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 clinicltrials.gov, 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:

Tuesday, September 9, 2014

How well do you understand the role of Biostatistics in Clinical Research?

Statistics plays a crucial role in clinical trials and the drug development process - from trial design to protocol development. Having a fundamental understanding of statistical issues can uphold the integrity of a clinical trial and improve communications between clinicians and statisticians. 

As a clinical trial professional, non-statistician, are you familiar with the following statistical concepts?
  • Confidence intervals
  • Multiplicity
  • Subgroup Analysis
  • Parametric vs. Non-parametric statistical methods
  • Sample Size Calculation
  • Types of endpoints
  • Statistical Reporting
  • Missing Data
  • Adaptive Trial Design
  • Bayesian Model
Biostatistics are involved in every step of clinical research including trial design, protocol development, data management and monitoring, data analysis and clinical trial reporting. A Harvard report on clinical research demonstrated evidence that suggests the researchers often misinterpret statistical methods due to poor knowledge of statistical concepts.

Statisticians and clinical operations personnel must always communicate in order to ensure successful trial design and analyses. A factor that can often hinder effective communication is complicated statistical terminology. Since statisticians can specialize in study designs, even complex designs like Adaptive Trial Design, therapeutic areas and statistical methods, it is crucial that the rest of the study team understands the statistical strategy proposed by the biostatistician.

Why is it so important to understand the role of the biostatistician?
How well do you understand the statistical elements in these areas of clinical research?
  • Protocol Development & Design
  • Data Management
  • Study Implementation
  • Study Monitoring
  • Data Analysis & Reporting
The biostatistician works closely with the rest of the biometrics team and management throughout the study 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 biostatisticans ensure data formatting is correct and select data to be pooled. In terms of medical writing, biostatisticians will often write the statistical part of the Clinical Study Report.

In the Statistical Analysis Plan (SAP), the biostatistician will outline study endpoints, sample size calculation, interim analysis planning and the hypothesis and testing procedures. Perhaps the most well-known responsibility of the biostatistician is the definition of sample size which involves several factors that influence the size of the study, timelines and budget requirements. 

Therefore, how well do you really understand these concepts when it comes to evaluating clinical research results?

CROS Academy's Course: "Understanding the Statistical Elements of a Study Protocol - for Non-Statisticians"
CROS Academy is hosting two courses on introducing the statistical elements of a study protocol to non-statisticians. This course is offered to clinical trial professionals who wish to comprehend the role of statistics and statisticians in clinical research. The course aims to enhance one's understanding of basic statistical principles as well as the statistician's view on clinical trial aspects.

Course dates:
26 November 2014 in Paris, France - Download the brochure
01 December 2014 in London, UK - Download the brochure

Friday, August 29, 2014

Interview ICT: CROS NT Discusses European Clinical Data Transparency Legislation

CROS NT's Global Head of Business Development & Marketing, Chris Hamilton, was recently interviewed by International Clinical Trials magazine regarding the European legislation on clinical data transparency, its implications and how to prepare. 

ICT: New European legislation in 2016 will require summaries of trials to be made public - what will change?

Chris Hamilton (CH): There is already a register of all clinical trials, but new draft European law mandates the publication, via a publicly accessible database set up by the EMA, of summaries of trials that have reached marketing authorisation. That will give very useful information to anyone interested in a particular therapeutic area and indication.

ICT: How is the new system being received by the industry?

CH: Many large pharma companies are already making such summaries available to the public, indicating good acceptance of the initiative. What is more contentious is the promotion of making raw data available, not just the summaries. Some companies have decided to challenge the draft mandate, so it will be interesting to see what happens.

ICT: What do you think the main benefits of greater data transparency will be?

CH: The sharing of information on completed research will be a positive contributor to the overall development of medicinal products by avoiding repetition of similar studies and generating ideas for product extensions for use in other indications. Initiatives such as the publication or risk management plans will also enhance patient safety.

ICT: What about patient confidentiality and privacy - how can this be protected?

CH: All stakeholders seem committed to ensuring patient confidentiality is protected. This is one of the key topics in debating the requirement to make data, not just summaries, available to the public. I expect that sponsors will need to introduce clear guidelines on how to ensure any possible patient identifiers are removed from trial data prior to publication, while maintaining the traceability of trial results.

ICT: How will the legislation impact sponsors and how should they prepare?

CH: The ultimate aim is to make it mandatory for sponsors to respond to reasonable requests from the public to access the data, not just the final results, collected during clinical trials. Sponsors can prepare by establishing how and when data can be anonymised, and in what format the data needs to be held so it is easily accessible. Identifying resources to prepare the data for the EU portal will also be important.

ICT: You advocate a more centralised approach to data - why?

CH: There are significant efficiencies to be gained by centralising data for a particular product. For example, the re-use of material from one study to the next saves around 30-40% of time and cost for database setup and statistical programming. Utilising the same data collection technologies and maintaining knowledge through team continuity makes studies run more smoothly.

Centralising data also allows you to apply standard formats. Taking this approach continues to facilitate the use of various clinical CROs, but it makes more sense to keep the data with one team.

Companies that plan for a pre-market sale of their compound and intellectual property can be assured of a certain valuea dd if they can show that all the data, analysis and reports on the drug development thus far can be located centrally in a consistent format. 

ICH: Tell us about clinical data visualisation tools and how they fit in.

CH: Clinical data visualisation tools can be an important component for sponsors conducting trials that need to make more informed decisions and make sense of clinical data which could eventually be shared publicly. They can be particularly useful for researchers looking at completed study data.

These tools facilitate drill-down and click-through to multiple levels of detail, allowing for the analysis of specific subsets and subpopulations. They allow researchers to make crucial decisions based on the information and trends revealed. 

As a CRO specialized in biometrics, CROS NT helps companies with their regulatory submissions to the EU and USA by preparing their clinical data in a reliable and traceable way. If you'd like more information on centralized biometrics, clinical data transparency or would like to consult one of our experts, please visit our website.