Almirall’s innovative streak has served it well as it adapts to the continuous transformation of the pharmaceutical industry. Diego Herrera, Almirall’s Head of Global Data Management and Project Information, and Merce de Frias, International Clinical Trial Manager, are on the front lines of this transformation.
Customer Story
Innovations in clinical research offer opportunities and challenges
How Almirall built a new data management standard that has dramatically streamlined data and medical monitoring and regulatory compliance across a network of study partners in Europe and the US
Almirall
| Challenge | Rapid growth in the clinical research industry requires innovative approaches to data analysis. |
|---|---|
| Solution | Use JMP® Clinical to implement targeted data review approaches that address regulatory requirements and ensure patient safety. |
| Results | Global data governance standards have helped Almirall grow efficiency across its study teams while also relieving the regulatory burden of reporting in the face of increasingly stringent requirements. Integrated data management plays a key role in enabling the support of Almirall strategies to expand into other markets. |
After years developing innovative products in the respiratory area, Almirall has become a leading skin health-focused pharmaceutical company. Today, Almirall uses its global network of 13 affiliates and strategic partners to bring novel products to consumers across the world. This innovative collaboration with health care and aesthetics professionals, both public and private, is key to Almirall’s strategy; by working with partners, its reach extends far beyond its size.
Almirall’s innovative streak has served it well as it adapts to the continuous transformation of the pharmaceutical industry. Diego Herrera, Almirall’s Head of Global Data Management and Project Information, and Merce de Frias, International Clinical Trial Manager, are on the front lines of this transformation, as they develop new strategies for meeting the needs of high data quality and regulatory bodies alike.
Patient-centric research offers opportunity and challenges
With improvements in technology and clinical research interest in new tools for managing clinical trials, researchers have begun to tap into the wealth of data that continues to become available. Whether from wearable devices, telemedicine or digital patient engagement, maximizing the utility of this data is a top priority in clinical research. Often used in combination with more traditional research methods, new patient-centric approaches to research – and health care in general – have expanded the quantity of data collected and the pool of potential study participants. A broader picture of each participant’s response to a study’s investigational product (IP) is invaluable to determining safety and efficacy, as well as giving study teams more data from which they can detect outliers, see patterns and identify risks. “The good thing is that as you have more data, then you have the possibility to select what you want to get,” explains Herrera. “This means that you can obtain more knowledge about the product you are running.”
On the other hand, the sheer quantity of data can present challenges for clinical researchers. “Hyperinformation can generate problems in the decision process since more information does not imply better decisions directly,” says de Frias. “A large amount of data requires additional advanced technologies and capacities to perform data scrutiny.” For a company that reviewed data using PDF listings until 2011, a higher volume of data was not necessarily a boon to study teams or a signifier of better outcomes. For small, early phase clinical trials, this time-consuming data review process was more manageable, but for large, pivotal studies that include hundreds of patients, reviewing data patient-by-patient is a non-starter.
“You need something that aggregates all the data and allows digitalization,” de Frias says. As a data management professional, Herrera agrees: “It’s very important to have advanced technology solutions and criteria in order to scrutinize what is relevant for this large amount of data. You have to have good tools to analyze this data. Otherwise, you are lost.”
Complying with growing regulatory demands
In parallel with increases in data volume, regulatory demands have likewise increased, resulting in growing costs and extended timelines. Already a highly regulated environment from the international to the local level, the pharmaceutical industry must continue to adapt to the need for data quality, transparency, patient data privacy and the integration of new technologies.
But how can researchers balance these competing priorities? “More and more, health authorities are asking sponsors to work in risk-based management, identifying where we have the risk and where are the critical steps [so that we] can focus on them instead of supervising and overseeing the whole process,” de Frias explains. Following a risk-based monitoring approach lets clinical operations teams concentrate their efforts and resources on variables with the highest potential impact on the study, while maintaining high data quality and ensuring patient safety. To facilitate this process and comply with regulatory requirements, the right tools are key.
“We felt that JMP Clinical would provide Almirall the data management possibilities [we needed] without requiring additional data transformation from the CROs to deliver integrated patient data access to clinical teams efficiently not only during the study but also when exploring data retrospectively.”
– Diego Herrera, Head of Global Data Management and Project Information
Efficient data review with JMP® Clinical
In considering their options, Herrera says, “We felt that JMP Clinical would provide Almirall the data management possibilities [we needed] without requiring additional data transformation from the CROs to deliver integrated patient data access to clinical teams efficiently not only during the study but also when exploring data retrospectively.” The bottom line, he adds, is that JMP Clinical would help them “save on cost and time in the data access process and extend patient data re-use along the clinical development life cycle.”
Since implementing the software, the Almirall team has transformed how they review data, allowing them to explore risk-based monitoring and collaborate effectively. “JMP Clinical allows us to analyze a large volume of data,” de Frias says. The aim of analyzing all this data is to ensure data quality and identify areas of risk. “Again, in a risk-based approach, where do you have the risk? In the outliers. We see why they are outliers and how you can solve issues and which actions we need to perform.”
JMP Clinical’s capabilities allow Almirall’s clinical and data management teams to thoroughly review the data in early stages of the clinical trials for early detection of patient data issues or deviations from the protocol, enabling them to make decisions where appropriate. They can also set up alerts for parameters of interest, a critical tool that lets them quickly address problems – like adverse events, for example – at the site level. “If you notice one site with a high rate of PDs or outliers, this may trigger an audit, and if results indicate that the quality is not good, you can decide to exclude subjects from the analysis population,” says de Frias. This adaptive study design approach can lead to protocol amendments or require regulatory authorities be alerted depending on the particular safety issue, so the alerts and documentation afforded by JMP Clinical’s Notes feature have relieved the regulatory burden on Almirall.
Visualization also played a large role in encouraging Almirall to switch to JMP Clinical. “We were looking for options to visualize the data in an efficient way,” says Herrera. “An integrated way [that is] interactive and allows the people to explore, visualize and get more sensitive data... We found JMP Clinical to be the best.” These dynamic and interactive visualization features give clinical teams the resources to conduct internal analyses on patient data during the review, to respond to regulatory questions, and reduce programming costs throughout the process.
“JMP Clinical allows us to analyze a large volume of data. In a risk-based approach, where do you have the risk? In the outliers. [JMP Clinical allows us to] see why they are outliers and how you can solve issues and which actions we need to perform.”
– Merce de Frias, International Clinical Trial Manager
Using Notes sharing architecture to facilitate regulatory compliance
Clinical study teams include individuals from various functional areas, including data management, clinical operations, biostatistics, safety and medical, with varying levels of comfort using statistical analysis or software. While Almirall has dedicated clinical biostatisticians to support study teams, any software they use must be user-friendly enough to allow study teams to conduct reviews, visualize data and share ideas and findings. JMP Clinical not only gives study teams the ability to quickly and easily create custom reports for the needs of each functional area, it provides a sharing architecture that lets reviewers assess data separately and then compile all notes into a single integrated file using the Notes feature.
As a sponsor, Almirall is required to document how they provide oversight of the study; JMP Clinical’s Notes feature confirms that the sponsor has appropriately monitored the safety of patients during the trial, supporting any inspections that may occur in the future and justifying the need to set up new risk-based monitoring approaches. For example, if a certain parameter has shown no safety risk, the study team may decide to source data verify a percentage of patients instead of all patients. When regulatory inspectors ask for justification, the study team can show the reports and notes that led to the decision.
Evolving alongside the clinical research industry
As the clinical research landscape evolves, so does Almirall. The company continues to build on lessons learned from its portfolio, and its use of JMP Clinical is no different; having requested a few customizations from JMP to better align JMP Clinical with regulatory body expectations, Almirall has recently set up and is running a new process of bringing pre-clinical (SEND) and clinical (SDTM) data together in one unique and collaborative data governance process. Furthermore, Almirall’s clinical data management team is now exploring with their colleagues from pre-clinical research how to develop and extend the use of JMP Clinical’s visualization capabilities. As a result of this collaborative project, global data governance standards will enable them to expand the use of data, allowing the generation of new hypotheses and compliance where regulatory bodies like the US Food and Drug Administration require that data from all phases of research to be integrated and submitted into a standard format. In addition to streamlining the collection and presentation of data, these standards allow Almirall to make the most of what JMP Clinical has to offer, visualizing and evaluating pre-clinical and clinical data throughout the project development process.
The results illustrated in this article are specific to the particular situations, business models, data input and computing environments described herein. Each SAS customer’s experience is unique, based on business and technical variables, and all statements must be considered nontypical. Actual savings, results and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software.