Let’s face it: the drug development life cycle is lengthy and meticulous. The clinical trials phase alone takes years to complete. However, this pace is driven by necessity. Pharmaceutical companies need to establish safety and efficacy at each stage for every new therapy.
Still, everyone wants to reduce cycle times while adhering to regulatory processes and constraints. Patients eagerly await new treatments to improve quality of life. And for pharmaceutical companies, faster trials mean more time for you to turn strong profits.
This begs the question: where and how can we speed cycle times up? The processes for clinical research and trials are sprawling, which guarantees inefficient processes you can clean up. If you’re looking to shave months or even years off the process, focus on these common challenges ripe for addressing with end-to-end process orchestration.
From our perspective, truly digital-first processes are the next evolution of digital transformation for the life sciences industry. This means designing your processes with digital components (like automation) in mind from the start, rather than trying to digitize manual processes. We believe this is the next frontier and the only way the pharmaceutical industry will get the efficiencies and reductions in time to treatment we are all striving to achieve.
Sharing data within and across teams easily and in a timely manner is critical.
For many, sharing data is easier said than done. You might have one software solution to monitor study sites, another for document management, another for investigator management, and yet another to track protocol adherence and deviations, to name a few. Some groups might track information in spreadsheets, making data accessibility, auditability, and transparency an even larger problem.
Data silos don’t happen by design. Most of the time, companies choose a point solution to solve a specific problem—then they do that again, and again, leading to an accidentally disjointed IT architecture. These technology decisions inadvertently impact the business, causing highly valuable knowledge workers to spend time on low-value manual efforts, like switching between systems to find the data they’re looking for. This both increases the length of time it takes to complete a given task and increases the chance of miscommunications or errors, which is a compliance risk. Orchestrating communication and actions between your existing software solutions is critical to improve your overall efficiency.
Imagine it: Data surfaced to the people who need it, when they need it. And imagine it all in one data fabric with the ability to take action to kick-off the next step in the process. Rinse and repeat.
Technology develops quickly. Yet, the length of a given clinical trial often prohibits teams from accessing these advancements. If a clinical trial takes north of 7 years, the software chosen at the outset will inevitably be behind the times by the end. For example, artificial intelligence (AI) was fairly nascent more than a decade ago, but now some consultancies have shined a spotlight on how AI can help speed up clinical trial processes1. Upgrading to the latest tech can speed up processes, but can also come with some organizational heartburn when switching systems midstream.
Adding new software solutions mid-stream can add to an already chaotic IT environment. Interestingly, swapping out old systems for newer tech may be unnecessary. Enter the modern, cloud-based, low-code automation platform to enable interoperability and support your composable architecture needs. The right low-code automation platform will include a data fabric to help make connecting systems and sharing data much easier.
Imagine it: The ability to extend your existing investments by deploying applications that incorporate these process improvement technologies without disrupting the underlying functions of your existing technologies. You can maximize your investments while adapting to tomorrow’s changes with agility. Stop collecting and start connecting.
Clinical trials are made up of hundreds of smaller subprocesses. Each of these processes has inefficiencies that add up to prolong the overall trial.
Perhaps one of the bigger drags on the entire process comes from a lack of overall process orchestration. Too much is left to human intervention when technology could speed up the process. See, the processes in the pharma value chain are horizontal across teams, not vertical like our functions and technology systems. What we’ve been missing all along was a way to drive work through the process: a process-centric view of the world. A digital orchestration layer that sits on top of your existing technology landscape to orchestrate, extend, and process-enable actions quickly and cost-effectively.
Imagine it: a way to facilitate handoffs between people and functions, share information between systems when needed, and automate portions of the process that can be done more quickly by a machine. Then, you can focus on the high value activities that matter most.
With the exception of a widespread emergency effort like COVID-19 vaccine development, clinical trials will always take years to complete. But there’s still plenty of opportunities to speed up the clinical trial process. Any excess waste in the system translates into needless time tacked onto the process. Removing this waste can give you substantial extra time to be first to market and own the patent to earn more for your hard-won research. Best of all, you’ll get treatments to patients faster, significantly improving their quality of life.
Find out how a low-code automation platform can help across clinical site management, global experiment management, study startup, study execution, and more.
1. “Using AI to Accelerate Clinical Trials,” Deloitte. https://www2.deloitte.com/us/en/blog/health-care-blog/2022/using-ai-to-accelerate-clinical-trials.html (February 2022)