I was at an Analyst conference last week where I met a couple of analysts (no pun intended :-)) focused on Life Sciences who felt that “Big Data” is a tough sell in Life Sciences, except for Genomic Data. That made me think. I always associated “Big Data” with the size of the data sets running into Peta Bytes and Zetta Bytes. What I learned in my journey since then is that the characteristics of Big Data does not start and end with the Size.
This article on Mike 2.0 blog by Mr. Robert Hillard, a Deloitte Principal and an author, titled “It’s time for a new definition of big data” talks about why Big Data does not mean “datasets that grow so large that they become awkward to work with using on-hand database management tools” as defined by Wikipedia. He goes on to illustrate three different ways that data could be be considered “Big Data”. For more, please read the blog.
One quality he explained that is of interest to me is “the number of independent data sources, each with the potential to interact”. Why is it of interest to me? I think Clinical Data, in the larger context of Research & Development, Commercialization and Post Marketing Surveillance definitely fits this definition. As explained in one of my previous posts title “Can Clinical Data Integration on the Cloud be a reality?“, I explain the diversity of clinical data in the R&D context. Now imagine including the other data sources like longitudinal data (EMR/EHR, Claims etc.), Social Media, Pharmacovigilance so on and so forth, the complexity increases exponentially. Initiatives like Observational Medical Outcomes Partnership (OMOP) have already proven that there is value in looking into data other than the data that is collected through the controlled clinical trial process. Same thing applies to some of the initiatives going on with various sponsors and other organizations in terms of making meaningful use of data from social media and other sources. You might be interested in my other post titled “Social Media, Literature Search, Sponsor Websites – A Safety Source Data Integration Approach” to learn more about such approaches that are being actively pursued by some sponsors.
All in all, I think that the complexities involved in making sense of disparate data sets from multiple sources and analyzing them to make meaningful analysis and ensure the risks of medicinal products outweigh the benefits will definitely qualify Clinical Data as “Big Data”. Having said that, do I think that organizations would be after this any time soon? My answer would be NO. Why? The industry is still in the process of warming up to the idea. Also, Life Sciences organizations being very conservative, specially when dealing with Clinical Data which is considered Intellectual Property as well as all the compliance and regulatory requirements that goes with the domain, it is going to be a long time before it is adopted. This article titled “How to Be Ready for Big Data” by Mr. Thor Olavsrud on CIO.com website outlines the current readiness and roadmap for adoption by the industry in general.
The next couple of years will see evolution of tools and technology surrounding “Big Data” and definitely help organizations evolve their strategies which in turn will result in the uptick in adoption.
As always your feedback and comments are welcome.
It is universal fact that the escalating costs of discovering new medicinal products are driving sponsors and CROs to scrutinize every dollar spent in the process. The situation is escalating fast as pressure mounts with the blockbusters of yester years come off patents. This means that there is a need for all the stakeholders in the value chain to revisit their approach to existing processes and come up with innovative ways to save costs.
Risk Based Site Monitoring:
US FDA has also recognized this fact and come out with a “Guidance for Industry Oversight of Clinical Trial Investigations – A Risk Based Approach to Monitoring”. As per this guidance the objective of the guidance is “to assist sponsors of clinical investigations in developing risk-based monitoring strategies and plans for investigational studies of medical products, including human drug and biological products, medical devices, and combinations thereof”. As per the document its overarching goal is to “enhance human subject protection and the quality of clinical trial data”. However, it clarifies on the strict interpretation that the industry has assumed long back and has spent billions in monitoring the sites. While this is draft guidance it is more than likely that this will end up in establishing the guiding principles for central monitoring of clinical trials, as such is the intent.
Risk Based Source Document Verification:
Primary activity of site monitoring is the source document verification and as was the case in site monitoring, industry has been mostly using the strict interpretation of source document verification. This resulted in 100% of source documents (patient eCRFs) being verified by the site monitors. However, the industry has realized that “law of diminishing returns” applies to this process as well and has been reducing the percentage of documents verified by the monitors. Medidata’s Insights “Targeted Site Monitoring Trend Snapshot” published in Applied Clinical Trials website confirms this trend. According to this report the SDV percentage has reduced from 85% in 2007 to 67% in 2010.
Virtual Clinical Trials:
Another key trend that is slowly evolving in this context is complete virtualization of clinical trials. Pfizer is taking the lead in this space. While Pfizer’s REMOTE program is ongoing, an interim feedback from the program is provided by Mr. Craig Lipset, Head of Clinical Innovation at Pfizer is provided by Applied Clinical Trials in their article titled “Pfizer’s REMOTE Virtual Experience”. As highlighted in the article, they are going through the roadblocks of an early adopter.
Adoption of Enterprise Collaboration and Content Management:
Electronic communication and collaboration:
The above trends indicate that it is just a matter of time that total virtualization of clinical trials is accomplished. The key question that needs to be addressed is “How will the human interactions be virtualized?” The answer is “to adopt electronic communication and collaboration channels”. The channels can range from adopting systems to capture and manage clinical data, electronic source document verification to seamless communication and collaboration tools. The unique constraint with respect to clinical trials though is to ensure that the tools used adhere to “Good Clinical Practices” as well as other regulatory requirements like 21 CFR Part 11, HIPAA etc.
Enterprise Collaboration and Content Management Systems:
Systems for Electronic data capture (EDC), Clinical Data Management (CDM), Clinical Trial Management System (CTM), Adverse Event Management etc. are already available in the market. The key tool that would make it easier to seamlessly transition from human interactions to virtual interactions, in my view, is an Enterprise Collaboration and Content Management tool. Tools like Microsoft’s SharePoint, as highlighted in one of my previous blog posts, will help organizations make this transition fast and cost-effective. While it is always easier said than done, from real world experiences that we already have, it is relatively easy to adopt these tools in a GxP environment, meet all the regulatory compliance requirements and also accomplish the degree of flexibility required to easily communicate and collaborate.
Social Media and Mobility:
A couple more initiatives that could complement in the process are Social Media and Mobility. The need for a social media outreach program to increase the patient recruitment is highlighted by the channels Pfizer’s REMOTE program has adopted. On similar lines, social media “like” features can be enabled on the collaboration and communication platform to be adopted. This can increase the accessibility and improve the response times from the patients. On similar lines, if the collaboration and communication platform can be made available over mobile devices like smart phones, tablets etc. the patient compliance and response times will improve considerably. Tools like Microsoft SharePoint make it easy to enable the social features and also deliver content to mobile devices.
Overall the ability of a sponsor or CRO organization increases tremendously to virtualize their clinical trial process by leveraging collaboration and content management tools. The overall “Risk-Based” approach to site monitoring and source document verification will also be “made easy” through these tools. As noted in my previous posts, leveraging a tool like SharePoint for such purpose will improve the Return on Investment (ROI) and reduce the Total Cost of Ownership (TCO) of these tools.
As always, your feedback and comments are welcome.
This post has been picked up by www.AppliedClinicalTrialsOnline.com and published on their website.
Recently I was asked to provide inputs to an Article/White paper that looks ahead in terms of Technology and its impact on Life Sciences in medium to long-term. Here’s a list (in no particular order) that I thought would be the key trends to look out for from a short to medium term. I pulled this together based on some predictions by the industry analysts as well as thought leaders along with my personal experiences with some customers and their immediate to medium term requirements.
- Mobility: It is a universal fact that the adoption of mobile devices, be it smart phones or tablets, is increasing at a phenomenal rate. This will force the pharmaceutical organizations to adopt a “think mobile” strategy. This trend will mandate the IT and technology teams to adopt an enterprise mobile strategy. In the long run this could even result in applications developed 100% for mobile devices only.
- Solutions on Cloud: Adoption of SaaS and Cloud based solutions and services have been increasing over the last 2 to 3 years. Pharmaceutical industry being historically conservative, the rate of adoption is not the same as some of its peer industries. The Sales & Marketing departments within life science companies have been better at this. This will change soon and we will see cloud based solutions adopted in the R&D space as well.
- Multi-Device Applications: As the pharmaceutical industry is highly regulated, for obvious reasons, their IT organizations have been seeking higher control on the devices used to access information and data. With the advent of smart phones and tablets and rapid adoption, all new applications developed, by default, will target multiple devices.
- Source Data Integration and Business Insights: Life Sciences organizations are realizing the fact that they have been collecting tons of useful data but have not been able to analyze and make smarter decisions using this data. This is leading to more and more programs and initiatives around Master Data Management, Source System Data Integration, and Enterprise Data Warehouses etc. This trend will continue and will even lead to industry wide cooperation and collaboration for the greater good in terms of patient safety, efficacy and outcome based pricing.
- Personalized Medicine and Technology Requirements: As the healthcare costs keep rising in countries like US, the scrutiny on the money being spent on drugs, devices and treatments is increasing. Also, the outcomes from usage of the products are being considered as a measure to regulate the pricing of the products. This will lead to more personalized treatment and care for patients based on whether they would be the right candidate for the proposed treatment/intervention. This would drive IT and technology teams to develop solutions for being able to identify the target patients for the products from the patient population.
- Standards Based Systems and Integration: Organizations and people cannot exist in silos. They have to continuously communicate and coordinate to make things work. This is the case with IT systems. Most of the legacy systems existing in pharmaceutical industry have been designed and developed to suit the specific needs of customers. In this day and age of continuous information exchanges this poses a big challenge due to the proprietary nature of data. While there are existing standards (from groups like CDISC, HL7, DIA etc.) that have been adopted, there is still need for building systems from the ground up to support these standards. This trend will increase and drive the IT organizations within Pharma as well as vendors developing solutions for Pharma industry to adopt these standards and build them into the tools and applications being developed.
- Social Media and Data Complexity: This is another area that has seen tremendous growth in the last 3 to 4 years. However, in the life sciences industry there is lack of guidance and direction from a regulatory stand point. However, this has not stopped the marketing and other customer focused groups embrace this channel of outreach. While this has benefited some customers tremendously, few others got into trouble with the regulators. Organizations that have started collecting the data are sitting on a gold mine of unstructured data. In order to process this data and generate business insights, it requires investments in technology. We will see more and more organizations increasing the adoption of social media but also increasing investments in leveraging the data generated and make strategic business decisions based on the insights thus obtained.
- Technology adoption for Emerging Markets: The dynamics in terms of technology adoption in emerging markets is unique and different from developed markets. For example, the adoption of mobile phones is higher than desktops in India. This requires a change in strategy in technology investments for pharmaceutical organizations. Similarly as the global nature of clinical trials increase, the technology available at some of the emerging market study sites is very different from US or EMEA study sites. This will demand a new technology approach to developing and deploying solutions to these markets.
- Global Regulations and increasing system complexity: As pharmaceutical customers introduce more and more products in emerging markets, they have to be compliant in terms of process and systems to meet the local regulatory needs. While there would be country/market specific regulations, the systems deployed to manage these processes are usually global in nature. This will increase the need for building systems compliant with multiple market regulatory compliance. For example a New Drug Application (NDA) can be submitted electronically in US and few other countries where as in some emerging countries these are still being submitted in paper form. This requirement will demand a system capable of reusing documents and content for multiple markets by taking the local regulations into consideration.
- Self-Assist Devices and Remote Monitoring: As stated earlier, due to increasing healthcare costs patients are trying to avoid hospital or clinical visits to the maximum extent possible. Healthcare and Pharmaceutical organizations are working towards providing devices that can be used by customers without much technical assistance. These devices should be monitored remotely and also data thus collected need to be pushed onto database systems for further analysis. This will pose challenges in terms of not only building easy interfaces to these systems but also ensuring accuracy and security of data.
- Healthcare and Pharmaceutical Industry Convergence: Healthcare organizations like Providers and Payers have gigabytes and petabytes of longitudinal data that can be mined to make more informed decisions about the target patients for certain treatments as well as outcomes of treatments. There are industry initiatives like the Sentinel project to leverage this data. These initiatives will drive industry wise collaboration and integration of systems to exchange information. This will demand existing and new systems to adopt standards for information exchange as well as develop and implement new systems to leverage the information gathered through this collaboration. We will see more and more systems that will cut across those two sectors and help in the convergence.
As always, your feedback and critique is most welcome.
I haven been part of my fair share of discussions on Drug Safety and Social Media. In fact, I have even written a blog post about how these two are being forced into an “arranged marriage”, which could be a good thing :-). While processing data from social media is very complex and often unreliable, there is increased push to process it anyway. Understandably, Marketing teams are the first to adopt social media channels in pharmaceutical organizations, now the drug safety teams are being forced to act as these channels could end up generating adverse events and they are obligated to register, review and report.
As mentioned, processing of data from social media could be complex and may yield very few cases (0.2% according to a Nielsen’s Online survey of health-related social media content) the high level process is very similar to Literature Scanning. The later is something that is already being handled by organizations. I think that the Social Media content search and analysis can becoming an extension to this process. Now lets look at both the processes.
Literature Search is used by BioPharmaceutical organizations to identify Adverse Events related to their medicinal products in medical and scientific journals published worldwide. This process was adopted as a result of multiple serious adverse events and the ensuing regulations and increased safety concerns. Many sponsor organizations have successfully built automated systems to speed up the overall process. These systems typically scan sources (Journals, Abstract Libraries and Reference Libraries) based on certain keywords, product names, Boolean expressions etc. and capture the mentions into a local database. These entries are then screened by trained professionals to either accept or reject them based on the required data elements to qualify as an adverse event. If additional details are required, the journals are purchased and reviewed to qualify the “hit” as an adverse event. Once identified, this becomes a case that will then be transferred manually or electronically (e.g. E2B) to an Adverse Event Management System and will follow the life cycle till it is reported as an expedited or periodic report to regulatory authorities.
This process can be very similar to Literature Search except that the source of data is much more diverse and also the data is far less structured. Depending on the source system, a manual or automated process can be adopted to monitor and record the “hits”. If the source system is a “blog” or “Twitter” or “Facebook”, a tool can be build to continuously poll certain blogs, tweets or Facebook pages to scan for keywords, products/brands etc. The resulting “hits” can be processed to filter and aggregate the “trends”. These trends can then be reviewed by trained professionals to make a decision on whether they qualify as “Safety Cases” that will then be processed per the AE case management process.
Enterprise Websites, Response Centers etc.:
The third variety that may be considered as source systems for safety cases are Brand Websites and other portals setup to increase the brand awareness or assist the patients to receive medicine faster or address any questions and concerns. This may even include response centers setup for patients, pharmacists and physicians to reach the sponsors for information and advice. Depending on the nature of inquiries, these could be potential sources of Adverse Events. This data, once screened and qualified, can also be fed into the AE Management System for subsequent review and reporting purposes.
Source Data Integration:
From a technology standpoint the architecture and design for aggregation and analysis of data may differ for each of the datasets. However, an integrated approach to collecting, aggregating, analyzing and reporting of Adverse Event data needs to adopted by the sponsor IT organizations. The diagram below depicts:
- Multiple Source Categories and Systems (Literature, Social Media, Enterprise Websites)
- Multiple Interfaces (Manual, XML, Text, API, RSS, Web Services etc.)
- Simple, High Level process to screen, record, review and report the case
(To Be Continued…)
Social media is all about freedom of expression. safety and Pharmacovigilance is about patient safety and utmost confidentiality of patient information and not to mention the huge financial implications of misinformation. Having said that, life sciences organizations have recognized the need for proactively managing risk and having access to information related to patient safety, good or bad, before anybody else. In the light of this realization, there is tremendous pressure on heads of safety to formulate a social media strategy. While there is anxiety on their part as to the implications of such a strategy in terms of cost, productivity and compliance they are also grappling with not having the right guidance from the regulatory authorities.
Despite the challenges, there are some organizations that are making best use of social media while there are a few that got burned in the process. My interest in this subject is more from a technology perspective. What does this mean from an automation, integration and analysis stand point? As such organizations have recognized the need for safety data integration and analysis and started moving towards setting up safety data warehouses. The chatter on social media about adverse events from drug, device or vaccine use becomes another source to be scanned, filtered, reviewed and stored. Each of these activities pose a great challenge for technology implementation as well as effort required to setup the process and maintain it efficiently.
The key to successfully handling these challenges lies in finding answers to questions like:
1. Is our social media strategy in line with our organizational and regulatory policies?
2. What are the technology implications?
3. Is our IT team ready for this challenge?
4. Is the market mature enough to provide solutions and services to assist out IT and Business teams?
5. If not, which of the partners in our Ecosystem can help us develop the right solutions and provide services?
While these are some random thoughts and questions, it has to be seen how the market matures and rises to this challenge. The key is for the industry, as a whole, to figure out the use of social media in safety and Pharmacovigilance context and subsequently identify the right solutions that will provide the necessary support to make this a reality. As long as this doesn’t happen, the early movers will always be at a disadvantage and end up spending lot of effort and money while struggling to justify the return on this investment.
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