New Infographic: Why choose open-source EDC?

May 3, 2013 by Clinovo    No Comments    Posted under: EDC, New Technologies, Trends

This infographic is a visual and appealing way to understand why open-source Electronic Data Capture (EDC) is an alternative of choice to proprietary systems or paper-based studies. Do you own a website, a forum or a blog on clinical trials or Electronic Data Capture (EDC) ? You are invited to share this infographic  with your readers! How? Simply copy this code to your page: <a href=”http://blog.clinovo.com/new-infographic-why-choose-open-source-edc/”><img alt=”Infographic: Why choose open-source EDC?” choose=”open-source=” src=”http://blog.clinovo.com/wp-content/uploads/2013/05/infographic-2-resized.png” style=”height: 1817px; width: 675px;” why=”" /></a>[Source: <a href="http://blog.clinovo.com" title="Infographic: Why choose open-source EDC?">eClinical Trends by Clinovo</a>]

Challenges and benefits of EDC adoption

Apr 26, 2013 by Clinovo    No Comments    Posted under: EDC, Trends

Clinical research is one of the most expensive areas of drug development. Bringing an approved new drug from initial private investment to a patient takes over 13 years and $1.3 billion, or an average of $146 million per year.¹

Industry data shows clinical trials costs are growing across all development phases. A 2011 report, Clinical Operations: Benchmarking Per-Patient Costs, Staffing and Adaptive Design by Cutting Edge Information, tracked costs for 100 trials across multiple therapeutic areas finding that per-patient clinical trial costs rose an average 70% from 2008 to 2011.² The largest increases occurred in Phase IIIa and Phase IIIb. Phase I trials are also suffering from cost inflation, with per-patient costs increasing by an average 46% over the same time period.³

Electronic Data Capture (EDC), which collects clinical trial data electronically rather than on paper, is becoming an increasingly popular solution for streamlining data processing. This white paper will review benefits that EDC brings, extending beyond, and contributing to, cost-efficiency. It will also discuss challenges and limitations that sponsor companies can expect when implementing EDC solutions in clinical research.

Key benefits of Electronic Data Capture

1. Cost-saving: Forrester Research analyzed cost-savings to Novartis, which has utilized a customized open-source EDC system for over 400 clinical trials. For a 12-month Phase II clinical trial with 20 sites and 10 patients per site, the operational savings were substantial: $347,600.⁴

Figure 1. Forrester Research Paper versus EDC cost comparison.⁵

The cost of the clinical trial was reduced from $732,000 to $384,000 thanks to remote monitoring, fewer site visits, shorter patient recruitment times, reduction (or elimination) of printing costs, faster data entry, and lower data cleaning costs.⁶ Visit-related costs were reduced by 50%, data cleaning costs by 80%, and all other operational expenses by 32%.⁷

Overall, Novartis claimed a savings of approximately $17 million by no longer needing to print CRFs on NCR paper, a necessity in paper-based trials, which represented $42,500 per Novartis study analyzed.⁸ If we consider that printing costs run as high as $100 per casebook, a study with 500 patients would cost up to an estimated $50,000 prior to factoring in staffing costs for casebook preparation, without accounting for shipping.

2. Time-saving: Single data entry—which replaces the completion of paper CRFs followed by double data entry—remote monitoring, and reduction in the number of queries each save a considerable amount of time. Overall, they have been calculated to reduce the duration of clinical development by up to 30%.⁹

It is critical to note that the most significant time-savings occur during database lock. It has been shown that, when it is time for database lock, there is less missing data and fewer errors and queries with EDC than with paper-based systems. As shown in the table below, database lock can take as long as nine days with paper, whereas database lock is performed in only one day with an EDC system.

Figure 2. Time savings.

3. Cleaner data and reduced queries: EDC adoption leads to a dramatic reduction in the types of data errors found in paper-based CRF studies, such as out-of-range values and missing data. In addition, errors can be detected and corrected much earlier in the clinical trial with EDC than with paper-based systems that can only rely on ad hoc mid-study analysis. EDC edit checks are automatic and visible at the time of entry and are therefore resolved immediately, resulting in cleaner data at time of entry in database.

A case study led by Applied Clinical Trials compared a paper query management system with an EDC system using edit checks and found a 65% reduction in the number of queries.¹⁰

Figure 3. Reduction of the number of queries.¹¹

4. Traceability: Title 21 Code of Federal Regulations Part 11 (21 CFR Part 11) is the United States Federal Regulation which applies to electronic records and electronic signatures in clinical systems.¹² EDC systems must track all data changes in audit trails in order to be 21 CFR Part 11 compliant. Vendors must also plan for disaster recovery and analyze and remedy potential risks. It is critical to note that answering FDA reviewers’ questions is made easier by EDC systems as they can track any changes automatically.

5. Simplified monitoring: Remote monitoring enabled by EDC systems drastically lowers the cost of monitor visits. EDC enables early identification of discrepancies or data entry errors, minimizing the time spent by monitors at sites. Estimating that a visit can cost up to $3,000, the total savings for a study with 20 sites can reach $60,000.

6. Reduced data entry: With paper-based systems, clinical data must first be written on paper and then double-data entered into a central system, which is a time-consuming and error-prone process. Electronic Data Capture’s Impact on Late Phase Research by Dr. Hugh P. Levaux claims that, when considering manual double-data entry costs can be as high as $3 per page, a 100-page casebook can cost as much as $300. These figures translate to a cost of $150,000 for a 500-patient study.¹³ EDC applications necessitate only single-data entry since data entry occurs directly at the site and is the equivalent of CRF completion on paper.

7. Reactivity: Some EDC systems provide real-time alerts and reports, giving decision makers instant access to critical data. ClinCapture by Clinovo recently introduced LiveReports^TM to provide a real-time overview of the clinical trial. Real-time reports enable decision makers to be more proactive in identifying bottlenecks such as late sites, and to be more reactive to data to ensure patient safety.

Ultimately, EDC systems enable sponsors to make efficacy and/or safety determinations earlier in the drug development process. EDC enables pharmaceutical, biotechnology, and medical device industries to focus on the development of the best drug, biologic, or device candidates that will most benefit patients, saving time and millions of dollars in drug development.

8. Reusability: A characteristic of EDC is the ability to reuse the system in future studies which lowers the cost of EDC adoption in the long run. Once forms and their associated edit checks are created, they can be stored in a library and reused for an infinite number of studies. In a case study from Clinovo, a leading global technology medical device company was looking to efficiently manage large amounts of data while staying on-time and on-budget.¹⁴ Clinovo trained the sponsor’s staff to build its studies on the open-source EDC system ClinCapture, enabling the sponsor to customize the ClinCapture platform and roll out nine additional studies themselves. In addition, the sponsor was able to host the system in-house, thereby avoiding vendor lock-in and retaining full control over their clinical data.

9. Mid-study changes: EDC systems make mid-study changes such as the addition of new fields in a Case Report Form (CRF) much smoother than do paper-based studies. Some EDC systems support CRF versioning to automatically update all CRFs in selected sites in just a few seconds.

10. Patient Safety: Improved data quality, better reactivity, and reduction in study time themselves contribute to the faster delivery of better medications. Some specific EDC features have an even bigger impact: faster notification of adverse events, for example, can help with earlier and better decision-making, potentially saving hundreds or thousands of patients from exposure to unsafe medication.

Limits and difficulties of EDC adoption

Despite the tangible benefits of Electronic Data Capture, the adoption of EDC systems has remained slow in some segments of clinical research. Only 40% of Phase I clinical trials had adopted EDC by the end of 2012.

Clinical trial experts suggest this slow adoption is explained by the high cost of proprietary EDC systems and by the structural changes and learning curves incurred by sponsor companies when implementing an EDC system. Some attribute low adoption rates to negative impressions of early EDC systems based on poor design and limited performance.

There is a common perception that paper-based studies are faster and less expensive to implement than are EDC studies. It is undoubtedly true that studies can be started faster on paper. But data shows that their overall duration is as much as 30% longer on average.¹⁵

EDC vendors are making an effort to minimize the study-build time by leveraging reusability and automation. It is now possible to deploy a full EDC study in days rather than the weeks or months historically, assuming study form reusability.

The initial cost of EDC is also a major determent to its adoption, especially for preclinical or Phase I trials with lower budgets. The most significant costs are incurred when hiring vendor(s), assigning clinical and data management experts to interface with programmers, and setting up internal computer systems, including the purchase of hardware and software. Following these initial setup phases, subsequent study costs for each new clinical trial can become marginal, leaving mostly fixed annual fees for system maintenance, including optional hosting fees.

Finally, data privacy and security is also a major concern among trial investigators. A study by Silico Research shows that investigators cite security and confidentiality as key concerns when conducting EDC-based clinical trials.¹⁶ It is essential to select EDC vendors who thoroughly follow regulations and offer secure hosting services with data redundancy ensuring full disaster recovery.

Figure 4. Trial investigators concerns on EDC-based clinical trials.¹⁷

Among other concerns, sponsors also worry about the steep learning curve and heavy training needed to switch to an EDC system. The implementation of an EDC system drastically changes the structure and the processes within a sponsor organization. EDC vendors are aware of these difficulties and are focusing on improving EDC systems’ ease-of-use. Vendors are also putting an emphasis on training sessions for end users as well as on ensuring reactive support services.

Moreover, one can observe standardization in the user interface guided by consensus-based collaborative standards like CDISC/CDASH, allowing for consistent user experience across vendors and studies and thereby requiring less training to adapt to new study screens.

Conclusion: Planning EDC deployment, a key success factor

A potential steep learning curve for clinical research teams, structural changes in organizations, and perceived high cost of EDC implementation are some of the legitimate reasons to hesitate before adopting EDC. However, considerable time- and cost-savings, along with drastic data quality improvement outweigh these difficulties.

It is necessary for sponsors to put controls in place to ensure data quality and integrity throughout their clinical trials. This can and is done with paper-based clinical studies, but often with unintended negative consequences, including delay and looping in the data entry process. With EDC, edit checks are integrated from the start and are seamlessly activated during data entry, ensuring that the sites, which are responsible for providing study data, can address most issues on the spot.

In order to fully benefit from EDC systems, it is critical for sponsors to plan ahead. Most importantly, planning must be carried out prior to study build. Data entry screens, online edit check specifications, and the annotated case report form (aCRF) must be implemented before the study goes live.

Though the process changes as it evolves, Electronic Data Capture brings complete and up-front integration of the trial design and setup to the different operational groups involved, including Clinical Operations, Clinical Data Management, and Biostatistics, thus ensuring not only that the data entry process is easy and well-customized for the clinical sites, but also that the final database exports will be fully compliant and meet analysis requirements.

Olivier Roth, Marketing and Communication Coordinator, Clinovo

References

1. Herper, M. The Truly Staggering Cost of Inventing New Drugs. Forbes website. http://www.forbes.com/sites/matthewherper/2012/02/10/the-truly-staggering-cost-of-inventing-new-drugs/. February 2012. Accessed April 9, 2013.
2. Per-Patient Clinical Trial Costs Rise 70% in Three Years. Cutting Edge Information website. http://www.cuttingedgeinfo.com/2011/per-patient-clinical-trial-costs/. July 2011. Accessed April 8, 2013.
3. Ibid.
4. Peachey J, Spink C, Fraser H, Henderson S. The eClinical equation: Part 1: Electronic Data Capture. IBM Global Business Services: IBM Institute for Business Value. 2005; 3. http://www-05.ibm.com/de/healthcare/literature/eclinical-equation-1-lang.pdf. Accessed April 8, 2013.
5. Ibid.
6. Ibid.
7. Ibid.
8. Ibid, 3-4.
9. Green, J. Realising the value proposition of EDC. Innovations in Clinical Trials. September 2003; 13. http://www.iptonline.com/articles/public/ICTTWO12NoPrint.pdf. Accessed April 8, 2013.
10. Mitchel J, You J, Lau A, Kim Y. Paper vs. Web: A Tale of Three Trials. Applied Clinical Trials: Internet Insight Section. August 2001; 1. http://www.medchannels.com/pdfs/whitepapers/ACTArticle.pdf. Accessed April 8, 2013.
11. Ibid.
12. Part 11, Electronic Records; Electronic Signatures – Scope and Application. U.S. Food and Drug Administration website. http://www.fda.gov/regulatoryinformation/guidances/ucm125067.htm. March 23, 2009. Accessed April 9, 2013.
13. Levaux, H. Electronic Data Capture’s Impact on Late Phase Research. Business Briefing: Pharmatech. 2004. http://www.touchbriefings.com/pdf/890/PT04_Ninaza.pdf. Accessed April 8, 2013.
14. Clinovo Case Study: Open Source EDC Unmatched Cost-efficiency. Clinovo website. August 28, 2012. http://www.clinovo.com/userfiles/clinovo-open-source-edc-unmatched-cost-efficiency.pdf. Accessed April 8, 2013.
15. Green, J. Realising the value proposition of EDC. Innovations in Clinical Trials. September 2003; 13. http://www.iptonline.com/articles/public/ICTTWO12NoPrint.pdf. Accessed April 8, 2013.
16. Peachey J, et al. The eClinical equation: Part 1: Electronic Data Capture. IBM Global Business Services: IBM Institute for Business Value.  2005; 9. http://www-05.ibm.com/de/healthcare/literature/eclinical-equation-1-lang.pdf. Accessed April 8, 2013.
17. Ibid.

Thank you Note

• Jean Maupas, Director of Operations, Clinovo
• Dave Alderson, Senior Director of Sales, Clinovo
• Anil Kishan, Marketing Assistant, Clinovo
• Maxwell Love, Business Development, Clinovo

2012: A Year in review in the life science industry

Jan 8, 2013 by Clinovo    No Comments    Posted under: Best-Practices, Trends

2012 was a good year for the life science industry, with a 7% growth in R&D pipelines and 35 new drugs approved by the FDA, delivering some truly innovative, needed therapies. Challenges faced include the feared patent cliff as well as passing of the medical device tax set forward in 2010.

FDA Approvals

This year, the FDA approved 35 new drugs during the fiscal year, which ran from October 1, 2011 to September 30, 2012. The approval rate in 2012 matched that of 2011, both reaching higher rates than previously seen.

Many of these new drugs are successfully going through the review process as they are addressing unmet needs for deadly diseases. Additionally, the FDA met their deadlines 34 of 35 times, surpassing their PDUFA goal of 90%. Since the close of the fiscal year, no less than 3 new drugs have already been approved.

However, the Sequester may affect the FDA approval rates and goals. The Sequester, passed in August 2011 as part of the Budget Control Act (BCA), is a package of automatic spending cuts projected to total $1.2 trillion, scheduled to begin in 2013 and end in 2021. Part of these automatic spending cuts will be geared towards FDA budgets, which could be forced to slash jobs and thus lose some of its capacity to approve drugs for 2013.

Top Blockbusters

On the basis of third-quarter earnings, Ernst & Young estimates combined sales at the global top 13 drug companies dropped by close to 4% this year from about $557 billion in 2011.

With the patent cliff taking its toll on some of the best selling drugs ever known to our industry, the biggest blockbuster of 2012 is Humira from Abbott Laboratories, totaling $9.48B. Initially approved for the treatment of rheumatoid arthritis, the money maker is drawing on the expanded treatment of 5 additional indications. In total, the top 15 selling drugs generated $95.55B in revenue (and counting).

In addition, 6 companies found themselves in the Top 10 most charitable organizations over the last year. Taking the top spot was Pfizer with over $3.06B in cash and products donated. Merck (#3), Abbott Laboratories (#7), Johnson & Johnson (#8), Eliy Lilly (#9), and Bristol Meyers Squibb (#10) round out the list with all 6 companies donations totaling $6.9B.

The Patent Cliff

The patent cliff has taken a large effect this year, and by 2015 will have an estimated $250B in lost sales for the industry. The once mighty Lipitor has fallen from the top spot to number 10 this year, with a 42% sales drop in the first quarter of 2012. Four other best-sellers lost patent protection this year as well, affecting $22.8B worth of retail sales for 2012.

Capital Market and Merger And Acquisitions (M&As)

As of the third quarter 2012, 14 U.S. life sciences companies completed IPOs, raising almost $950 million. Twelve of the 14 U.S. companies are in drug discovery and development, and California companies account for half of the IPOs in 2012.

The $146B M&A market this year found some much watched participants, including the acquisition of Human Genome Sciences by GlaxoSmithKline. However, overall M&A fell by 35% in 2012, down $79B from last year. According to the 2013 Baybio 2013 California Biomedical annual report, As of November 2012, 53 M&A transactions were recorded of California companies of which 33 were biopharmaceutical, 18 diagnostics and two R&D companies. The top M&A deal was the acquisition of Amylin Pharmaceuticals for $10.6 billion by Bristol-Myers Squibb in collaboration with AstraZeneca.

According to sources, multi-billion-dollar acquisitions were outnumbered by more modest research pacts and partnerships in which drug companies acted to add promising compounds to their pipelines. The early weeks of 2012 brought a flurry of research pacts focused on oncology, typical of a more targeted approach. Takeda Pharmaceuticals, Merck & Co., Eli Lilly & Co., and AstraZeneca all gained access to compounds that biotech firms were developing for cancer.

Investments

Overall, U.S. life sciences (biotechnology and medical devices) investment for the first three quarters of 2012 is down 19 percent in dollars and 12 percent in deals from the same time period in 2011.

Investments in emerging markets increased by 65% this year, reaching a total of $20B, with China as leader of the pack. While the US will remain the largest market, China’s growth of 14 – 18% over the next 2 years will give it a firm place at #2.

Market presence is expanding to developing countries due to the need for higher medical demand, use of generics, and growing populations. Latin America, North Africa, and other parts of Asia are seeing increased attention from the industry while Brazil, Russia, India and China (BRIC) continue to grow.

Biggest Marketing Settlements

2012 saw 4 of the largest marketing settlements ever handed out to pharma. Not only did it see 4, but they ranked among the first 7, including the #1 spot, totaling $6.462B. The winners, or losers in this case, are GlaxoSmithKline ($3B), Abbott ($1.5B), Johnson & Johnson ($1.2B), and Amgen ($762M). All of the settlements shared a common thread of unlawful promotion with a few having kickbacks as reasons for judgment. The increase in penalties can be related to the Justice Departments continued outrage for misbehaving, going so far as suggest future penalties be given to executives for irresponsible corporate behavior or taking away patent rights.

This year also saw the banning of pay-for-delay deals, where brand name drug companies made deals for their generic competitors to delay the release of the competition. The Federal Trade Commission led this mission as these delays cost taxpayers $3.5B a year in higher drug prices, as well as violating trade laws.

Medical Device Tax

Effective January 1^st, 2013, the Medical Device Excise Tax went into effect, generating an expected $29B in revenue over the next 10 years. Part of a 2010 healthcare law, 2012 saw the attempt, and fail, for repeal and has since become finalized by the IRS. The tax, applied to most tools used by medical professionals (including those used for humanitarian efforts), has garnered much criticism with some reflecting that the tax will prevent researchers from innovation, ultimately costing lives for patients who need these tools. As the tax will apply to all companies, regardless of profit, companies have to navigate the new arena for funding, R&D, and expansion. Some companies who will be hit hardest, such as Stryker, have already started reducing costs by reducing work force.

How the medical device tax will affect the industry remains to be seen, as well as the patent cliff. 2013 is projected to be another year of growth with a strong pipeline of potential new blockbusters under development. Will big companies look to acquisition as a way of bolstering their offerings? Will the rising stars, such as Onyx, be purchased by the industry giants? Will Alzheimer’s treatments catch a break? Only time will tell what the future holds.

References

• “Life Science Trends 2012”, Alexander, D., McMerty, B., Frey, K., Waddell, A., Carlyle & Conlan, 2012
• “FY 2012 Innovative Drug Approvals”, U.S. Food and Drug Administration, December 2012
• “Pharma R&D Annual Review 2012”, Llyod, I., citeline, 2012
• “The 15 Most Generous Companies Of The Past Year”, Sprung, S., Business Insider, July 26, 2012
• “The Best Drug Companies Of The Past 15 Years”, Herper, M., Forbes, February 9, 2012
• “Startups struggle with impending device tax”, Garde, D., www.fiercemedicaldevices.com, November 2, 2012
• “These are the top 10 payers of the medical device tax, says Moody’s”, Parmar, A., Med City News, March 8, 2012
• “Pharma’s Top 11 Marketing Settlements”, Staton, T., Palmer, E., www.fiercemedicaldevices.com, June 26, 2012
•  “Beyond the Patent Cliff”, By Rick Mullin, December 10, 2012. http://cen.acs.org/articles/90/i50/Beyond-Patent-Cliff.html
• “The Sequester, explained”, By Suzy Khimm, September 14, 2012. http://www.washingtonpost.com/blogs/wonkblog/wp/2012/09/14/the-sequester-explained/
• “California Biomedical Industry 2013 Report”, By BayBio, CHI and PWC, January 7, 2013. www.CaliforniaBiomedReport.com
• “A Banner Year for New Drugs”, The 2012 Burill Report, http://www.burrillreport.com/article-a_banner_year_for_new_drugs.html
• “Big pharmas eyeing innovative targets”, October 25, 2012. http://www.acquisitionsdaily.com/2012/10/25/big-pharmas-eyeing-innovative-targets/

Contact Information

Sophie McCallum
Marketing Manager at Clinovo
408-773-6258
sophie.mccallum@clinovo.com

Joshua Elvert
Associate, Business Development
408-940-3934
joshua.elvert@clinovo.com

Game-changing predictive solution for clinical research

Oct 4, 2012 by Clinovo    2 Comments    Posted under: Events, Trends

I wanted to share the following article with you, borrowed from the Drug, Discovery & Development online magazine:

Drug development programs today have a 5% to 10% probability of success. Almost half of the failures are due to drug safety issues found very late in the clinical development process. The lack of improvement in outcomes, despite advances in technology and the near doubling of pharmaceutical R&D expenditures, highlights the need for novel approaches to drug development.

Currently, the identification of efficacy and safety risks for a lead compound primarily uses cell line and in vivo studies. Unfortunately, these experimental systems are black boxes that offer limited visibility into selected phenotypes and biomarkers and very little insight into the effects of a compound on important physiological pathways. Due to this lack of transparency into pathway effects, it is difficult to generate insights into system-level changes in the physiological network. This is often a reason for potential oversight of toxicity issues and incorrect assessment of efficacy.

In the era of molecularly targeted drugs that affect specific targets and pathways, developers must have insights into the off-pathway effects of drug candidates. Use of predictive methodologies that emulate human physiology to test the impact of the drug candidate prior to moving the drug into clinical testing is crucial to improve the drug development success rate. By predicting clinical outcomes early on, the success rate of drug development can dramatically be improved.

The development of a predictive system emulating disease physiology is feasible because of the massive amount of published reductionist information on signaling and metabolic pathway components and “omics” data coupled with advances in mathematical techniques and computing power. Coupling the massive library of published data to computing power enables researchers to connect the dots in a way not possible before and, therefore, predict clinical outcomes early on.

Predictive models offer the promise of predicting clinical outcomes early in the development process and give the ability to rationally construct efficacious therapies with lower potential for side effects. The large availability of data and information on the components of the biological networks and interactions has enabled the creation of such systems. This approach provides transparency to manipulate different pathways in the network and assay intermediate and endpoint biomarkers and disease phenotypes. The key criterion for deployment of such an approach is extensive validation of predictions with experimental studies.

About the author - Pradeep Fernandes has a background in semiconductor engineering and has applied the engineering approaches and technologies to create the Cellworks technology platforms. Shireen Vali has a background in molecular and cellular neurobiology and has worked extensively in developing the disease networks underlying complex multi-phenotype disorders.

Olivier ROTH
Marketing & Communication Coordinator at Clinovo

The Changing Role of the Clinical Data Manager (CDM)

Sep 27, 2012 by Clinovo    No Comments    Posted under: Trends

How is the growing adoption of EDC affecting CDMs?  Is processes automation easing or threatening the work of CDMs? How is systems integration changing the required skillsets of CDMs and how to adapt? The Clinical Data Manager today: Emergency-based fireman or provident manager?

The evolution of technologies in clinical trials leads to a redefinition of the CDM role. The fast-pace adoption of EDC systems reduces the overhead of manual cleaning tasks and time-consuming back-and-forths. As a result, CDMs are asked to handle a far greater volume of complex data streams. They are also expected to spot and solve problems at earlier stages, and to collaborate with statisticians and site monitors to set specifications for validation and edit checks prior to data collection.CDMs are becoming a key cross-road and take on the role of information providers in their organization with the sponsor and sites. They need to understand the entire clinical development spectrum and how data fits.

Today, Clinical Data Managers are not only Clinical Data Managers, they can also be projects managers, programmers and in some cases medical managers, quality or regulatory experts. This inflation of competencies lead to the development of a new generation of cross-trained CDMs, eager to match their skillset with the job market expectations. CDMs have been taking on new responsibilities within their organization and benefit from additional professional opportunities.

Do you want to learn more and react on the topic? On October 24th, Clinovo will broadcast a free webinar on the Changing Role of the Clinical Data Manager. This webinar will benefit CDMs but also industry professionals looking for ways to understand and benefit from upcoming trends in the Clinical Data Management field. The presentation will be followed by an open discussion on the topic.

Click here to register now!

Mobile Devices Pave the Path for Clinical Research Evolution

Sep 19, 2012 by Clinovo    No Comments    Posted under: New Technologies, Trends

Clinical trial sponsors looking to stay at the forefront of efficiency and accuracy should consider whether they are making the best use of the growing trend of access to clinical data on mobile devices. From the secure sharing of electronic patient reported outcome (ePRO) data, to creating more flexible clinical data management, mobile technology has the potential to improve processes across the clinical research process. In many cases, sponsors are already seeing the benefits – including real-time alerting capabilities and increased efficiencies – of incorporating mobile technology in their research process.

Real-time results – delivered to the right people at the right moment

Real-time alerting can dramatically improve a trial’s overall success rate. Alerts can be configured to automatically send an email or text message to a mobile device when a pre-specified event occurs, such as when a serious adverse event (SAE) is entered into the system. It is important that alerts notify mobile devices; most people are not always logged into their computer workstation, but many keep their smartphone or tablet close by. This helps ensure that all relevant stakeholders are informed as quickly as possible when their action is required. For example, if a patient in Sweden reports symptoms via their iPad after intake of Drug X, their information can be instantly analyzed in California, where a data manager will be notified that he or she needs to take appropriate next steps, which may include alerting sites across the globe to suspend the use of Drug X. With the use real-time notifications delivered through mobile devices and the ability to act upon this feedback from any web-enabled device, response times can be reduced from days or weeks to hours or minutes, giving clinical teams the opportunity to address problems before they put a study in jeopardy.

Consumer-based efficiency – taking advantage of familiar technology

Increasing trial efficiency and correctness are common requirements for CROs and trial managers when implementing new clinical trial technologies. Luckily, mobile devices and their efficiency benefits can be easily introduced into the research process without costly hardware investments or extensive user training. Most trial participants and managers currently utilize mobile devices in their everyday life, so the functionality is already available. Because participants are using a technology they already understand, it becomes easy for them to enter data directly. In addition, trial participants will be more likely to engage with tools they’re already familiar with, enabling increased accuracy and improved reporting. And because of the connectivity of mobile devices, it is easy for trial managers to retrieve data from patients without costly delays.

Data security concerns – succeed with caution

In order to make mobile capabilities a research reality, we can’t ignore the possibility of security threats and regulatory concerns. However, mobile software can be very secure if written properly, and the clinical trial industry can benefit from the great strides other industries such as online banking have made in mobile security. Similarly, regulatory concerns can also be addressed by ensuring mobile software is fully Title 21 CFR Part 11 compliance. Data security is a risk in any electronic platform, but when addressed carefully, its risks need not outweigh the vast benefits that electronic technologies provide.

Propelling into a mobile-charged future

As the clinical industry becomes more dependent on technology, waiting for results or data batches to be complete will no longer be acceptable or considered the norm. The ability to increase efficiency, analyze live data and implement results immediately demonstrates collectively the key benefits of utilizing mobile devices in clinical trials. Taking advantage of new and innovative technologies is a key to the future of clinical trials, and mobile capabilities will pave the way.

Rick Morrison
CEO, Comprehend Systems

Rick Morrison is the co-founder and chief executive officer of Comprehend Systems. Prior to founding Comprehend Systems, Rick served as the chief technology officer of an internet-based data aggregator, where he was responsible for product development and operations. Rick has over a decade of experience writing software for clinical trials, including tools that are now used by the FDA and top pharma. Rick holds a bachelor’s degree in computer science from Carnegie Mellon University.

Pioneering Cloud Computing for Clinical Trials

Aug 13, 2012 by Clinovo    No Comments    Posted under: New Technologies, Trends

The cloud: A new paradigm

The cloud generated $36.1 billion dollars in 2011 and is expected to reach $72.8 billion by 2015 according to a recent IDC study.  With a CAGR of 21% per year from 2011 to 2015, the cloud is growing three times faster than traditional IT infrastructures. It is nowadays a commonly known revolution, yet very few people grasp the nuances and the potential behind this term. In simple words, the cloud turns everything into easily accessible and affordable services, unleashing unmatched potentials for organizations and individuals.

Defining the Cloud

The cloud is the ability to access value-added services from anywhere at any time with a level of simplicity, flexibility and cost efficiency never met before. The cloud provides on demand access to software/applications, platforms and infrastructures commonly known as:

- Software-as-a-Service (SaaS) such as web hosting services, collaborative or CRM applications such as the well-known Salesforce.com.

- Platform-as-a-Service (PaaS), providing developers the tools to develop their own applications such as databases, operating systems, etc. without any initial costly IT investment in hardware. For example Google’s App Engine is a PaaS enabling developers to create new applications.

- Infrastructure-as-a-Service (IaaS) enables access to computer infrastructures such as servers, data-centers and network equipment, once again without any heavy initial investment. This type of cloud service is often used by organizations that have the IT expertise to manage their IT requirements but not the infrastructure itself. For example, Amazon’s Elastic Compute Cloud (EC2) provides resizable compute capacity to make web-scale computing easier without the need for CAPEX.

Those three categories are called “services” in the sense that users access, subscribe, use, monitor them on an on-demand and pay-as-you-go basis. The user can monitor the Service Level Agreement (SLA) he signed for, submit tickets if necessary, look at its IT usage bill on its own, without any human interaction. The cloud is thus a very automated, elastic and cost-efficient environment.

This level of autonomy is possible thanks to processes automation: Workflows are automatically processed in the cloud without human intervention. The advantage of process automation is cost-efficiency since less IT hours are billed. Today, around 70% of IT budgets are spent on maintaining the infrastructure, leaving only 30% for new projects.  This tends to frustrate departmental managers who see their projected queued, sometimes for years.  The cloud provides an immediate and cost effective solution while empowering these managers.

Clouds rather than Cloud

Traditionally the cloud is split into four types:

Read more about Clinovo cloud-based hosting services

Cloud technology in the life science industry 

Clinical trial professionals already use public clouds but mostly for administrative, IT, marketing or sales purposes (such as Google Drive, any document sharing system or CRM tools) but very few of the cloud services are directly related to life science.

Although cloud-based systems are gaining momentum in almost all the industries, the adoption rates for this innovative technology remain low in the life science industry. Some IT vendors in clinical trials such as Medidata Rave are arguing they are offering cloud services, whereas their services are neither self-service nor on a pay-as-you-go basis.  This is not uncommon; many companies exploit the cloud marketing buzz, yet provide services that are not self-service, automated, flexible nor cost-efficient.

In clinical trials, cloud technologies are a new opportunity to lower skyrocketing costs. Electronic Data Capture (EDC) systems, Clinical Trial Management Systems (CTMS) or ePRO systems would be configured and implemented at a much faster pace and at a much lower cost. In January 2012, Forbes calculated the average cost of bringing a new drug to market at $1.3 billion (at times $4B to $11B for big pharmaceutical companies), this calculation takes failed drug application in account.

Thanks to the always-on and automated properties of the cloud, drug development cost is bound to decrease since clinical trials will be started and ended faster than ever before.

Upcoming challenges

One of the major concerns of pioneering cloud computing for the healthcare industry is compliancy. Pharmaceutical companies must ensure that the cloud service providers they use follow GCP as guided by 21 CFR Part 11 regulation, to ensure the system is fit for its intended use;  including IP/IQ (Installation protocol and qualification), OQ (Operation qualification) and PQ (Performance Qualification).  Here are some tips about validating a clinical application in the cloud:

• You must have an installation protocol to install the application into the cloud; as well as for every minor and major version upgrade.

• In a public cloud you cannot have an installation protocol for installation of the hardware and OS images.  More and more auditors understand and accept this is a limitation of the cloud.  Do check with your QA department, if in doubt.

• You must provide test and production environments for each application in the cloud.

• You must test backup and restore of all production applications.

• It is a good idea to test your disaster recovery procedures.  You may need the cooperation of your cloud provider to simulate a disaster for you.

• Validation of the application must take place in the cloud and you must use the same documentation and methods as if the application was running on a local server.

Since clinical trials are more and more international, there is also a need to ensure that local regulations are followed. For example it is essential to know where the data is hosted. Indeed some countries require the clinical data to be hosted in the actual country of the clinical trial. For example, if a pharmaceutical company runs a clinical trial both in the US and in Japan, the Japanese data must be hosted in Japan. This regulation should be taken in consideration while implementing a global cloud-based clinical system.

Even though the cloud is promising autonomy, flexibility and cost-efficiency for pharmaceutical companies, there is a need for experts to ensure that the transition to cloud-based services for clinical trials is made in a safe and compliant manner. IT and life science are two very different areas of expertise, so it is critical to take the time to choose a vendor that has proved its worth in both area and that can guide you through this new technology.

Ultimately, the cloud technology will revolutionize the healthcare and life science industries, enabling pharmaceutical companies to bring their drug to patients faster at a lower cost.

At Clinovo, we pride ourselves to seek and bring the most innovative technologies and apply them to the life science industry to streamline clinical trials. Our team is composed of experts in both the IT industry and the life science industry

Marc Desgrousilliers, Chief Technology Officer at Clinovo

Olivier Roth, Marketing & Communication Coordinator

Are you prepared for CDISC?

Jul 17, 2012 by Clinovo    No Comments    Posted under: CDISC, Trends

CDISC® (Clinical Data Interchange Standards Consortium) is establishing data standards to speed up data-review and improve clinical data exchange, storage and archival. Today, 60% of FDA submissions are already done in CDISC standards. The FDA is getting more and more involved into CDISC standards, a meaningful signal for the industry. Theresa Mullin, Director of Office of Planning and Informatics within CDER, claimed that “the FDA is committed to using CDISC standards for the foreseeable future”. These data standards are expected to be mandatory by 2016 for every drug submission.

CDISC standards hold the clinical data to a greater level of readability and compliancy in regards to FDA requirements. Carey Smoak, Senior Manager of SAS Programming at Roche Molecular and CDISC Device Team Leader, points out that “a submission without CDISC standards can have a review period twice as long as one under standards”. Indeed, they facilitate the FDA review process since they are known and understood by reviewers.

A 2009 study conducted by Gartner in collaboration with the CDISC organization shows that the overall clinical trial duration is divided by two when using CDISC standards. Thus CDISC standards ultimately speed up time to market.

So if the benefits of using CDISC standards are so obvious, how can we explain that so many sponsor companies are still not adopting them?

Converting legacy data to CDISC standards is expensive

Clinical data standardization is no simple process:  It is time consuming and proves to be tedious. However, a few open source CDISC conversion tools have been launched to address this problem. One successful example is the OpenCDSIC validator software, recognized by the FDA and freely available. CDISC Express, Clinovo’s free SAS-based SDTM mapping tool, has been downloaded 600 times.

In the future, standards can be adopted smoothly if the industry works harder at incorporating them earlier in the process. Indeed, the next challenge is to push CDISC standards upfront in the clinical trial process. CDISC experts agree the best timing to implement CDISC standards is the database built.

CDISC standards are still evolving

Standards are still being built and are in constant evolution. The CDISC organization is still releasing new versions of its clinical standards. Sponsors companies are often scared that if they convert their clinical data to a format, it will be obsolete a year later. Clinical trial experts still state however that sponsor companies should shift to CDISC standards as soon as possible.

Companies often lack the internal expertise

In order to be efficiently used and maintained, Carey Smoak points out that “the wiser choice is to hire people with expertise on CDISC standards”. Companies should educate themselves on this topic and exclusively hire experts from CDISC Registered Solutions Providers organizations.

Ale Gicqueau, CEO at Clinovo

Open Source Technologies for Clinical Trials

May 30, 2012 by Clinovo    No Comments    Posted under: Business Best Practices, EDC, Trends

Clinical trials have become increasingly complex and, as a result, costly. Only 333 drugs and biologics have been approved between 2000 and 2010 due to stricter regulatory procedures while spending has increase by 15 in the same period of time.

The need for innovation is critical in the pharmaceutical and biotechnology industry. Life science companies and service providers are looking for innovative solutions to improve study performance and minimize their risks. This article will demonstrate how open source technology presents an innovative solution to this challenging environment, and ultimately helps bring medical innovations faster to patients.

What is open source? Open source is a type of software license. There are various types of open source licenses, but the common characteristic to all is allowing free distribution of the underlying source code. Famous open source systems include Linux, Apache, MySQL, and many others. Below is a definition of Open-Source Software:

1. Free redistribution
2. Source code
3. Derived works
4. Integrity of the author’s source code
5. No discrimination against persons or groups
6. No discrimination against fields of endeavor
7. Distribution of license
8. License must not be specific to a product
9. License must not restrict other software
10. License must be technology-neutral

Taken from Opensource.org. See http://opensource.org/docs/definition.ph​p for an annotated description of the above points.

Open Source in the Clinical Trial Industry. Two pioneers in open source technology for clinical trials are Cynthia Brandt and Prakash Nadkarni of the YaleCenterfor Medical Informatics, with their TrialDB system (http://ycmi.med.yale.edu/trialdb/), an open-source Clinical Study Data Management System (CSDMS) for the storage and management of clinical data initiated in the 1990’s.

The US National Cancer Institute launched a wide-ranging, open-source friendly initiative named CaBIG (Cancer Biomedical Informatics Grid - https://cabig.nci.nih.gov), that aims to develop a collaborative information network to accelerate the detection, diagnosis, treatment, and prevention of cancer.

Open source software is also used for electronic data capture (OpenClinica, ClinCapture), clinical research (LabKey Server), Electronic health or medical record (OpenEMR), analysis (R project), and CDISC conversion (CDISC Express, OpenCDISC).

Benefits of open source technologies for clinical trials. While open source is prevalent in many industries, this technology is still emerging in the field of clinical trials. The development of open source technology in the clinical arena has been quickly growing. Eric Morrie, Manager for Clinical Programming in one of the worldwide leading medical device companies, shared his extensive experience on open source technologies at a Silicon Valley BioTalks (http://www.clinovo.com/biotalks/open-source/article). Eric explained how open source technologies save time, improve re-usability and simplify the customization of systems to a company’s needs.

• Provide state-of-the-art, cost-effective solutions

Proprietary systems for clinical data management are often too expensive for individual researchers and smaller companies. As a result, they often use slow, error-prone paper-based methods.

Ale Gicqueau, President and CEO of Clinovo, a CRO based in the Bay Area, explains that with open source technologies, the license fee for proprietary systems is no longer a barrier entry for small and mid-size companies (http://www.clinovo.com/biotalks/open-source/article). Open source clinical data management systems save money by eliminating the reliance of using expensive proprietary systems, while insuring the same levels of quality. It provides a means for smaller companies to access high quality technologies for clinical data management and comply with international regulatory standards.

• Avoids the risks of vendor lock-in

Proprietary systems lock a customer into a vendor’s product from which they cannot escape without substantial switching costs. Such dependence includes reliance for maintenance and support, and the necessity to accept version upgrades that the buyer may not need.

Widely adopted open source systems on the other hand have multiple vendors supporting it. Surveys demonstrate that early adopters of open source technologies are driven by the “reduced dependence on software vendors”, often seen as one of the most important advantages of open source technology.

• Enables a larger community to maintain and enhance the source code

The open source model enables quick improvements by giving access to the underlying source code to a large community of talented developers. In the open source community, developers are encouraged to produce derived works to enhance the existing source code.

“The Open Source community attracts very bright, very motivated developers”, explains the UK software consultancy company GB Direct (http://open-source.gbdirect.co.uk/migration/benefit.html). “Highly prized factors are clean design, reliability and maintainability, with adherence to standards and shared community values preeminent.”

A rising trend: Open source for electronic data capture: One of the most famous and number one open source system for clinical trials is OpenClinica, with a community of over 12,000 developers.EDC systems are often prohibitively expensive, ranging in the hundreds of thousands of dollars. As a result, open source technology has been particularly well-received in the field of electronic data capture. Open source EDC platforms deliver the same benefits as proprietary EDC systems but without the license fee.

The one I am most familiar with is an open source EDC system developed by Clinovo : ClinCapture. It is a validated and enhanced version of the #1 open source EDC platform, fully customizable to any clinical study. Learn more

This open source EDC system has been successfully implemented by major pharmaceutical, medical device and biotech companies. Victor Chen, Director of Clinical Affairs at Intuitive Surgical, explains that he decided to use this technology due to the low price and the flexibility that suits adaptive clinical trials. However, he emphasizes on the importance of rigorously assessing any open source system vs. proprietary systems and evaluating the cost for validation. Read case study

The emergence of open source based tools for CDISC: Converting clinical data to the widely recognized CDISC SDTM standard is often done manually, which can quickly become tedious, error-prone, and time-consuming.CDISC SDTM data is the standard format recommended by the FDA for clinical trial data submission. The mission of CDISC is to develop and support global, platform-independent data standards to improve medical research.

Clinovo developed an open-source system to help with this conversion to CDISC SDTM: CDISC Express. CDISC Express is a powerful open source SAS®-based system that automatically converts clinical data into CDISC SDTM using an Excel framework.

The CDISC Express framework is highly extensible. The system significantly speeds-up CDISC SDTM conversion, and has been successfully implemented for major biotechnology and pharmaceutical companies. Download for free

Conclusion: Today, it takes on average 10 to 15 years to develop a drug and costs near $1.2 billion. With only 2 of 10 marketed drugs returning revenues that match or exceed R&D costs, developing medical innovations has become more and more risky. Open source technologies are an innovative way to lower the cost of clinical trials and minimize risk, while ensuring the same level of quality as proprietary systems.

Ultimately, open source technologies increase the scope and variety of clinical trials, by enabling smaller institutions to pursue their clinical research that would otherwise be out-of-reach and beyond financial capacity. “We believe that an open-source approach has the best chance of ensuring that all kind of groups can be involved with the development of systems that have bearing on global public health”, explains Greg W. Fegan and Trudie A. Lang in their featured article Could an Open-Source Clinical Trial Data Management System Be What We Have All Been Looking For?

Read our latest white papers now

References

• Silicon Valley BioTalks, June 2011 : http://www.clinovo.com/node/129
• “Could an Open-Source Clinical Trial Data Management System Be What We Have All Been Looking For?”, By Greg W. Fegan and Trudie A. Lang, March 4, 2008
• “Overcoming Obstacles To Successful Clinical Trials through Open Source”, by Benjamin Baumann, Nov 10, 2011
• 2011 profile, PhRMA Pharmaceutical Industry
• Opensource.org
• https://cabig.nci.nih.gov
• http://ycmi.med.yale.edu/trialdb/
• http://open-source.gbdirect.co.uk/migration/benefit.html
• Health Decision Webinar “Top 10 Benefits of Adaptive Design”, Jan 25, 2011

Download

• CDISC Express: www.clinovo.com/cdisc
• ClinCapture brochure: http://www.clinovo.com/resources/brochures/clincapture
• Clinovo case studies on open source systems: http://www.clinovo.com/case_studies

Drug development time is money for some, life-and-death for others

May 24, 2012 by Clinovo    No Comments    Posted under: Best Practices, Trends

For years, critics have said the FDA’s medical device approval process takes too long, particularly when compared with the one in Europe. In the U.S., companies argue they lose valuable time and money as they seek to improve the lives of patients they serve.

This paper argues that the development process for experimental drugs could be accelerated without significantly endangering the Public’s health thus saving lives and cutting cost. Read more »