AWS for Industries
Executive Conversations: Streamlining Clinical Trial Submissions in the Cloud
The success of pharmaceutical and biotechnology organizations rests on their ability to bring new therapies to market, which requires submitting clinical trial data to regulatory agencies. However, it involves massive quantities of data and significant manual labor. To automate and optimize the process, life sciences organizations are leveraging curated solutions powered by the cloud—affording them more time for innovative, value-generating tasks.
In this Executive Conversation, Asha D’Souza, Principal Healthcare and Life Sciences (HCLS) Industry Advisor at Amazon Web Services (AWS), speaks with Debbie Profit, Vice President of Clinical Management and Applied Innovation at Otsuka Pharmaceutical, to discuss the potential of cloud technologies in streamlining clinical trial submissions to regulatory bodies.
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Asha D’Souza: Hello and welcome. To get us started, could you speak about Otsuka Pharmaceutical’s mission and your role in the organization?
Debbie Profit: Otsuka’s mission is to create new pharmaceuticals to serve patients with unmet medical needs, focusing on three areas: neuroscience, nephrology, and digital innovation. Our digital innovation arm addresses the challenges of those living with serious mental illness, by enabling them to engage and communicate with their care teams in new ways.
At any given time, Otsuka has between 60 and 100 ongoing clinical trials, many of which are outsourced. As Otsuka’s VP of Clinical Management and Applied Innovation, I spend a lot of my time thinking about how we can future-proof our clinical trials, and make them more efficient and patient-centric.
AD: Clinical trial submissions to regulatory agencies are a critical milestone in bringing new therapeutics to market. How has the process evolved over the years?
DP: Part of the problem is that processes have not evolved fast enough. Despite a shift from paper to electronic submissions now required by regulators, the current submission workflows are manual, costly, and slows the ability of the trial sponsors to get their therapeutics to the market faster.
The industry needs to understand that clinical trials have changed. Outside the traditional settings, we are capturing a huge amount of data remotely from patients using sensors, wearables, patches and smartphones, for example. Then, there are companion diagnostics. While clinical trials have always involved data, we are working with—and will continue to work with—exponentially more of it. Yet, we are still relying on legacy processes to manually compile it, gather insights, and report. This is unsustainable in the long term.
AD: What are some of the challenges with manual regulatory submissions? Where are the major pain points and friction?
DP: The submission process is time-consuming, and it’s reactive rather than proactive. A best-case scenario timeline for submission is between four to six months, which is a long time for patients to wait. It’s reactive in that life sciences organizations only start to think about gathering what the regulatory agency needs in their phase three study, versus thinking about how to correlate submissions downstream from day one. We at Otsuka are refining that process internally by thinking about how we can incorporate automation to prepare for a simultaneous submission. I think the entire industry should do this, to remove the undifferentiated heavy-lifting.
The current process is error-prone, since it involves a lot of cutting and pasting, from one format or document to the next. This creates risk of error. We need technology to facilitate speed with quality—not only to take away the administrative burden, but also reduce the risks associated with human error and improve the overall time to market.
AD: How do you see cloud technology, and AWS in particular, transforming the clinical trial analysis and regulatory submission process for both Otsuka and the industry?
DP: In the last few years, the industry viewed technology as a tool to create trial efficiencies. We now need to shift gears to leverage technology to enhance the experience of trial participants, and streamline submissions to regulatory authorities so we can ultimately get our therapeutics to patients faster.
We’ve been working with a multi-functional team at AWS to understand all the ways cloud technology can accelerate the submission process, be more cost-effective, and improve quality. Automating manual processes around quality control that don’t require a human touch, for example, not only saves time but also removes human error. We can use automation to roll data from one phase to another, and then centralize it, which will allow us to work with large volumes of data in less time. Working backwards, we’re also thinking about how cloud technology can help us prepare the data for analysis once its stored, in a way it is both secure and accessible.
AWS has been a great partner in enabling us to make data-driven decisions in meaningful ways. They look at every step that’s involved, as well as who does what, and when they do it. That’s important because implementing technological change also requires people to change how they do their jobs.
But, ultimately, it’s about the mental model, and getting all stakeholders together and aligned on what the change will look like. Many times, organizations hesitate as they feel that the technical part is the hardest, but I would say no—the people and processes part is the hardest. Everyone loves progress, but no one likes change. My advice to other organizations looking to automate and streamline their regulatory submissions process is to look at all these three aspects holistically—people, processes, and technology.
AD: What new opportunities do artificial intelligence (AI), machine learning (ML), and internet-of-things (IoT) present to stay competitive in this heavily regulated world of trial submissions and extracting insights from the data?
DP: AI, ML, and IoT can help us learn quickly and at scale so that our submissions achieve a higher probability of success. For example, we can use machine learning to analyze feedback we’ve received on previous submissions from global agencies over time. AI can learn from feedback that’s come in three times, and flag it so that we don’t overlook that feedback a fourth time. Previously, all this knowledge would be confined to people’s heads. Using technology, we are able to reference this historical data, including international submissions from years prior, to really improve our success rate on a global scale. The more we can reduce feedback, the faster the agency can get it to us, and the faster we can get a product to market that will help people.
Another opportunity is how NLP [natural language processing] can complete sections of the dossier for submission, by pre-populating standard information into the final clinical study report or final data cleaning by ML methods. I strongly believe infusing AI, ML, and IoT, for the right purpose, can help us get a differentiated, competitive edge over rest of our industry peers.
AD: Clinical trial data transparency is a big focus for Otsuka. How can cloud technology empower transparency along with data privacy?
DP: Cloud technology facilitates a thorough data management strategy, data governance and logging, and allows the right people the right access to the right data in one place, no matter where they are. As a global company serving a global market that follows different regional regulations, it is crucial that our team have open access to summaries of clinical study reports while remaining compliant in any location. Not only does the AWS Cloud accommodate high volumes of data in one place, but it allows us to format it effectively. This helps us stay compliant with regulations pertaining to request response times, for example.
AD: What do you think the future of clinical trials look like?
DP: On the back end, we are going to see further democratization of access in terms of being able to go where the patient data is, whether that’s the local pharmacy or their home or the doctor’s office—and we’ll be able to access that data in as near to real-time as possible. On the front end, we’ll see expanded access to telehealth and communications through various devices, which will enable us to make our trial flexible and agile and allow for greater diversity of patients. This will help us meet regulatory requirements, protect the integrity of our data, and have faster and easier access to patients while relieving them of the burden of an inconvenient in-person visit. Ultimately, that increases retention. This is going to change Otsuka and, eventually, accelerate the R&D pipeline across the entire industry. We are seeing more adoption of modern technology architectures, and for that reason the future is bright.
AD: Absolutely, clinical trials are complex, and very complicated because so many people touch it. I am excited to see where Otsuka and AWS land together as we head into the future. We look forward to what we know will be a positive outcome for not just us, but for patients and for the industry. Readers who are interested in hearing more about how AWS is helping pharma companies streamline their clinical trials, please visit the AWS for Health website.
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Debbie Profit is the Vice President, Clinical Management and Applied Innovation, at Otsuka Pharmaceuticals. She has spent 21 years across different leadership roles at Otsuka Pharmaceuticals, spearheading initiatives around using technology to drive organizational transformation. She is passionate about using technology as an enabler for improving patient outcomes and experience, and advocating for bringing much-needed changes to the antiquated clinical trial process to make it future-ready.