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.

Wednesday, August 20, 2014

Implementing Smart Clinical Data Strategies for Timely Post-Market Studies

Regulatory authorities such as the FDA and EMA are increasingly stressing the importance of timely post-market studies in order to determine the safety and efficacy of drugs already on the market in order to update drug labelling if necessary.

In the medical device sector, regulatory authorities are putting pressure on companies to prove the safety of a device in use and are requiring more post-market study data. In particularly in the EU, in an effort to guarantee patient safety, more PMCF (Post-Market Clinical Follow-up) studies and safety surveillance has been proposed including harmonization among EU member states in terms of market surveillance.

Therefore, how can companies conduct their post-market studies in a cost-effective manner while meeting the "timely" demands of regulatory authorities?

CROS NT suggests effective techniques for managing your post-market study data that will guarantee cost control, efficiency and regulatory compliance:

1. Implementing data management strategies for the management of vast amounts of data from large patient populations.
The use of a Global Library can significantly reduce DM costs by re-using forms - cost reductions of up to 50% if implementing the centralized biometrics outsourcing model. This guarantees a uniform traceability of data, better preparation of data traceability, due diligence ready datasets and documentation and one single Project Manager.

2. Implementing and/or Mapping to CDISC standards for regulatory acceptance.
It is important to start implementing CDISC standards during data collection by having Data Managers design the CRF using CDASH standards. This makes the the process of mapping data into SDTM and ADaM datasets much more straightforward. Identifying the right process for implementation and choosing the appropriate technology can reduce the costs of adopting these standards.

3. Implementing technology solutions such as eClinical platforms with EDC/ePRO/IWRS/CTMS in order to collect and analyze data in real time
Biostatisticians need to be able to make crucial and informed decisions. An eClinical, cloud-based solution allows for real-time study management, access to data from any device and flexibility of contracted resources. Using the same ePRO/EDC/IWRS reduces set-up, training and HelpDesk costs and allows for easy data integration.

With cloud-based eClinical applications, key performance indicators and the creation of clear Service Level Agreements with CROs becomes more achievable.

4. Implementing clinical data visualization tools that allow Sponsors to make sense of clinical data immediately.
The return on investment from the implementation of data visualization tools is the amount of time saved by being able to access and analyze data immediately and using that data to identify and fix problems.

Business Intelligence tools are the best technology option for Data Visualization, especially if implementing a Risk-Based Monitoring approach. They allow for data retrieval, report development from different data sources, report delivery and cloud-based technology. Web-based applications can be accessed from various devices including PC/laptops, smartphones and tablets.

Have an upcoming post-market study in the drug or device development cycle? Contact CROS NT for clinical data and technology solutions that fit your study and budget needs.


Monday, August 11, 2014

Statistical and Technology Solutions for Streamlining Orthopedic Device Trials

According to a recent report (Millennium Research Group), the orthopedic device market is growing steadily, and this is due to several changing factors in the industry. There has been a significant increase in devices for the treatment of extremities including devices for hands, wrists, elbows, shoulders, feet and ankles. This market change is due to both an aging population that is still physically active and an increase in the number of sports related injuries. 

What does this mean for device development and clinical trials?
Orthopedic device development is a rather saturated market, however device companies have the opportunity to develop new devices to meet market demand and streamline trial costs for more "mature" products such as hip implants through a clinical trial strategy that combines smart trial design and integrated technology. 

Combining the right statistical solutions with an eClinical platform can result in up to 20-30% cost savings.

Statistical Solutions
Reducing uncertainty in the planning phases of orthopedic device development can eventually reduce timelines, and inevitably costs. Statistical methods in device studies test for proof of safety and efficacy and also an estimation of effects.

Involving an expert biostatistician from the beginning can help with the protocol development and study design, especially in the areas of adaptive trial design. Since statisticians in orthopedic device trials must balance potentially expensive products, long follow-up periods, possibly large sample sizes, and unique endpoints, adaptive trial design can help account for these changes. The FDA accepts the use of Bayesian design in medical device trials since it combines data from previous studies and the ongoing study to make changes to the study if necessary which can reduce timelines.

Clinical trial managers should also consider the following:
  • Smart Trial Design & Methodology including solutions for adaptive trial designs: adaptive design in orthopedic trials allow statisticians to make mid-course corrections, include fewer patients if possible and reduce timelines.
  • Consultancy from statisticians experienced in medical device trials for power/sample size calculations and specific analyses for orthopedic implant studies: composite endpoints, pain assessments, radiographic data and QoL measures
  • CDISC compliant datasets: consider that the FDA will soon require CDISC-compliant datasets; meaning the statisticians need to be expert in these standards
Integrated, Cloud-Based Technology
To reduce costs in orthopedic device development, an integrated eClinical platform can provide immediate feedback, more accessible trial information and higher data quality. It can facilitate an adaptive approach, or in the case of a trial that is showing a negative trend, it can allow early termination, thereby reducing the risk to patients and reducing the cost of the trial.

An integrated platform that bundles EDC/ePRO/IWRS/CTMS in the cloud provides the following benefits:
  • Sponsors can negotiate enforceable expectations for clinical data entry into the eClinical application
  • Move away from time based unit of measurements to activity-based measurements
  • Standard ad hoc reports
  • Industry and regulatory compliant archival records
CROS NT has expertise in conducting medical device trials in both the US and Europe and has represented many companies on regulatory panels. We have particular expertise in orthopedic and implant studies and have completed more than 60 studies in just the past 5 years including successful submissions in the treatment of knee pain, heel pain, THR, hip resurfacing, cartilage replacement, fusion products, artificial discs and bone growth simulators. We have also been involved in several non-inferiority trials for the lumbar and cervical spine. We have expert biostatisticians with over 25 years of experience in the medical device field with a track record of FDA panel representation for medical device submissions and proven expertise in adaptive trial design.

CROS NT joined the DATATRAK Partner Connect Program in 2013 to provide an eClinical platform with EDC/ePRO/IWRS/CTMS to reduce study costs and improve the device development process. 


Monday, July 28, 2014

CROS NT Releases Autumn 2014 CROS Academy Course Schedule

CROS NT is pleased to announce our course and webinar schedule for CROS Academy for this autumn. We are bringing back our classic course list and adding one new city to our schedule.

CROS Academy also offers in-house, tailored trainings for companies who have specific training needs or want to provide training for a large group of people.



CROS Academy Autumn/Fall 2014 Schedule

23 September 2014 | Webinar
Statistical Considerations in Oncology Part I: Requirements for Successful Phase I and II Studies

Oncology is a main area of focus for many pharmaceutical and biotechnology companies around the world. Cancer claims more than 7 million lives a year and has over 450 indications. This two-part webinar describes why oncology is a unique area and the statistical methods best suited for these trials.

Part I covers Phase I and II product development which lays the foundation for successful Phase III studies. Particularly in oncology, the heterogeneity of the disease can influence the planning of clinical trials.

Register Here

30 September 2014 | Webinar
Statistical Considerations in Oncology Part II: Statistical Methods for Early Decisions in Phases II and III

During Phase III development, efficacy of the drug should be confirmed. Many new products have to find a very specific mechanism of effectiveness, so therefore subpopulations are necessary. Flexible study designs that allow early termination and the use of fewer patients can be a successful solution for determining clinical efficacy. The advantages and disadvantages of flexible designs will be discussed in Part II. 

Register Here

9 October 2014 | Copenhagen, Denmark | Course
Introduction to Adaptive Trial Design

Adaptive Trial Designs offer greater flexibility and the possibility to modify a study in progress based on new information derived from accumulated data. Participants will learn the adaptations possible in a trial, the potential risks and benefits of adaptive trials and conduct a hands-on exercise.

Course brochure and registration link coming soon.

28 October 2014 | Paris, France | Course
Understanding the Statistical Elements of a Study Protocol - for Non-Statisticians

This course is offered to clinical trial professionals who wish to comprehend the roles of statistics and statisticians in clinical trials. The course aim is to enhance one's understanding of basic statistical principles as well as the statistician's view on clinical trial aspects.

Course brochure and registration link coming soon.

29 October 2014 | Paris, France | Course
Introduction to Adaptive Trial Design 

See description above. A discount is offered to participants who register for both Paris courses.
Course brochure and registration link coming soon.

12 November 2014 | London, UK | Course
Understanding the Statistical Elements of a Study Protocol - for Non-Statisticians

Course brochure and registration link coming soon.

13 November 2014 | London, UK | Course
Introduction to Adaptive Trial Design 

See description above. A discount is offered to participants who register for both London courses.
Course brochure and registration link coming soon.

Tuesday, July 22, 2014

Strategies for Reducing Clinical Data Management Costs Without Sacrificing Quality

Clinical Data Management has certainly evolved over the years to reflect the changing clinical trials landscape. Pharmaceutical, biotechnology and medical device companies rely on various outsourcing methods to carry out data management activities such as putting a Functional Service Provider (FSP) team in place for product-specific work, outsourcing to low-cost countries or centralizing biometrics to ensure quality and traceability. With the advancement of technology, there are also various data collection, reporting and visualization systems to consider. Sponsors need to find cost-effective ways to manage vast amounts of data in a traceable and transparent way

The key to any successful project is effective planning. Due to increased requirements by regulatory authorities and new legislation, such as the EMA's upcoming clinical data transparency law, the Clinical Data Manager has more of a stake in the requirements for data collection, data accuracy and quality.

Moreover, when it comes to your clinical data management activities, how do you evaluate quality vs. cost? CROS NT discusses cost reduction strategies for clinical data management that still ensure top quality clinical data.

Consulting a CRO with Global Libraries. The use of a Global Library can significantly reduce DM costs by re-using forms - cost reductions of up to 50% if implementing the centralized biometrics outsourcing model. In EDC studies, Sponsors can save 40-45% on second and subsequent studies in database setup, reuse of forms from the library and training costs.

This method guarantees a uniform traceability of data, better preparation for the EMA's transparency initiative, due diligence ready datasets and documentation and one single Project Manager.

CDISC Implementation. Adopting and implementing CDISC standards can increase drug development analysis costs. However, identifying the right process for implementation and choosing the appropriate technology can reduce the costs of adopting these standards, making it a very worthwhile investment in the medium to long term. Conversion to CDISC standards generally includes SDTM (Study Data Tabulation Model), ADaM (Analysis Data Model) and CDASH (Clinical Data Acquisition Standards Harmonization). 

It is important to start implementing CDISC standards during data collection by having Data Managers design the CRF using CDASH standards. This makes the process of mapping data into SDTM and ADaM datasets much more straightforward. 

Consult your Data Manager on EDC. 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. The availability of cost-effective, open source or proprietary EDC applications for individual physicians/researchers, departments and institutions has the potential to improve clinical and research activities. Cost is an important, if not the most important, factor to be considered while choosing an EDC system. Although the nature of licensing and support required to maintain EDC systems are the main predictors of cost, data capture and workflow at the site implementation also have a major influence.

Introducing FSP 2.0 - If the FSP model is your outsourcing method of choice, consider a new and improved model that deals with the negative effects regarding staff retention and dedication. CROS NT's "next-generation FSP" solution can put together a DM team that controls costs by significantly lowering staff turnover, guaranteeing coverage of sick days and holidays and eliminating the "silo" effect.

If you'd like to evaluate your upcoming data management needs, schedule a meeting with CROS NT to decide which outsourcing strategy is best and how we can reduce DM costs. CROS NT has over 20 years of clinical data management experience, managing more than 1,000 studies with resources worldwide. We are also a CDISC Gold Member and can consult on the implementation of these data standards. 

Tuesday, July 1, 2014

The Approaches of Successful Sample Size Calculation

In an extract from our CROS Academy course: "Understanding Study Designs & Successful Sample Size Calculation", we discuss the different approaches to sample size calculation and why it is an important statistical component in successful clinical trial methodology and strategy.

The target of drug development is to license a drug for a particular disease which is beneficial to all patients and bears a minimal risk on a patient's health. That being said, the drug development cycle consists of a pre-clinical phase followed by Phases I through IV, and each phase has its own population characteristics and defined endpoints. The target populations are as follows:
  • Pre-clinical Phase: vitro- and animal testing to test for kinetics, toxicity and carcinogenicity
  • Phase I: Phase Ia looks for healthy volunteers, while Phase Ib looks for diseased patients with a sample size of approximately less than 10 per dose level to determine the highest possible dose with an "acceptable" rate of dose-limiting toxicity
  • Phase II: Restricted diseased patient population with a sample size of approximately 30-100 per dose level to examine the preliminary evidence of efficacy
  • Phase III: Unrestricted diseased patient population with a sample size of over 100 in order to confirm efficacy
  • Phase IV/Post-market: Unrestricted diseased patient population with a wide variety of medical conditions; with a sample size of usually between 300-10,000 to monitor the safety of a drug once it is released on the market.
There are two approaches to sample size calculation: the precision-based approach and the power-based approach. 

The precision-based approach estimates an unknown parameter with a certain precision. This approach limits the confidence interval of the parameter to a certain width. 

In the power-based approach, the target is to reject a Null-hypothesis with certain error probabilities. This approach is related to hypothesis testing. The necessary assumptions provided include the level of significance and power, standard deviation, clinically relevant significance and the effect size. 

The power-based approach is also used for time-to-event data such as "survival" time (time) or "failure" and "censored" (event). In the case of time-to-event data, the Kaplan-Meier method estimates survival time and log-rank-test can be used where the sample size is calculated in two steps: determining the number of events needed, and then determining the number of patients needed.

It should be noted that the following practical considerations have an effect on sample size:
  • Type I and Type II error
  • Variability of data
  • Effect size
The determination of sample size is critical in the planning and success of clinical trials, however sample size formulas exist for many situations. In complex situations, sample size can also be determined by simulation. Sample size calculation is always based on assumptions about real effect sizes and variation of the data, therefore it is important to get as realistic assumptions as possible. CROS NT biostatisticians recommend calculating sample size under different assumptions as well as in a conservative manner.

CROS Academy Biostatistics Courses
CROS Academy offers biostatistics courses taught by our expert biostatisticians. We organize courses periodically in various cities throughout Europe or the U.S., however we also offer in-house, tailored courses based on company requests. Our current list of courses includes:
  • Understanding Study Designs & Successful Sample Size Estimation
  • Understanding the Statistical Elements of a Study Protocol - for Non-Statisticians
  • Introduction to Adaptive Trial Design
  • Statistical Considerations for Oncology Trials (Early and Late Phases)



Tuesday, June 24, 2014

The Advantages and Disadvantages of Endpoints in Oncology Trials

In this week's blog post, we look at an extract from an article written by CROS NT's expert biostatistician, Thomas Zwingers, on adaptive trial design for oncology studies. How can biostatisticians use adaptive trial designs to deal with the advantages and disadvantages of endpoints in oncology studies?

Oncology is significantly different than other therapeutic areas. One contributing factor is the long timelines to reach clinical endpoints. The ultimate endpoint for registration of a new drug is still the "Overall Survival Time". Surrogate endpoints like "response rates" or "time to progression" are often used but mostly as secondary endpoints or in earlier phases of the development process.

Let's look at the advantages and disadvantages of these endpoints:
  • Overall Survival: the advantages are that is it universally accepted as a direct measure of benefit and easily measured, however its disadvantages are that it usually involves larger studies, may be affected by crossover therapy and sequential therapy and includes non-cancer deaths.
  • Disease-Free Survival or Progression-Free Survival: The advantage to this endpoint is that it usually requires a smaller sample size and shorter follow-up compared to survival studies. However, this endpoint is not statistically validated as a surrogate for survival in all settings, and definitions may vary among studies.
  • Time to Progression: The advantages to TTP endpoints are that they usually require a smaller sample size and shorter follow-up and they are not affected by crossover or subsequent therapies. Like the above-mentioned endpoint, TTP is not statistically validated as a surrogate for survival. Additionally, it is not precisely measured and is subject to assessment bias particularly in open-label studies. Definitions may also vary among studies.
The long time period before any conclusion from the study can be drawn is the main reason for the use of adaptive designs in the this setting. Adaptive designs enable researchers to make early decisions on interim analyses on one or more of the following issues:
  • Early stopping
  • Adjustment of sample size
  • Treatment selection
  • Change of observation time
  • Change of test statistic
In Phase III trials, or even Phase IIb trials, the main accepted endpoints usually need a long time before they can be evaluated. Implementing a Seamless Phase II/III adaptive design can minimize time and save costs in terms of patient enrollment. 

To request the full article "Adaptive Trials in Oncology: Part III Adaptive Designs for Successful Late Phase Oncology Trials", or to request the full article series, send an email to info@crosnt.com.