Change is the lone constant you can depend on. When it comes to scientific discovery, most of that change – whether it be in smart phones or space travel – has led to greater achievements and efficiencies. Among Clinical trials, however, efficiency continues to be a challenge. Clinical development success rates have fallen to their lowest level in more than 10 years, to an average 5% likelihood of progressing successfully through all phases to approval.
Clinical trials are – and always have been – lengthy, expensive, and prone to failure. On average, it takes 10 to 15 years to bring a new treatment from discovery to medicine cabinet, a process that costs an average of $2.6 billion. From 2009 to 2019, the rate of return on late-stage drug development pipeline fell from over 10% to less than 2%, while the number of Good Clinical Practice (GCP) inspections that resulted in at least one critical finding grew from 4% to 50%.
Clinical teams are under an immense amount of pressure. They need a solution to ease the burden on patients, site personnel, and sponsor teams whilst improving GCP compliance, increasing efficiency, and managing cost.
The solution lies in the crux of what has changed most dramatically since the 1990s: technology. All Clinical teams are working with some form of technology today, but it’s often homegrown and/or outdated, disconnected, and requires teams to manually migrate data across key applications, forcing teams throughout the organization to work in silos.
Some technology providers attempt to solve this fragmentation using a closed system, locking customers into a proprietary ecosystem. More recently, technology vendors have begun offering open-architecture solutions, which are able to share data with any solution, whether it’s from the same vendor or not. Open-architecture solutions give organizations more flexibility when it comes to connecting their clinical platform.
Connected clinical platforms deliver a common user experience and easy third-party integrations to maximize the potential of each solution, from CTMS to eTMF, EDC, RTSM, and more. The result is optimal performance and efficiency.
When these connected systems share data and documents across a single platform it empowers teams to manage the challenges of modern clinical trials more efficiently, ensuring compliance and data security while laying the groundwork for advanced automation.
Shared Data Models Increase Efficiency and Provide Deeper Insights
The most challenging part of building a connected clinical platform is creating shared data models. Shared data models are key to delivering on the promise of a connected clinical platform: bringing more coherence to clinical data is the primary reason most organizations look to a single provider for connected, open-architecture solutions. These platforms enable teams to enter data once, then seamlessly and instantly share that data across applications. This information can be accessed from any system via a central, curated clinical data repository saving time and allowing for improved reports and dashboards.
This method of sharing a consistent data model across applications significantly increases the efficiency of the Clinical lifecycle. For example, consider the advantages of global search capabilities: connected systems have been shown to deliver search results 35% faster by searching both metadata and content for keywords, so your team can spend more time on the work that matters, and less time digging for documents or data sets. Similarly, information can be quickly pulled from other applications when completing reports: one company using LifeSphere Clinical reduced time to complete clinical site monitoring trip reports by 30%.
Connected Clinical Solutions Eliminate Repetitive Busy Work and Empowers Clinical Operations
Imagine deploying a study with just a few mouse clicks. Technology that handles repetitive busy work with reliable automation. An enabled team focused on the big-picture, strategic initiatives, not distracted by unique user experiences. A connected, relatable Clinical platform from a single provider can transform your clinical operations. As a more practical example, technology could feed design elements from study planning and build environments directly into trial conduct environments, logically separating development, test, and production phases — empowering teams to focus on what matters.
The benefits of data sharing extend beyond your organization, too. A connected platform makes for stronger collaborations with external partners: pre-built data gateways, powered by an open API, enable easy data sharing between CROs and sponsors, biopharmas and regulatory authorities, and any other system or service up- or downstream of the internal trial system.
Connected Teams Break Down Silos
These clinical platforms connect more than the various applications your organization uses – they connect the teams who work within those systems using shared authentication. A common user experience delivers simple and direct communication within solutions that are part of the interconnected platform. Clinical teams stay better aligned with tasks and workflows, both within their own function and across Clinical roles. Better alignment across teams will make for a more efficient Clinical team and enhanced collaboration.
Additionally, advancements in data and analytics are making it possible for teams to further integrate data and processes, to deliver deeper and more timely clinical insights. By breaking down silos preventing bringing data together from multiple sources, curating it, and acting on the results of analyses conducted, teams can more proactively be more efficient, while avoiding bottlenecks and issues – all in service of driving better clinical outcomes. Our partnership with Snowflake is an example of how we are actively moving on data analytics across the LifeSphere platform.
Artificial Intelligence is a Game-Changer, but is Only as Good as its Data
For years, the life sciences industry has been promised that artificial intelligence (AI) would pave the way toward bigger, faster breakthroughs and more efficient research and development. While there is truth behind that promise, the fact is that AI is only as powerful as the data it has to work with. Connected clinical platforms with shared data provide the critical foundation for powerful AI.
AI learns by analyzing enormous databases, which means it can have blind spots when it comes to the types of data it’s never seen. For example, a system that had primarily been trained on identifying skin lesions with images of white patients had only half the diagnostic accuracy that its creators claimed when tested on Black patients. It’s a common misconception that this problem can be fixed with more data, but in reality, the AI needs more diverse data sets to draw from.
Connected clinical platforms position organizations to truly benefit from AI by providing full access to data and healthy governance. Advanced data management methods govern the information held in a data lake or warehouse, ensuring the AI has access to a wealth of data across studies, trials, sites, and countries.
AI has the potential to deliver deeper insights by identifying patterns across trials and sites, delivering automatically produced visuals and graphics, and processing enormous data sets. This empowers Clinical teams to work more strategically. Take an example: when a risk-based monitoring approach uses remote site monitoring, the organization can use smaller monitoring teams and make fewer site visits. Rules-based data, analyzed by the AI, can flag outliers or events to indicate the need for a review, so risks are caught and mitigated and site monitoring is enhanced.
Cloud Technology Keeps Organizations Nimble
Native cloud technology is the backbone of connected clinical platforms. It provides for seamless connections among various applications and keeps them connected as data migrates to the cloud. Cloud technology also ensures these apps stay up-to-date and allows for organizations to quickly take advantage of the latest software updates, which may include new workflows or capabilities. new cloud-native technology.
Cloud technology also allows Clinical teams to operate more freely. Operating in the cloud makes decentralized or hybrid trials possible, and the increased technological mobility improves the patient experience. Plus, Clinical teams have immediate access to all information from key applications – CTMS, EDC, eTMF, and so forth.
A single platform built in the cloud mitigates IT woes and minimizes training across the company too, as it ensures that cross-functional teams are working with the same technology interface. Cloud technology has further benefits when it comes to maintaining compliance, using specific permissions for data input, automatic compliance checks (think spell check, but for GCP) and more.
Greater Collaboration Benefits All
To truly work as a team, teams need to be on the same page, with access to the same information and a single source of truth. Unifying your operations on a robust Clinical platform makes for stronger working relationships both inside and outside of the organization, better data governance, deeper insights, and more time to focus on strategic initiatives, all while maintaining compliance.
Learn more about boosting cross-functional collaboration through our new eBook, which explores revolutionized eTMF technology.