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The 2022 Crystal Ball: What the Next Year in Pharma Will Look Like

At the end of every year, I take some time to reflect on the previous 12 months. I look at trends that developed in the pharma trials industry, successes that seemingly came out of nowhere, and the “next big things” that didn’t quite materialize. It is always a fascinating process, and I am constantly amazed by the spirit of innovation that drives this industry year after year as all of us strive to create a healthier world for ourselves and for future generations.

Needless to say, 2021 was unlike any other year in recent memory as the entire global healthcare industry focused its efforts on a singular mission: controlling and eradicating the COVID-19 pandemic. This has upended many of the existing paths that the industry was on before any of us had ever heard of the novel coronavirus, and we are entering 2022 with more questions than answers. This is a perfect opportunity for all of us to reflect on the remarkable accomplishments of the last few years while at the same time also looking ahead to see what the future might look like.

I have asked a number of peers and colleagues in the industry to share their thoughts on what the next year has in store for the clinical trials sector. What comes through clearly is that there is a lot of optimism about what the future holds, but at the same time, there are a great number of variables that will ultimately dictate where we are going. In the spirit of collaboration and cooperation, I would like to share some of these observations and predictions.

Megan Dunham, Associate Director of Clinical Data Innovation at Jazz Pharmaceuticals

It’s all about innovation – we can never stop innovating. 80% of industry executives have named innovation as one of their top three business priorities, and well-recognized Silicon Valley ideas like “disrupt or be disrupted,” and “fail fast,” started becoming pretty commonplace in our corporate vernacular in the last few years. Unfortunately, clinical trials, despite themselves being the catalyst for innovation of medical treatment, have historically been innovation laggards. For a very long time, BioPharm has been able to get away with conducting trials without changing traditional methods for data acquisition, review, and submission. That’s no longer the case. What internal and external factors are driving us to innovate or ways of working with clinical trial data? One driver is the changing complexity and the introduction of novel clinical trial designs, as we try to bring drugs to patient populations faster. Patient-centric, precision medicine, real-world data and adaptive trial designs will all significantly reduce the risk of drug development and improve the success rate.

Nick Hargaden, Associate Director, Clinical Data Systems, Agios Pharmaceuticals

The clinical research industry generates amazing data, but sometimes it can be difficult to decipher it and to use it. One of the biggest trends that I see for the next year and beyond is the evolution of data visualization. In simple terms, everyone should be able to understand the information that clinical trials generate. This starts with curating reporting and dashboards. We now have reporting capabilities that go beyond Excel spreadsheets. The second piece of this is to build out the historical database for benchmarking to make sure that the platforms and processes can properly leverage the historical view of the data. The final piece of this is accessing additional data sources, which leads back to that idea of the operational data hub being used to identify and leverage the data that will help all of us use this technology to improve our governance, risk management, and compliance.

Igor Proscurshim, Vice President, Head of Clinical Development, Ichnos Sciences

It’s all about digital transformation. This is a term that people use a lot, and sometimes it’s overused a bit. But I think it’s an important tool for our industry. That’s because of the volume and velocity of data being generated by validated machines or devices, from key clinical data to operational data, we need to ask what the strategy should be to ingest and consume all of this information. This is especially true when handling unstructured data. So when you have high-velocity data, and when you are collecting data from patients directly using instruments or devices, you have large volumes of raw data. What should be the principle and the approach to bring it together for meaningful insights? It’s one that we’re starting, and we’re just scratching the surface right now. We’re going to have to create or transform that data into meaningful chunks, and given the volume of data being generated right now, the answer is that we’re going to have to figure out how to transform the flood of data into pieces that we can analyze. And that’s another set of tools that need to be developed because we have to be able to look at this data and be able to query it in a way that is meaningful. I think this is something that we’re going to start playing out over the next couple of years. It won’t take long.

Venu Mallarapu, Sr. Director & Global Head of LS R&D Solutions Group at Cognizant

I’m really focused on the automation of change management and business process, and any of these initiatives and transformations, and innovation as a whole, will have to take into consideration the people in the process as well as the technology aspects. And all of it would have to create change across the board for the change to be meaningful. Having said that, from a change management standpoint, some of the best practices that we recommend is, “do not ignore.” That’s the biggest best practice that is going to guide 2022 and beyond, Do not ignore change management. First and foremost, make sure that there is a workstream in your program that specifically addresses change management, which could be in terms of establishing the strategy overall and identifying the stakeholders – not only those who are directly impacted, but also indirectly impacted because they also need to have a say in the adoption at the end of the day. And then, having the right training and enablement strategy and a plan and having the right checkpoints as to how you’re progressing along the way, and governance, and then communicate. You can’t overcommunicate! Communicate what is coming to you, make sure you’re communicating up, you’re communicating down, you’re communicating across the enterprise as well. Because unbeknownst to you, you might be making changes that might impact them.

Steven Lesser, Vice President of Enterprise Solutions at Medable

It’s easy to focus on the science, but what really matters are the people. I think in the next year, you’re going to see a lot more of a focus on the participants in trials, not just on the data that those trials generate. If you think about it, patients who enroll in clinical trials are the true heroes of the pharma research community. Imagine a world where you can actually wrap a clinical trial around the patient experience and reap the benefits of having near-immediate access to the data and results that move therapies forward. But in order to improve data, quality, patient retention and recruitment, you need some real metrics that can be generated by a decentralized clinical trial. That’s only possible if you prioritize reducing the patient burden. A couple of years ago, I got very excited about entering into this space specifically instead of just being on the periphery. And because I think there’s every stakeholder has something to win here. I think if we do our jobs right collectively as an industry, clinical trials get better. And then, all of the stakeholders actually have a better experience.

Ted Snyder, Director of Clinical Informatics at Praxis Precision Medicine

Data needs to be aggregated from multiple sources. This is nothing new, of course, but it is especially important now, and I believe it will be a major trend over the next 12 months. A lot of the work that we conduct running our trials is outsourced, so the information isn’t just coming from our own research. That’s why we need a tool to bring information from disparate sources together under one roof. Throughout my career, I’ve used a lot of different approaches, and I’m a big believer in automation and having a central system for handling everything together. Part of this is having prebuilt visualizations and dashboards so that research scientists can quickly find the information they need rather than forcing them to look for needles in haystacks. Every company in the industry has to manage a massive amount of clinical data, and the material needs to be treated in a particular way so that organizations can use it to develop effective therapies. This trend is only going to accelerate over the next few years.

As you can see, the future is taking shape in a number of new and exciting ways. Existing paradigms will still exist, of course, but evolutions in technology and improvements in data analysis and visualization are creating new ways to help Pharma companies benefit from clinical trials and accelerate the development of promising new therapies. There is no single “magic bullet” that is going to magically transform the clinical trials industry, but as we all embrace new technologies and recognize the need for radical innovation, I think it’s safe to say that the future is a bright one for all of us. And that benefits everyone.

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