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Safety Analytics – What does Oracle Argus Analytics bring to the table?

Many large Drug Safety organizations have initiatives to leverage the historical data available to them and measure the operational inefficiencies of their processes. In my opinion these initiatives are worth spending your dollar. With the increased scrutiny by regulators on patient safety, drastic increase of data sources and dwindling budgets, the more you know about how good or bad you are at managing your processes to handle safety cases is worth the investment.The challenge always is with deciding what do you want to measure beyond your typical KPIs that you’d get from standard reports made available by the drug safety system vendors. Also, how flexible is the tool in making it easy for your team to define additional KPIs, create dashboards/reports and combine historical data with current data to perform comparative analysis.

Oracle has quickly established themselves as a leader in the Drug Safety space through acquisition of Relsys and Phaseforward. They probably have 3x the customers compared to their nearest competitor for all of their three safety systems. While this creates confusion in the short term, Argus Safety is emerging as the strategic product that they would support and continue enhancements in the long run. One of the initiatives that has come to fruition around this tool is Argus Analytics (formerly Oracle Pharmacovigilance Analytics ot OPVA) which has been available as a general release for close to 2 years now. While it demands additional investment from sponsors, I think it is a good starting point for any sponsor or CRO trying to measure their operational efficiency, identify bottlenecks and improve their decision making process.

I will keep this post brief and not go into the details of each KPI/Dashboard that is available in Oracle Argus Analytics and give a list of dashboards available. Many of these are self explanatory. More information can be found in the user guide available online here: http://docs.oracle.com/cd/E35225_01/doc.11/e29106/toc.htm

Dashboard Type Filter Pages (Tabs)
Case Processing History Trailing Enterprise ID Case Processing Volume History
Case Processing Compliance History
Workflow State Repetition History
Case Processing Management Current Enterprise ID Case Processing Volume Management
Case Processing Compliance Management
Workflow State Compliance Management
Personal User Dashboard Trailing & Current Enterprise ID Personal User Case History
Personal User Case Management
Personal User Case Work History
Personal User Expedited Report History
Personal User Expedited Report Management
Expedited Report History Expedited Submission Volume History
Expedited Non-Submission Volume History
Expedited Submission Compliance History
Expedited Report Management Expedited Submission Volume Management
Expedited Submission Compliance Management
Expedited Failed/Pending ACK Volume Management
Case Work History Case Modified History
Case Unmodified History
Case Read History
Case Idle History

Hope this gives a high level idea about the various dashboards available in Argus Analytics.

Leveraging Technology to Improve Patient Recruitment for Clinical Trials

I was asked to respond to a costumer inquiry recently to help them with providing a solution to improve their patient recruitment in clinical trials. Initially, I thought this must be a question to one of our experts in our CRO. However, I kept thinking about it and realized there isn’t a silver bullet that would solve this problem. There is no commercial off-the-shelf solution to fix this problem. Sponsors, CROs, Site Coordinators, PIs and other stakeholders involved in the clinical research have been struggling to address this situation but it is still a challenge and is the root cause of delays in clinical trials which will result in increased and lower Returns on Investment (ROI).

Discovery and development of medical products take a long time and consume lot of resources (Effort & Cost) from sponsors from molecule to patient. This involves discovery of the molecule to pre-clinical and clinical development to marketing & sales. A lot of these resources are typically spent in late stage (Phase III) of clinical trials. One of the root causes for delays in clinical trials in phase III is delay in recruiting the patients that meet the inclusion criteria of the protocol. Another key concern is patient drop out during the course of the trial. These issues not only delay the trial but also force the sponsors and CROs to consider changes to the protocol or force them to take alternative steps to ensure the necessary patient population is recruited to continue the trial.

Adherence rates across the duration of therapy

Adherence rates across the duration of therapy

According to a report on Patient Adherence by Capgemini consulting [1], “Patient adherence levels vary between 50% for depression to 63% for enlarged prostate. On average, adherence levels drop over the course of the patient journey from 69% of patients filling their first prescription to 43% continuing their treatment as prescribed after 6 months.”

Also, if you notice in the attached diagram, 31% of the patients recruited will not last until they fill their prescription. Further, by the sixth month almost 57% patients do not show up for their refills. At this rate, in order to continue the trial, the sponsor has to continue to recruit patients during the course of the trial. This recruitment due to a drop out comes at a cost. The report has also identified that the cost of recruiting a new patient is 6 times the cost spent by sponsors to retain an existing patient.

So, what are the sponsors/CROs doing to improve the patient recruitment and reduce the drop outs? The key to fixing any problem is identifying the root cause. For this problem, there are multiple areas of failure and hence requires a comprehensive, multi-pronged strategy to fix the problems.  Some of the best practices being adopted by sponsors and/or CROs include:

  • Comprehensive and incremental approach to integrated solutions rather than silos  by leveraging :

–          Patient registries

–          Better communication between patients and clinicians

–          Electronic records

–          Better engagement of physicians

  • Refine Site selection

–          Analysis to select better performing sites

  • Patient centric recruitment process

–          Simplify informed consent process (move to informed choice)

  • Collaborative approach to Protocol design

–          Engaging Principal Investigators (PIs) in protocol design by research coordinators

  • Improve patient retention

–          Better follow-up systems to increase adherence

–          Enhanced post-trial engagement

In order to implement these best practices sponsors can adopt technology solutions like:

  1. Create strategy to improve the recruitment process by leveraging technology solutions
  2. Analyze site performance and select high performing sites and drop out non-performing sites
  3. Patient Recruitment Systems to search and match protocol eligibility criteria with patient’s available Electronic Health Records (EMRs, Narratives, Health Insurance and Claims Documents)
  4. Social Media tools to target patient communities to identify potential subjects from the available patient population
  5. Social Media tools to gauge trial buzz in patient and physician community
  6. Study & Investigator Portals to enhance engagement and collaboration between study coordinators and Principal Investigators
  7. Mobile Trial Adherence Systems to alert and notify patients of visits and other trial compliance activities to reduce drop outs
  8. Key Opinion Leader portals to better engage physicians
  9. Analytics to identify potential subjects, site initiation process and performance, patient recruitment effectiveness, patient drop out alerts etc.
  10. Advanced analytics to simulate recruitment performance based on historical data and thus tailoring recruitment strategy based on sites and other factors

Despite all these best practices and solutions, will be able to help the sponsors and CROs in:

  • Collecting historical and real time operational and scientific data
  • Performing objective analysis of data
  • Visualization of such performance
  • Identifying the bottlenecks and root causes for the problems
  • Helping in making decisions to select the right sites, recruit the right patients, avoid costly drop outs and improve the collaboration and communication among Patients, Primary Investigators and other stakeholders.

I will be writing about each solution in my “Top 10” list above. As I mentioned in the beginning of this post, there is no silver bullet for this problem. A strategic and integrated approach to create solutions that will aid in collecting, analyzing and decision making is the only way to solve this problem.

As always, please let me know your feedback. If you have more insights into the problem or solutions, I will be more than glad to discuss with you and also post some of the inferences in a subsequent post, as promised. Happy Reading!!!

References:

  1. “Patient Adherence: The Next Frontier in Patient Care – Vision & Reality, 9th Edition Global Research Report”  by Capgemini Consulting

Predictive Analytics : Capacity planning for fluctuating Safety Case Volumes

Wikipedia defines Predictive Analytics, as “Predictive analytics encompasses a variety of statistical techniques from modeling, machine learningdata mining and game theory that analyze current and historical facts to make predictions about future events.” While not all of the techniques stated above are required, a lot of data mining and statistical analysis need to be performed on historical data before one can predict the future trends and outcomes. The accuracy of the prediction depends on the variables and assumptions considered and will be the key to making accurate predictions of risks and opportunities.

Case in point, the volume of cases that come in for a product safety case processing organization varies depending on many factors. The variance could be due to factors like Seasonality of Adverse Events, A news item discussing potential side effects of a product, A blog post by a physician or some influential group or organization so on and so forth. With the ever increasing cost pressures on life sciences organizations, it is very difficult to plan for peak volumes while there will be additional unused capacity during the troughs. This is the kind of situation where any organization can use some predictability so they can plan the capacity within a reasonable deviation thus normalizing the peaks and troughs.

Imagine an business intelligence solution that can mine the historical case volumes and the corresponding capacity in conjunction with the process efficiency and be able to predict the future capacity requirements. Add the ability to evaluate some ‘What if” scenarios where one can change variable like case volumes and be able to predict the capacity requirements. While this may sound like a “Holy Grail”, it is possible with some of the sophisticated tools available. A screenshot of one such solution below:

Predictive Analytics - Product Safety Capacity Planning

possible solution for capacity planning for a product safety organization

Do you have a need for such solution in your organization? Have you built a predictive analytics solution for other purposes? Please share your feedback and inputs.

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.

Jumpstart your PV Operational Efficiency Improvement Initiatives through Oracle Pharmacovigilance Operational Analytics (OPVA)

I attended Oracle Open World (OOW) recently during the week of Oct 2nd. I got a sneak peek of the newly released Oracle Pharmacovigilance Operational Analytics tool. This tool is intended to provide a jumpstart to the efforts of Safety & Pharmacovigilance departments of MAHs and CROs in being able to monitor the operational performance of the organizations and identify the bottlenecks. The key point to note is that this tool provides only the Operational Analytics and doesn’t include the Scientific Analytics.

Some of the Key business benefits it will deliver include:

  • Insights into the case processing operations
  • Measure compliance and productivity across the organization
  • Provide ability to monitor the KPIs and metrics through dashboards in real time
  • Provide ability to drill down to identify the bottlenecks in the process
  • Improve productivity and save costs across the organization
  • Improve compliance and enable better patient safety

From IT Systems perspective:

  • Single repository of operational safety data
  • Star schemas that could be populated with data from internal and external sources
  • Predefined reports, KPIs, Metrics and Dashboards
  • Ability to customize and extend the dashboards and reports
  • Ability to view current as well as historical operational performance of organization and individuals
  • Out-of-the-box integration with Oracle’s Argus Safety
  • Built using Oracle BI (OBIEE) which gives ability to view dashboards on web as well as on mobile devices (iPhones and iPads)

Some of the key dashboards that are provided out-of-the-box:

  • Case processing history in terms of volumes, compliance and repetition
  • Case processing management in terms of volumes, compliance and workflow state SLA management
  • Personal user dashboards with individual’s case management and case history,

Some of the reports include:

  • Completed case volume overview and trends
  • Pending case volume overview and trends
  • Case version line listings
  • Individual case workload reports and line listings

OPVA is compatible with Argus Safety 6.0.2 and Argus Safety 7.0.

One of the key uses of OPVA for organizations that want to define additional metrics, KPIs, dashboards and reports is the start schema that is provided with the product. It comes with a set of predefined dimensions and facts that can be leveraged to speed up the process of developing the additional custom dashboards, KPIs, Metrics and Reports.

Dimensions provided by the OPVA schema are:

  • Period
  • Product
  • Study
  • List of Values
  • Users
  • User Group
  • Case Processing Site
  • Country
  • Enterprise (in a multi-tenant scenario more relevant for CROs)

The pre-built facts into the OPVA data mart are:

  • Case Version History
  • Case Routing History
  • Case Workflow History and
  • Pending Cases

I think this is a very good addition by Oracle to its stable of products and compliments the existing tools quite well. This is also a very good tool for customers wanting to jumpstart their efforts to measuring their safety operations (aka Case Processing), identifying the bottlenecks in terms of compliance and productivity and rein in costs through improvement plans to enhance these aspects.

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