Bayer’s Clinical Trials Device-Driven Future: Powered by the Oracle mHealth Connector Cloud Service

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Bayer’s Raj Pallapothu is developing one of the first enterprise mobile health platforms for clinical trials utilizing the Oracle mHealth Connector Cloud Service technology. He leads mHealth (mobile health) initiative at Bayer Pharmaceuticals USA and happens to be a medical doctor with extensive experience with infectious diseases. His project at Bayer is timely at this juncture in history—with an explosion of personal devices (cell phones, step monitors, mobile ECGs, etc.) opens new communication and collaboration not to mention data collection and aggregation opportunities for clinical trials.

The First mHealth Platform for Clinical Trials

Forbes picked up on Oracle’s paid content contribution from Margaret Lindquist. The explosion of apps available for clinical research is real ad covered from time to time by TrialSite News. In the case of Bayer, they are creating what they claim (and we cannot verify) is the first mHealth platform for clinical trials based on the Oracle mHealth Connector Cloud Service technology. The article reveals that Accenture and Oracle professionals services are collaborating on this important endeavor for German Bayer which is one of the ten largest pharmaceutical companies in the world.

The “To Be” Vision

Apparently, the platform is not complete yet. The author reports that the team is striving for one complete software platform enabling digital monitoring and interactions with new ways to capture data such as biosensors, wearables, and mobile applications. Once complete, clinical trial teams can connect to easily embrace new innovative biosensors and patient-centric engagement apps which in theory offer heretofore, not feasible ways to gather, collect and manage data in real-time supporting deeper insights into the patient in the day-to-day world.

Building Blocks for Compliant Rich Patient Data

The mHealth platform includes Oracle Analytics Cloud, Accenture’s INTIENT Clinical platform and other supporting systems. Once all of this is put together, in theory, clinical teams will have access to a powerful 360-degree view of the patient throughout the clinical trials process—for all studies worldwide. With command of this type of data goals of patient safety, greater more targeted patient care and analytical insights become within reach. Ultimately supporting the mission for accelerating the development of efficacious and safe therapies. All of this must factor in, at each step of data collection, the legal and regulatory requirements (from different world jurisdictions) for data protection, privacy, and compliance.

Key Factors Include Requirements

Global pharmaceutical companies such as Bayer are complex, globally distributed organizations. This author has worked with Bayer (and many other “tier 1 pharma) on a major clinical trials technology initiative and big pharma’s history is littered with the failed results of big IT data projects. Pharma IT projects fail for a number of reasons for which we will not go into in this summary about Bayer’s Oracle mobile platform initiative. But requirements are a key factor. In the case of the mHealth platform for Bayer they needed to address four (4) distinct challenged including 1) data privacy and standardization 2) drawing in the large and diverse array of clinical trials stakeholders for buy-in (e.g. CRAs, statisticians, medical writers, CRO partners, investigators, and their staff, as well as patients 3) data capture (e.g. do we collect a certain data point or not) and 4) regulatory compliance (Bayer collaborating with federal regulators for inputs).

Medical Model Modernization

Bayer’s position is that clinical trials models that were developed in the 1960s in response to disastrous ethical failings (e.g. Thalidomide) introduced a lot of rigor, governance, and compliance and only minimal change in core process incremental change has occurred since then. Hence today clinical trials practice is reflected by a laborious, fragmented, often manual data entry with disparate data silos. Pulling data together from different silos can take months or even a year and this is undoubtedly a driver for new cloud-based models to emerge in clinical trials IT. The Oracle position is that driving toward a reality where a clinical trial system supports real-time data flow is a radical change. They are right it is and many of the underlying technologies used in global pharmaceutical companies are actually utilizing Oracle databases. With real-time access to ACCURATE data, the goals of greater patient safety improved productivity and deeper and richer patient engagement is in reach. Mobile technology helps as heretofore new ways to digitally engage with the patient are now feasible. A premise in all of this is that once a system such as this is up and running that costs will go down. Phase I-III adds some of the greatest costs to clinical research with everything from patient recruitment and site visits so if a fast and accurate system offers patients new ways to engage with the study without frequent inconvenient and costly trips to a site. Losing a patient is costly in this business. By embracing new technologies and using remote monitoring, in theory, the number of physical visits to the research site can be reduced and patients’ ability to have more ad hoc, on-demand interactions with the investigator could increase thereby increasing the probability that any one particular patient doesn’t drop from the study.

The Pilot

Bayer, Accenture, and Oracle will conduct a pilot of the new mHealth platform in a simulated clinical trial setting. The goal is to derive insight into all the process involved and ensure the data collected is usable by all participants (e.g. Stakeholders). Rolling this digital clinical process out won’t be easy—with 20 different domains within the company to consider. The goal is worth it for those driving the initiative—within the data are hidden signals that can help the organization transcend it’s today.

Uncharted Territory: Validating the Business Process

Information technology systems involved with drug development must be validated. This new platform will force Bayer to validate actual business processes—which is new territory for the Bayer team. The clinical trial process, from trial design and start-up through to trial endpoints, is a global and complex one and with a lot of regulatory oversight notes the Oracle author. Bringing this all together and verifying that the system (process) flows as is intended is complex and challenging. The goal in all of this notes Accenture consultant Louis Kauffman is the development of the “end-to-end digital clinical trials operating model.” In other words, how will the technology be utilized by the clinical trial sites and research teams and how will the data be utilized by Bayer, for example.

Cost Consciousness

The Bayer effort will undoubtedly be expensive. TrialSite News doesn’t have insight into that kind of proprietary data but rests assured we had experience peering into Accenture and Oracle projects. The two companies have a long track record of collaborating on major data-driven initiatives in big pharma. To be fair, often big pharma demands require layers and levels of service, oversight, and quality and hence the cost of doing business with “validated” data is high. The two spent several years implementing clinical data warehouses in global pharmaceutical companies. For example, a decade or so ago there were a number of large, costly and what was reported to be in some cases painful Life Sciences Hub aka Life Sciences Warehouse projects in global pharmaceutical companies. In some cases, we suspect these large programs yielded ROI (return on investment) but in some other cases, the results could be questionable. 

As pressure mounts to drive innovation (e.g. transform clinical trial models for greater patient safety and productivity) there will be various approaches and options to consider—and waves of vendor ecosystems marketing solutions. Many of the systems in big pharma were Oracle-based, developed in the 1990s or early 2000s and they are still there—in silos. New cloud companies have come in and sold the dream of easy access to seamlessly integrated functions in the cloud (e.g. Oracle’s biggest competitor Veeva or Salesforce) but there is no easy way to transform big pharma from the “as is” to the “to be” in regard to transformative data collection, management, and analytics powered by new devices available on the market. Oracle and Accenture offer the reader an option that should be carefully studied, contemplated and considered. A critically important element–the rapidly unfolding situation of mobile-enabled clinical research and how this impacts clinical trials not only today—but how the dynamic can be harnessed to transform how clinical trials are conducted in the near future—it is essential to shape a firm-specific vision, grounded in reality yet transformative– that propels groups forward with demonstrable results sooner rather than later.