Unlock Data for Clinical Trial Analytics with MuleSoft and AWS

Blog guest contributing authored by Ryan Stastny, Product Manager at MuleSoft

Clinical trials are highly complex, lengthy, and expensive. They require effective collaboration among many key stakeholders including subjects, sites, sponsors, contract research organizations (CROs), and government agencies. However, the data needed to drive successful outcomes is often siloed and inaccessible where and when it is needed most.

By combining the power of MuleSoft’s Accelerator for Life Sciences and Amazon Web Services (AWS), life sciences organizations can integrate and surface data from disparate sources ultimately leading to more efficient and faster clinical trials.

Current state of the market and its challenges

Life sciences organizations stand at a crossroads of unparalleled opportunity and increasing costs. On the one hand, these organizations are aiming to capitalize on potential high growth areas, such as targeted therapies. The volume of clinical trials is at an all-time high. In the United States, for example, the number of trials registered with the Food and Drug Administration has increased by 310% over the past 10 years.

While the opportunity for growth is strong, product development costs continue to rise. According to a study performed by the Tufts Center for the Study of Drug Development, over the past 10 years, per-drug research and development (R&D) costs have increased at an average of 8.5% per year above inflation. This brings the estimated average out-of-pocket R&D cost per approved new compound to more than $2.8 billion dollars.

Increasingly life sciences product development has skewed away from the commercialization of mass-market blockbuster drugs toward personalized drugs. The challenges of the R&D cost only grow in magnitude because of this shift towards targeted therapies, which have a smaller addressable market to capture.

Downward price pressures, driven by private payors and government regulations, further exacerbate this challenge. The combination of increasing costs and downward price pressures have forced a paradigm shift in how life sciences organizations seek to run clinical trials, and the role that technology must play to support business strategy.

Solution

MuleSoft, a Salesforce company, provides integration software for connecting applications, data and devices.

MuleSoft’s Accelerator for Life Sciences, in conjunction with AWS, unlocks critical data for analysis and allows sponsors and CROs to run more efficient and intelligent clinical trials.

MuleSoft Accelerators for Life Sciences adds value to customers in three domains:

Makes implementation faster and easier.
Offer customers building blocks that can be easily extended and modified to serve specific customer requirements.
Represents a best practice approach for customers to mimic as they embark on their MuleSoft development journey.

This solution enables organizations to unify reporting and build visualizations to support their analysis of study components, including study milestones and subject outcomes. With near real-time access to this information, trial operations teams are better equipped to take appropriate and timely action to accelerate a successful trial.

Ultimately, pharmaceutical companies and their stakeholders will be able to launch new drugs and treatments faster.

Partner solution/customer deployment using AWS

MuleSoft’s System APIs and implementation templates surface clinical trial data from Veeva CTMS (Clinical Trial Management System) and CDMS (Clinical Data Management System).

The surfaced data can be stored in Amazon Simple Storage Service (Amazon S3) using the provided MuleSoft AWS System API. Amazon S3 is an object storage service which provides industry-leading scalability, data availability, security and performance. There is no minimum charge to use Amazon S3. You pay only for what you use.

Customers leveraging Amazon S3 can use Amazon Athena (Athena) to organize and prepare trial data for visualization. Athena is an interactive query service that makes it straightforward to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Amazon QuickSight allows organizations to better understand the trial data in Athena by asking questions in natural language, exploring it via interactive dashboards, or identifying patterns and outliers powered through machine learning. The solution also provides options for reporting through Tableau.

“When our team was exploring options for our customers to store and consolidate critical clinical trial data, AWS was chosen due to our organization’s strong partnership and its proven ability to scale and secure sensitive information. We are excited to provide the Accelerator for Life Sciences to accelerate our joint customers’ efforts with this set of key integrations.”―Ryan Stastny, Product Manager at MuleSoft

High-level architecture

The following diagram represents the workflow portion of the overall solution as it pertains to clinical trial analytics.

Fig 1 – High Level Architecture of the Workflow

Workflow

Here is an example workflow to walk through: A Clinical Trials Operations manager needs a report including study data, such as subject status, across different sites. They seek help from their IT operations staff to surface the relevant data from Veeva.

The IT operations staff triggers the initial full load and schedules the subsequent delta loads to sync the data from Veeva.
A job is created within Veeva to prepare the study data extract.
After the job status is confirmed as successful within Veeva, the study data is written to the target system. If the target system is Amazon S3 storage, MuleSoft’s Amazon S3 Connector is used to streamline data into an Amazon S3 bucket.
If the target system is Tableau, the study data is uploaded as a file to tableau server.

Steps 5-9 are extensions to the MuleSoft Accelerator for Life Sciences that will be executed in customer’s AWS account.

An AWS Glue crawler scans the data from the Amazon S3 bucket and populates the AWS Glue Data Catalog with tables. Users can find and access data using the AWS Glue Data Catalog. It automatically infers schema, format, and data types from the Amazon S3 bucket. AWS Glue is a serverless data integration service that makes it straightforward to discover, prepare, and combine data for analytics, machine learning, and application development.
You can schedule the crawler to run at regular intervals to keep metadata, table definitions, and schemas in sync with data in the Amazon S3 bucket. The crawler automatically detects new partitions in Amazon S3 and adds the partition’s metadata to the AWS Glue table.
Amazon Athena is used to perform the following actions:
1. Uses the table populated by the crawler in AWS Glue Data Catalog to fetch the schema.
2. Queries and analyzes the data in Amazon S3 directly using standard SQL.
Amazon QuickSight uses the Amazon Athena Connector to import the Amazon S3 metrics data for building data visualization.
After the study data is available in either Amazon QuickSight or Tableau, the Clinical Trials Operation manager can generate the required report and share dashboards with other users.

Fig 2 – Sample Dashboard of a Clinical Study

Results

Beyond the broader benefits of the API-led connectivity approach, this solution provides the following benefits to its users:

Unlock clinical data across stakeholders: You can surface insights across sponsors, CROs, site and subjects to streamline coordination and consolidate study information into a single place.
Establish a future-proof foundation: By developing reusable integrations into core clinical trial systems, like Veeva, organizations can onboard future projects faster versus starting from scratch for each subsequent requirement.
Accelerate clinical trials and increase likelihood of success: This unified and near real-time approach to reporting allows organizations to analyze trends, identify issues and take appropriate actions faster, ultimately making clinical trials more efficient.

Conclusion

Clinical trials are complex, lengthy and incredibly costly. Data required for effective collaboration across the stakeholders is often siloed and inaccessible. With the MuleSoft Accelerator for Life Sciences, in conjunction with AWS, organizations can overcome the challenge of siloed data sources through pre-built integration assets. This solution surfaces clinical trial data from Veeva CTMS and CDMS, and the data can be persisted at low cost in Amazon S3. Furthermore, Amazon QuickSight or Tableau can be used to visualize the data and share dashboards. Through the power of MuleSoft’s Accelerator for Life Sciences and AWS, life science organizations can increase the efficiency and effectiveness of clinical trials.

The Mulesoft Accelerators are a set of pre-built assets and blue prints designed as modular building blocks. You can contact our partner MuleSoft to learn more about their Accelerator for Life Sciences.

AWS offers workshops designed to support and facilitate the development of Life Sciences solutions on AWS. Reach out to your AWS Representative to learn how you can get started with and leverage AWS services.

You can learn more about the AWS Life sciences solutions from our library.

About MuleSoft

MuleSoft helps organizations change and innovate faster by making it easy to connect applications, data, and devices. The company’s Anypoint Platform of integration products is designed to integrate Software as a Service (SaaS), on-premises software, legacy systems, and other platforms. With its API-led approach to connectivity, MuleSoft empowers over 1,400 organizations in approximately 60 countries to build application networks. By unlocking data across the enterprise with application networks, organizations can easily deliver new revenue channels, increase operational efficiency and create differentiated customer experiences.

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Ryan Stastny has 7+ years of experience in the IT industry spanning a number of technology categories across multiple functions including sales, customer success and program/product management. He is currently responsible for identifying the top challenges facing MuleSoft’s healthcare and life sciences customers and developing solutions to accelerate implementation of their most common integrations.