Tag Archive | Source Data Integration

Impact of Technology on Life Sciences Industry

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.

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.

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Social Media, Literature Search, Sponsor Websites – A Safety Source Data Integration Approach

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:

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.

Social Media:

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:

  1. Multiple Source Categories and Systems (Literature, Social Media, Enterprise Websites)
  2. Multiple Interfaces  (Manual, XML, Text, API, RSS, Web Services etc.)
  3. Simple, High Level process to screen, record, review and report the case
Literature Scanning, Social Media & Enterprise Websites  - Safety Source Data Integration

Social Media Safety Source Data Integration

(To Be Continued…)

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