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.
Marketing & Communication Coordinator at Clinovo
It is a very exciting time for Clinovo! We are now officially launching our TechTrainings, a new opportunity for a successful career in the clinical trial industry. These hands-on classes enable entry-level or already experienced clinical trial professionals to improve their skillset. Real-world case studies were designed with 10+ years experienced professionals to help our students reach the next step in their career.
Please visit this page to check out the first session 101 Clinical SAS Programming by Jennifer Kang, Senior Statistician at the Palo Alto Medical Foundation Research Institute (PAMFRI). We know it takes time and effort to “go back to school” so we came up with a convenient format: one 3-hour class per week during 10 weeks. If you happen to know anyone interested in learning SAS, note that you can win a $50 giftcard and your friend can benefit from a discounted registration.
Some of our readers and followers expressed the need for other trainings in the future. If you think of another major topic for which Clinovo’s expertise is needed (CDM, EDC, CDISC, clinical trial design, etc.) feel free to comment this article.
Marketing & Communication Coordinator, lead for Clinovo TechTrainings.
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:
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.
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
The FDA’s mission is to protect public health by assuring “the safety, efficacy and security” of drugs. Indeed, the FDA has the tremendous challenge of ensuring sponsor companies deliver efficient treatments to patients while meeting the highest possible safety requirements. FDA reviewers always need to thoroughly weight risks versus benefits. This sometimes has dramatic consequences: The FDA admits that in the United States 100,000 people die every single year taking FDA-approved pharmaceutical drugs. In addition to that, two million people a year suffer from serious adverse events, which include stroke, heart attack, and permanent neurological damage.
The FDA is increasing efforts to improve patient safety and identify potential side effects. It is more and more demanding with healthcare companies, trying to ensure qualified processes are in place . Indeed, while the number of FDA approvals per 1,000 US-based clinical trials has declined from 7.5 in 2004 to 3.1 in 2010, industry experts are facing increased complexity and cost when managing clinical trials. A 2010 PhArma report argues that between 2000 and 2007, the median number of procedures per clinical trial increased by 49%.
For a drug or a medical device, everything starts or ends one day in the walls of the Food and Drug Administration. What make the difference between failure and success are your clinical data and the way you deal with the FDA. This article intends to help you understand the secrets behind a successful FDA submission.
Provide regulatory compliant data
One of the new FDA expectations includes using standard format for clinical data for their submission. The FDA is thus gradually implementing CDISC standards. CDISC® (Clinical Data Interchange Standards Consortium) established these data standards to speed up data-review and improve clinical data exchange, storage and archival. CDISC standards have been acknowledged as recognized standards by the FDA for years now. They are gaining momentum and undoubtedly are an asset to accelerate the FDA review process. By 2016, CDISC standards are expected to be mandatory for any drug submission.
Understand and follow the FDA’s transformation
Staying up-to-date on any new initiatives is fundamental in order to always anticipate FDA expectations. The FDA is adapting to therapeutic-based clinical trials or personalized medicine. On the same note, the rise of orphan drugs forces the FDA to develop specific and shortened review processes. The FDA is continuously adapting to these life sciences developments. Christine Conroy, Vice President of Regulatory Affairs and GCP compliance at Affymax, points out that with the growing number of very particular compounds and patient-specific therapies, it has become sometimes difficult to provide data the FDA asks. The FDA sometimes lack experience in new fields such as biomarkers. Indeed, there is no reference point as everything is new, so it happens that the FDA brings up issues not always relevant in that field.
Find creative study design strategies to meet your endpoint
Small companies often lack financial or human resources to oversee CRO activities and analyze the quality of the data. This can be overcome by being more creative in the sponsors’ design strategy to reach the endpoints. Sponsors can for instance rely on open source based eClinical Systems (such as CDISC Express or ClinCapture marketed by Clinovo) in order to avoid expensive licensing fees and meet tight budget requirements.
Partner with the FDA
Transparency is an absolute pre-requisite in partnering efficiently with the FDA. It is critical to be detail-oriented and to think upfront to provide and anticipate the information the FDA will need and require. Having internal checking prior to the actual FDA submission is critical because “if you have questions or doubt about your data, the FDA will too”, explains Sandra Nino-Siddens, Executive Director of Regulatory Affairs at Geron Corporation.
Sandra Nino-Siddens claims that “sponsors should be straightforward in presenting rationale and steps followed to develop a safe product.” She outlines the importance of building good relationships with the FDA from the beginning and to keep forth-coming interactions with them. Sandra Nino-Siddens states that “the FDA should be seen as a as a long-term partner, and not be seen as the police, nor as a consulting company.”
Olivier Roth, Marketing & Communication Coordinator at Clinovo
If you liked this article, we recommend you to read: What is the prescription drug user fee act in a nutshell
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:
- Free redistribution
- Source code
- Derived works
- Integrity of the author’s source code
- No discrimination against persons or groups
- No discrimination against fields of endeavor
- Distribution of license
- License must not be specific to a product
- License must not restrict other software
- License must be technology-neutral
Taken from Opensource.org. See http://opensource.org/docs/definition.php 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?
- 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
- Health Decision Webinar “Top 10 Benefits of Adaptive Design”, Jan 25, 2011
- 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
On March 7th 2012, Clinovo hosted the third Silicon Valley Biotalks, hosted by SNR Denton in their Palo Alto offices. The event welcomed over 60 professionals from the biotechnology and pharmaceuticals industry. The panel was composed of top-tier CDISC experts:
- John Brega (PharmaStat) CDISC Implementation and eCTD Submissions
- Carey Smoak (Roche Molecular) Senior Manager, SAS Programming and CDISC Device Team Leader
- Dave Borbas (Jazz Pharmaceuticals) Senior Director, Data Management
- Ale Gicqueau (Clinovo) President & CEO
- Carey Smoak made the point that the medical device world is on the move to implement CDISC standards. One has to be aware that the simple fact in putting data in an electronic database is quite new for some medical devices companies. Combination products in which medical device interact with a drug is favorable to the implementation of CDISC standards. Indeed, the medical device world is learning from the experience of the drug industry on CDISC standards.
- John Brega mentioned that 60% of FDA submissions are already done in CDISC standards. He also stated that smaller pharma companies adopt CDISC standards faster. Indeed, a lot of the bigger companies have already developed in-house standards and even though they see the benefits of CDISC standards, it takes money and time to transform their processes and change their habits. On the other hand, smaller players that have no or few standards in place are more prone to start using FDA approved CDISC standards.
- One of the advantages of CDISC standards is that it holds the clinical data to a greater level of readability and compliancy in regards of FDA requirements. A submission without SDTM can have a review period twice as long as one under SDTM standards. CDISC conversion allows submitters to find out problems or discrepancies even before the FDA does, which gives more data consistency and confidence for the FDA submission. It saves time and frustration on both sides.
- Carey Smoak said that the earlier the CDISC standards were utilized, the better. The best timing to implement CDISC standards is the database built. There is a real challenge to push CDISC standards upfront in the clinical trial process. He recommended to hire people with expertise on CDISC standards. One should educate themselves on this hot topic and only hire real experts and approved service providers.
- Dave Borbas mentioned existing CDISC conversion tools, such as the open CDSIC validator software, recognized by the FDA and freely available. He talked about CDISC Express, Clinovo’s free SAS-based SDTM mapping tool. Carey Smoak mentioned the development of new softwares, and that applications on smartphones are also mushrooming, but stated that quality, validation and compliancy were very tricky in this case and an upcoming challenge.
- Dave Borbas said that the FDA is getting more and more involved into CDISC standards. FDA calls it “their” standards now, which is new and great signal to the CDISC community.
Do you want to learn more on CDISC conversion?
Register for free for our next Webinar on March 28th at 9am:
CDISC® SDTM Conversion Made Easy with CDISC Express
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