for Monitors
  • Logistical issues
  • All data must be transcribed
  • Data cannot be evaluated in real-time
  • More time and effort needed for data cleaning
  • Extended timelines from LPLV to DB Lock
eCRF significantly reduces the time and costs for certain stages of a clinical study. Direct and indirect costs can be reduced thanks to parallel operations during the use of a centralized database that can be accessed simultaneously by many people using the Internet.

Choosing the Ideal EDC System
Conducting studies in accordance with industry guidelines like ICH and GCP leads to reporting and documentation requirements that are burdensome and complicated. There is no real guidance from regulatory agencies on how to evaluate the many EDC systems available.

The availability of cost-effective, open source or proprietary EDC applications have the potential to improve clinical and research activities. User-friendly and simple interfaces, adherence to industry standard security protocols, customization and low maintenance costs are some of the major benefits.

Commercial EDC systems can be expensive in comparison to open source or proprietary EDC systems. It is important to evaluate and find the functions that best fit data management needs.

What do Data Managers want in an EDC System?

  • An EDC sytsem compliant with regulatory requirements: audit trails, data validation, system integrity
  • A system than enhances communication and sharing with users
  • Flexibility to allow for study specific customizations and dynamic forms
  • Intuitiveness and user-friendly system that is easy to navigate
  • Intuitive to select visits and enter data for end users
  • Easy to retrieve data queries
  • Efficient data cleaning and easy to update
  • Easy for study monitors to perform and mark SDV
  • Easy for Investigators to sign when CRFs are complete
CROS NT can also offer a cloud-based eClinical application which is an integrated platform of EDC/ePRO/IWRS/CTMS. Combining an eClinical platform in the cloud with a centralized approach to clinical data, Sponsors can reduce set-up, training and HelpDesk costs and allow for easy data integration. A cloud-based solution allows for real-time study management access to data from mobile devices.

Monday, December 1, 2014

5 Things to Consider in a Global Data Strategy

Most clinical trials today are being conducted on a global level with vast amounts of data to collect, analyze and report. Trial strategies include collecting data from multiple sources and sites, ideally in real time so Data Managers can manage discrepancies and unusual data patterns and Biostatisticians can analyze incoming data and make critical decisions on trial progress.

Therefore, when implementing a global data strategy, what factors should Sponsors consider in order to ensure efficient project management, timely and quality data and cost-effective measures? CROS NT guides you through some considerations:

1. Which technology solutions are best for managing vast amounts of data?

The obvious solution may be to consider an EDC solution for clinical data management which can organize multi-language, global study data into a single database.. Sponsors can resolve discrepancies faster and reduce time and costs with immediate feedback from patients. Data can be transferred in real time during the study into the eCRF. Query management is accelerated, and any inconsistencies in CRF or ePRO data can be checked in real time.

A cloud-based EDC system can eliminate the need to invest in an IT infrastructure while reducing training efforts. Cloud-based clinical applications also guarantee better data quality and data security through secure data transfer connections.

However, Sponsors should also consider eClinical platforms that include ePRO integration, CTMS and IWRS to manage all aspects of a clinical trial. It is important to note that not all EDC systems and/or eClinical applications fit all studies, so Sponsor should consult their CRO on which system is best.

2. Consider a Centralized Statistical Monitoring Approach

Centralized monitoring has been proposed as a new, more efficient approach to on-site visits. A CSM approach can be useful in detecting faulty equipment errors, negligence or fraud, protocol deviations and unexpected patterns which then identifies the sites that need further investigation. CSM has been suggested as a cheaper and more efficient alternative to on-site monitoring. Combining CSM with EDC and Clinical Data Visualization solutions can make monitoring extremely efficient and cost effective.

3. Should clinical data be centralized?

A centralized biometrics approach promises the Sponsor:
  • One relationship between the biometrics CRO and Sponsor and team continuity
  • Better integration of studies across all phases with common assessment methods and data standards
  • Uniform traceability of data
  • One set of biometrics Standard Operating Procedures
  • Centralization of study metrics and reporting
  • Cost reduction through the re-use of global libraries (savings up to 40%)
4. Building the Best, Most Efficient Project Team

The clinical data team is crucial to success and it’s important to have team continuity throughout global data projects. Sponsors should work closely with CROs to put together the best team of project managers, statisticians, data managers and medical writers. By centralizing biometrics, Sponsors can be ensured of the same biometrics team from start to finish. This is particularly important when it comes to the biostatistician who can provide insight from protocol to reporting through all phases of the development process.

Sponsors can also look to implement the Functional Service Provision model in which teams are assigned to a certain project for a fixed period of time. This allows the Sponsor to cover peaks and troughs in the workload while having a dedicated biometrics team.

5. Making Sense of Clinical Data: Biometrics Consultancy

Many challenges present themselves through the drug and device development process. Sponsors can’t be prepared for all issues that many arise: from trial design and sample size recalculation to regulatory challenges, sometimes Sponsors need help making sense of clinical data on a case-by-case basis. Having an expert biostatistician, data management expert or quality assurance professional available for consultancy can help Sponsors resolve small issues that arise during trials but have the potential to make a big impact.

Tuesday, November 11, 2014

Win-Win Approach for Clinical Trial Operations: Centralized Biometrics and Cloud Technology

The cost of bringing a new drug to market is now somewhere around $5 billion USD (according to Forbes) as the operational costs of conducting trials continue to rise. Sponsors are constantly looking for outsourcing methods that can cut costs. The centralized biometrics approach for clinical data has proven successful in the past at cutting costs - sometimes up to 40% with the use of global libraries. This strategy combined with cloud-based eClinical platforms can significantly reduce costs and timelines. As mentioned in last week's post, cloud technology solutions can speed up trials by 30%, pushing down costs by up to $400 million USD.

Centralized Biometrics

Using a centralized biometrics provider ensures a high level of importance and attention is given to clinical trial data. Efficiences include standardized data formats, uniform traceability of data, due diligence ready data sets and documentation as well as a single project manager for all data services.

Having the same biostatistician is also beneficial in order to provide expert consultancy on trial design and methodology, and/or apply methods to combine trial phases or adjust the sample size based on interim study results.

This model also provides financial benefits such as:
  • Saving up to 40% on database setup costs on second and subsequent studies when using EDC
  • Saving up to 40% on statistical programming costs for follow-on studies
  • Saving overall 30-40% on biometrics costs through the use of global libraries and standardized formats
Cloud Technology

Technology platforms such as EDC and ePRO solutions, pharmacovigilance applications, centralized storage and data visualization can be part of the centralized biometrics bundled package. It can potentially reduce setup, training and HelpDesk costs and allow for easy data integration. 

Cloud-based eClinical applications allow:
  • Negotiable expectations for clinical data entry into the application
  • Pay based on data quality 
  • Activity-based measurements as opposed to time based units of measure
  • Standard and ad-hoc reporting
  • Industry and regulatory compliant archival records
Risk Based Monitoring - Implementing Biometrics & the Cloud

Centralized Statistical Monitoring has been proposed as a new, more efficient and cost-effective approach to on-site visits. Centralized monitoring analyses are performed in a more efficient manner when data is centralized and the same biometrics study team has been collaborating since the beginning of the study.

In a CSM strategy, many discrepancies can be improved by implementing cloud-based technologies. Clinical Data Visualization and analytical business intelligence tools should be considered to query the EDC database and design reports for the main personnel involved in the trial review. This is especially important in order to aggregate data across multiple systems and even multiple studies. 

For more information on how to centralize your clinical data and implement a cloud-based eClinical platform, contact CROS NT.

Wednesday, November 5, 2014

Why Consider Cloud-Based EDC for your next Clinical Study?

The eClinical trial technologies market is set to reach $1.37 billion USD by 2018. The driving forces behind this surge are the need to optimize the drug development process through real-time data analysis and while cutting costs along the way. While various sectors such as small and large pharmaceutical companies, biotechnology companies and medical device companies have different trial needs, a strategic outsourcing approach that optimizes data collection and analysis can benefit any company in these sectors. Once you've decided on your clinical data outsourcing strategy, cloud-based technology can significantly improve the efficiency and accuracy of your next clinical study.

While CROS NT specializes in clinical data services - biostatistics, clinical data management and medical writing - its niche is the combination of biometrics services with clinical trial technology. We discuss why Sponsors should be shifting towards the cloud.

Several industry reports have estimated that the implementation of cloud computing technologies could lead to 30 percent increase in speed to trial for clinical work, resulting in up to $400 million USD in savings. If the market continues to adopt EDC/ePRO technologies, paper studies and subject diaries may no longer exist in 10 years or less.

Eliminating investment in IT infrastructure and reducing training efforts
Cloud computing allows companies to significantly cut budgets by not having to invest in computer software or hardware along with IT installation. It is estimated that computer systems can cost up to $2 million USD to install plus additional maintenance fees. Cloud-based systems generally require minimal training efforts due to high usability and packaged eLearning solutions which not only cuts training costs, but also logistical training expenses.

Better quality data, more efficient trials
Cloud-based EDC systems allow for real-time data, immediate feedback and real-time data transfer for query management and faster data cleaning. In addition to better data quality, cloud-based systems allow for global, multi-center and multi-language studies to be organized in one single database. This becomes extremely efficient for statisticians studying metrics in real-time. Real-time metrics are important in a risk-based monitoring strategy when data managers are evaluating unusual data patterns and statisticians are analyzing data in order to target sites that need further investigation.

Data Security
Cloud service providers can implement security measures, including user and password protections, and HTTPS connections to ensure secure and private data transfers to meet tough data privacy laws. Most cloud providers have disaster recovery plans in place to guarantee data protection in case of power or network failure.

Reducing clinical trial costs
Quicker trials generally translate into reduced timelines and inevitably costs. An added benefit to cloud-based technology is that they are usually configurable and pay-as-you-go features. Some cloud-based EDC systems can even provide baseline technology for low budgets with add-on features. This allows Sponsors to effectively manage a study budget and allows clinical personnel to be more independent in study build and management.

CROS NT and Cloud-Based EDC
CROS NT can also offer a cloud-based eClinical application which is an integrated platform of EDC/ePRO/IWRS/CTMS. Combining an eClinical platform in the cloud with a centralized approach to clinical data, Sponsors can reduce set-up, training and HelpDesk costs and allow for easy data integration. A cloud-based solution allows for real-time study management access to data from mobile devices.

Thursday, October 30, 2014

Good Practice Designs: Biostatistics for Breast Cancer Trials

October is Breast Cancer Awareness Month, and CROS NT is addressing the implications of conducting clinical studies in breast cancer and how Sponsors can implement smart designs and strategies to conduct more efficient trials. 

Oncology is perhaps the most complex therapeutic area in clinical trials with over 450 indications and various unique characteristics like slow recruitment and long timelines to reach clinical endpoints. While breast cancer is just one indication, it is the most common cancer in women worldwide, and it is estimated that 1 in 8 women in the U.S. will be diagnosed with breast cancer during her lifetime. Early detection and screening along with treatment options such as medicines and hormone growth therapy have aided in making progress in curing breast cancer.

However, according to, there are more than 2,000 ongoing breast cancer trials and approximately 1,000 ongoing in the EU according to its clinical trials register.

Good study designs in breast cancer trials can reduce the risk of failure in early phases. Oncology trials, particularly breast cancer trials, are unique for numerous reasons:
  • Use of various treatment combinations
  • Regimen modifications are likely during treatment
  • Slow recruitment
  • Numerous and complicated prognostic and predicative factors: age, menopausal status, hormone receptor status, etc.
  • Making the decision between adjuvant and neoadjuvant therapy
  • Determining HER2 status for possible monoclonal antibody treatment
What are the implications of these unique traits?
  • Study Design in early phases is extremely important: safety and efficacy, ethical considerations and long patient recruitment need to be taken into account
  • There will be vast amounts of data to analyze, including SAE safety data, and therefore biostatisticans will need access to real-time data in order to make go/no-go decisions.
  • Investing time in the proper design set-up of a breast cancer trial in the early phases is essential to increase success rates in later phases
Good Practice Designs: Involving the Biostatistician
The Statistical Analysis Plan for breast cancer trials, especially for Phase I trials, is extremely important in terms of determining trial design, sample size, endpoints and determining inclusion/exclusion criteria. The biostatistician should be involved in the beginning to consult on:
  • Protocol Development
  • Trial Design
  • Appropriate sample size calculation and possible recalculation
  • Defining Study Objectives and appropriate design
  • Defining the statistical method
  • Defining hypothesis and testing procedures
Good practice designs can speed up the planning phase enabling a reduction of time from the study synopsis to first patient in the study by defining adequate target criteria, interim analyses and specifying the most efficient statistical method for analysis. 

Considering an Adaptive Trial Design approach and consulting an expert biostatistician
Given the unique characteristics of breast cancer trials, Adaptive Trial Design can be an ideal statistical methodology for more efficient, cost-effective trials. It allows for the selection of the right target population for the drug. This is of special interest in the development of highly specific cancer drugs, which are only effective in a selected patient population, for example monoclonal antibodies. The advantages of adaptive design for breast cancer research are a reduction in overall time in the development of a drug, fewer patient required and the early availability of long-term safety data. Phase II/III seamless design has the possibility to select the right target population which is important for specific cancer drugs leading to fewer patients and quicker availability of safety data.

CROS NT & Breast Cancer
CROS NT has extensive expertise in conducting clinical studies in the oncology area - especially in the field of breast cancer. We have expert statisticians who have followed breast cancer studies from protocol design to reporting. CROS NT is also a supporter of breast cancer awareness and this month we raised funds for the National Breast Cancer Foundation at the Outsourcing in Clinical Trials OCT New England conference in Boston. 

Monday, September 29, 2014

RBM: Centralized Statistical Monitoring & Technology Considerations

On the 8th of October, CROS NT is sponsoring Nordic ePharma Day in Copenhagen. This event focuses on "Risk-Based Monitoring in Clinical Trials: a new approach for managing risk throughout the design, conduct and evaluation and reporting of clinical trials". 

Risk-based Monitoring (RBM) of clinical trials is an approach that combines on-site monitoring along with centralized remote monitoring by coordinating centers. Based on risk assessments about how the clinical information is captured and protocol designed, risk-based monitoring activities can be proactively supported by the usage of reporting tools. 

Leading up to this event, CROS NT discusses the considerations and impact of centralized statistical monitoring and which technology solutions will facilitate this approach. Centralized Statistical Monitoring (CSM) is the remote evaluation and analysis carried out by clinical trial personnel (e.g. clinical monitors, data managers, statisticians, etc) at a location other than on-site. This approach focuses on targeted data cleaning, subject level data review and statistical analysis to decide whether an on-site visit is triggered by risk. 

Why Centralized Statistical Monitoring (CSM)?

Centralized monitoring has been proposed as a new, more efficient approach to on-site visits. A CSM approach can be useful in detecting faulty equipment errors, negligence or fraud, protocol deviations and unexpected patterns which then identifies the sites that need further investigation.

Centralized monitoring techniques can be applied to:
  • The monitoring of data quality through routine review of submitted data to identify different types of errors
  • The identification of data trends not easily detected on-site like data consistency and accuracy or missing data
  • The analysis of site characteristics which aids in defining poorly performing sites
  • The verification of critical source data remotely
  • The completion of administrative/regulatory tasks
CSM has been suggested as a cheaper and more efficient alternative to on-site monitoring. Source Data Validation is usually time consuming and not as effective at identifying potential risks. A CSM approach performs data quality checks on all trial centers at the subject and site level. Statisticians can then analyze the data in real time to identify sites that need further investigation due to unusual data patterns.

The main errors found at the participant level are incorrect dates and outlying values. Meanwhile, at the site level, data discrepancies can be found when rounding numbers, comparing mean/average results, analysis of variability, inliers and correlation checks. In a CSM strategy, many of these discrepancies can be improved using technology solutions.

Technology Considerations

Electronic Data Capture is an essential part of an RBM technology strategy since it captures data in real time. EDC allows Investigators to capture and monitor site activity and captures data and determines which data need to be verified and analyzed. Although most EDC systems provide built-in reports to support data management activities, other metrics and information which are needed to verify the risk-based approach are not provided to final users.

Therefore, analytical business intelligence tools should be considered. By using a business intelligence tools to query the EDC database, reports can be designed depending on the target audience involved in the trial review including project and data managers, site staff, clinical monitors and safety staff. Reports with centralized monitoring metrics that assess site activity can be easily made available for quick analysis and decision-making.

Clinical data visualization and analysis are especially important to aggregate data across multiple systems and even multiple studies. An added value is the ability to drill-down data and click-through multiple levels of detail. Tools available today are generally cloud-based which means Sponsors avoid the technology hassle of HTML or plug-ins and enjoy the convenience of data "on the go". 

Nordic ePharma Day

Join CROS NT in Copenhagen on the 9th of October for Nordic ePharma Day to be part of the discussion on RBM in clinical trials. For more information visit the event website.

Monday, September 22, 2014

Making the Connection between Centralized Biometrics & Adaptive Trial Design

Flexible study designs are gaining popularity in clinical research as sponsors search for ways to reduce study timelines and costs by making modifications along the way. Implementing Adaptive Trial Design has been one flexible design that has proven successful for many clinical trials with 20-30% of trials now using this methodology. However the degree of success of this design approach doesn't just depend on the capabilities of your biostatistician. It can also depend on your outsourcing model.

CROS NT looks at the connection between a centralized biometrics outsourcing approach and adaptive trial design success.

In an adaptive approach, at each stage of the study and and in each phase of the drug or device development cycle, the probability of success is quantified and the study team is fully informed in order to evaluate risks and benefits associated with each decision. This begins with the protocol where scenario planning acts as a critical "stress test" key tool for demonstrating the value of adaptive design.

Ways of maximizing efficiency through adaptive designs are:
  • Early stopping (futility, early rejection)
  • Change in treatment allocation ratios
  • Alterations of hypothesis (non-inferiority vs. superiority)
  • Use of different test statistics
  • Sample size re-assessment
  • Dropping/adding treatment arms
  • Select special populations (inclusion/exclusion criteria)
  • Combination of trial phases (adaptive seamless design)
These are generally statistical concerns, therefore where does the centralized biometrics outsourcing model fit in?

It is generally agreed that the best time to involve a biostatistician in a clinical study is at the very beginning. This allows the biostatistician to understand the study design and make suggestions on hypothesis testing and analysis and also ensures continuity throughout the study team. If one study team - including the biostatistician - is assigned to trial design, data analysis and medical communications from the start, common data standards can be applied throughout the drug development process. This is a centralized approach to data collection and analysis.

As planning is an important step in preparing and implementing an adaptive design approach, there should be a good communication plan defined between the CRO and Sponsor. Agreeing on a statistical analysis plan, methodologies and programming formats can reduce the number of reviews, therefore saving time and costs.

In order for statisticians to make "go/no-go" decisions, they need access to real time data as soon it is collected. This can be achieved through a centralized approach when all data are stored in a central data warehouse and/or archive which avoids having to keep track of multiple repositories. 

The biostatistician really does collaborate with the rest of the study team, including Data Managers, Statistical Programmers and Medical Writers. Regarding Data Management, the biostatistician can assist with CRF development and dataset specifications. Working with statistical programmers, methodological statisticians ensure data formatting is correct and select data to be pooled. These interactions all contribute to the biostatistician's statistical analysis that lead to adaptations in a trial such as the decision to recalculate the sample size, alter study endpoints or even terminate a study. When the study data is dispersed among various sources, it becomes more time consuming for the biostatistician to gather the data needed and calls in question the quality of the data being pooled.

Some studies have already suggested that the implications of adaptive designs could save Sponsors between $100-200 million USD per year. Those savings, coupled with the considerable 30-40% cost savings of a centralized biometrics approach, due mostly to global libraries and achieved efficiencies through one project team, can result in significant cost savings for trial Sponsors.

CROS Academy: "Introduction to Adaptive Trial Design" Course

We are offering three courses this fall in adaptive trial design. These courses are designed to teach clinical trial professionals about the adaptations possible in a trial and how to use the proper statistical methodology.

"Introduction to Adaptive Trial Design" is being offered: