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A closer look at the most path-breaking enterprise cloud technologies, which have come about in the recent past, reveals that they are addressing either efficiency issues (time, cost or both), or a need which has been unaddressed or are solving for a latent need. Participants in the clinical trial industry have not been early adopters of technology – as compared to other industries such as BFSI, travel & transportation and many others. This is perhaps to do with the need for multiple levels of regulatory compliance in collecting, analyzing and reporting data related to clinical trials making the perceived risks outweigh immediate benefits.
The advantage of being a laggard has its own silver lining.
We can predict the evolution of technology in healthcare and life sciences industries much better and in fact increase the probability of success through insights obtained from other regulated industries such as BFSI.
Cloud-based technologies are not new to the clinical trials industry. Studies estimate that cloud computing solutions can lead to a 30% increase in speed to trial for clinical work, and can result in considerable cost savings (some estimates suggest savings of up to $400 million until approval). If the market continues to adopt ePRO/EDC technologies, paper studies and subject diaries could cease to exist in 10 years; and focus would shift to new opportunities and/or risk-mitigation via multitude of meaningful information – all accessible conveniently. As the availability, and abundance of data continue to increase, the kaleidoscopic nature of data would prove to be more insightful, when analyzed in combination with other data.
We are heading into a Future of cloud-based information paradigm in an integrated health & life sciences industry, and it has a lot to offer for holistic patient care.
Here are some of the changes which cloud-based technologies are likely to drive in the healthcare and life sciences industries, many of which are already manifesting in other industries.
BYOD policy is under active consideration by policy makers. The FDA requested suggestions on the use of technology in conducting clinical trials and specific questions around the usage of BYOD policies and compatibility between multiple devices. BYOD is a certainty in that the efficiency in collecting data, recruiting and retaining subjects it provides is high. Cloud will enable the usage of BYOD – by making data capture convenient and efficient and also solving for compatibility-related issues between multiple device types.
Most wearable technologies ranging from MCOT devices and other vital sign monitoring devices are leveraging a ‘smartphone-cloud’ technology to log a continuous stream of data and make it available for analysis. Clinical trial data so far has been discrete, i.e., various data points captured periodically during the course of a trial. The use of wearables enables clinicians to see a continuous stream of data and this has multiple implications:
It is a given that we would be dealing with a lot more unstructured data in the coming years than ever before. Another fact we need to reconcile is that the breadth and depth of analysis expected to be run on trial data would increase manifold. The combination of complex analysis requests on data which is significantly larger than what we see today implies that our cloud-based information architecture should be equipped to deal with this. Especially running multiple analyses on the cloud (since the data would be contained there), would require a new way to be architected. This is something one should be prepared for.
Practicing clinicians will vouch for the fact that they expect many collaborative studies to happen in the future. We are witnessing collaborative studies bringing pharma, genomics, and information sciences together. The same data would be used to run multiple analyses towards various end-objectives. Cloud easily enables that. The corollary which goes with this is the issue of multi-tenancy and compliance. Those working on cloud technologies would need to build in enough flexibility and security to enable collaborative studies, while ensuring that access to data for different collaborators is kosher.
The fact that the cost of bringing a blockbuster drug to market is increasingly becoming more steep and that is well understood and several attempts are on, to rationalize this cost. However, an area which offers a goldmine to new studies is how those involved in clinical development can learn from existing data, within their own organizations, partners, collaborators, institutions and from the internet. One can anticipate the emergence of collaborators who pool in data from multiple studies to draw from each other’s learning and avoid obvious pitfalls. This would be invaluable to further science, but also reduce risk and cost to bringing good science to market!
While #1 is an example of how cloud technology brings about efficiency, #2 through #3 are emerging needs which need to be addressed by technologists. #4 & #5 are those problem statements where the need is not acutely felt, but addressing these can lead to paradigm shifts in the way clinical trial analysis is done. For technologists and industry participants like myself, there could not be a more exciting time than this!
At MaxisIT, we believe that complex data analysis can produce simple yet powerful insights.
MaxisIT’s Clinical Trial Oversight System (CTOS) is a purpose-built command center designed to manage biopharma and life sciences clinical trials as mission-critical business processes. With its complete AI-enabled analytics platform, the CTOS enables “data-driven digital transformation” from data ingestion, processing, and analysis to in-time clinical intelligence. Its real-time data ingestion, analytics, and visualization empower researchers to identify and address errors as they occur.
The CTOS elevates the value of data, improves efficiency, and empowers clinical stakeholders to seize new opportunities. The platform brings clinical operations and patient data together in a single, central data hub as a single-source-of-truth to help clinical operations, clinical data management, biostatistics, and clinical R&D portfolio management.
A complete self-service, AI-enabled analytics platform, the CTOS unifies trial data from disparate eClinical systems to support study planning, clinical data quality, clinical review, patient safety, clinical operations, CRO performance, risk-assessment, portfolio management, compliance, and submission.
From study setup to data ingestion, clinical trial stakeholders can manage clinical development processes with insight into the study conduct and take proactive actions to reduce costs, mitigate risks, and ensure compliance.
MaxisIT’s CTOS helps you maintain an ongoing health-check on your portfolio of clinical trials, using real-time data, analytics, and visualization to drive rigorous analysis of the entire dataset, allowing for proactive trial risk management.