We implement cloud data warehouses and migrate data warehouses to the cloud for a number of biotech and pharma companies. The key to an effective implementation is ensuring secure and fast data access across devices. Whether your clinical trial data needs to be accessible by a mobile salesforce or global partners, it’s essential the right solution works seamlessly across platforms, operating systems, and devices. Read more.
How do I use a cloud data warehouse for clinical trials?
Using a cloud data warehouse for clinical trials enables data gathering and access that simply wasn’t available even 10 years ago. With the proliferation of mobile devices and connected devices, a clinical trial can access and interpret information that is exclusive to your trial and combine it with other data sources.
Per Amazon Web Services: “Using mobile technologies with traditional technologies in clinical trials can improve the outcomes of the trials and simultaneously reduce costs. Some of the use cases that the integration of various technologies enables include these:”
- Identifying and tracking participants in clinical trials
- Identifying participants for clinical trials recruitment
- Educating and informing patients participating in clinical trials
- Implementing standardized protocols and sharing associated information to trial participants
- Tracking adverse events and safety profiles
- Integrating genomic and phenotypic data for identifying novel biomarkers
- Integrating mobile data into clinical trials for better clinical trial management
- Creation of a patient-control arm based on historical data
- Stratifying cohorts based on treatment, claims, and registry datasets
- Building a collaborative, interoperable network for data sharing and knowledge creation
- Building compliance-ready infrastructure for clinical trial management
What is a cloud data warehouse?
A cloud data warehouse is simply a place to store data. Data warehouses allow businesses to store and share data for sales funnel processes, data analytics, and reporting. A properly structured and implemented data warehouse becomes a “single” repository for all data, allowing datasets to “talk to each other”. This connected data allows businesses of any size to discover new data insights that could lead to additional revenue.
Data warehouse architecture has been moving to the cloud, from on-premise data warehouses, because of several huge advantages:
Cloud data warehouses simply cost a lot less. Why? Generally, there are no licensing costs, nor longterm contracts. Plus, because it’s a cloud, there’s no hardware to buy, nor maintain. And lastly, you pay less when your data storage needs are small — then you pay incrementally more as your data storage needs grow.
Generally, a cloud data warehouse grows with your data needs. As you have more data to store, or as you add new applications, your cloud automatically grows.
A more modern data warehouse architecture allows cloud data warehouses to process complex queries much faster. This is in part due to MPP (Massively Parallel Processing), and other modern data warehouse elements.
A cloud data warehouse can theoretically be implemented in minutes. Whereas, a traditional on-premise data warehouse could take weeks or months to build.
Is it common to use cloud computing for clinical trials?
Yes, it is now commonplace to use a cloud data warehouse for clinical trial data storage and gathering. In fact, one reason the number of registered studies has grown 250x in the past twenty years is because of the proliferation of cloud data warehousing.
What are the advantages of a cloud data warehouse for clinical trials?
Decreasing costs and a faster research and development process are the clear advantages of a cloud data warehouse. Generally, our clients are shocked by the ease with which cloud data can be shared across platforms and devices. It’s an eye-opening transformation, when migrating from an on-premise data center, or using older forms of clinical trial data storage. Per PharmaVoice:
“With cloud-based technologies, sponsors can implement an end-to-end data management strategy to transform their clinical development life cycle processes, including data acquisition, storage, aggregation, and analysis. Different applications such as electronic data capture (EDC), clinical trial management systems (CTMS), safety systems, and data repositories can be seamlessly integrated. Cloud-based applications provide sponsors with access to data in real time as large amounts of data are stored in a central location. Additionally, cloud-based clinical trial platforms enhance collaboration between sponsors and investigators, and allow information to be shared and managed quickly and securely, which leads to increased productivity.“
Does the FDA permit cloud data warehouses?
Yes. Per PharmaceuticalCommerce.com: “Mitigating risks and avoiding new ones is top of mind for pharmaceutical IT and quality professionals. Now that cloud-computing models are well accepted across many industries with proven security models and high reliability, it is becoming a viable option for life sciences enterprises.”
“FDA-scale systems validation requirements
Validation refers to the process of checking that a software system meets specifications and that it fulfills its intended purpose. Properly capturing validation documentation is key for deploying cloud-based solutions and should be documented in accordance with the company’s internal SOPs. If an auditor reviews a company’s software environment, the company must be able to demonstrate how the software was validated per its internal SOPs. With cloud solutions, the time-consuming tasks with regards to validation that normally occurs during the Installation Qualification (IQ) and Operation Qualification (OQ) in many cases can be provided by the software vendor.
When it comes to electronic record keeping and FDA, they made an early attempt to be proactive when they came out with guidance for complying with Title 21 of the Code of Federal Regulations; Electronic Records; Electronic Signatures (21 CFR Part 11). According to FDA:
We suggest that your decision to validate computerized systems, and the extent of the validation, take into account the impact the systems have on your ability to meet predicate rule requirements. You should also consider the impact those systems might have on the accuracy, reliability, integrity, availability, and authenticity of required records and signatures…We recommend that you base your approach on a justified and documented risk assessment and a determination of the potential of the system to affect product quality and safety, and record integrity.”
For the full article, click here.
What is the FDA guidance on cloud computing?
The FDA does not seek to approve cloud data warehouse systems or any data system that does NOT alter the data itself. So if the systems simply houses data, shares data, and disseminates data, the FDA need not approve it. Per FDA.gov: “Medical Device Data Systems (MDDS) are hardware or software products intended to transfer, store, convert formats, and display medical device data. A MDDS does not modify the data or modify the display of the data, and it does not by itself control the functions or parameters of any other medical device. MDDS may or may not be intended for active patient monitoring.
Per section 520(o)(1)(D) of the Federal Food, Drug, and Cosmetic Act:
Software functions that are solely intended to transfer, store, convert formats, and display medical device data or medical imaging data, are not devices and are not subject to FDA regulatory requirements applicable to devices. The FDA describes these software functions as “Non-Device-MDDS.”
Hardware functions that are solely intended to transfer, store, convert formats, and display medical device data or results are “Device-MDDS”.
Examples of Non-Device-MDDS include software functions that:
Store patient data, such as blood pressure readings, for review at a later time;
Convert digital data generated by a pulse oximeter into a format that can be printed;
Display a previously stored electrocardiogram for a particular patient.”
What are some FDA cloud validation and compliance issues?
The FDA is clear that validation and compliance, regarding Device Software Functions and Mobile Medical Applications “intends to apply its regulatory oversight to only those software functions that are medical devices and whose functionality could pose a risk to a patient’s safety if the device were to not function as intended.”
How should your clinical trial interpret this? As a general guideline, as long as your cloud data warehouse doesn’t manipulate patient or trial data, and then risk patient safety, you may proceed with caution.
For a full report, click here to see the FDA’s “Medical Device Data Systems, Medical Image Storage Devices, and Medical Image Communications Devices: Guidance for Industry and Food and Drug Administration Staff”
And simply put, per PharmaceuticalCommerce.com: “The truth of the matter is that it is not the regulator’s role to instruct companies on how to meet regulations.”
What is GxP compliance?
GxP guidelines and regulations are intended to increase the safety and quality pharmaceutical products. The guidelines address: Storage, Auditing, Review, Engineering, and Automated Laboratory Practices. In regards to data storage, GxP guidelines discuss data integrity:
Data Integrity (DI): the reliability of data generated by the system. DI could be determined by the following activities:
- Identifying the data generated by the system during critical processes (data flow diagram)
- Defining the DI requirements (e.g. ALCOA data attributes) during the lifecycle of data
- Identifying the risks and mitigation strategies (e.g. technical or procedural controls) to avoid DI breaches.
What are the top cloud solutions for clinical trials?
There are numerous cloud solutions for clinical trials, our top recommendations to clients have been: Snowflake, Amazon Redshift, and Microsoft Azure
Does the FDA prefer AWS or Azure cloud data warehouses?
The FDA does not prefer AWS or Azure, over another. The FDA however, does seek assurances that your data is secure and unaltered by your cloud storage solution.
What are the phases or steps of cloud migration?
The phases and steps of cloud migration are pretty straightforward:
- Select a Provider
- Prep for Migration
- Migrate Data
How To Select A Cloud Migration Provider
Select a cloud migration provider or partner based on your needs. Generally, any experienced partner can advise your business on its needs, best practices, and appropriate solutions. We would recommend speaking to three providers, presenting your business needs/goals, and then deciding which provider establishes your trust. If you have any questions, we’re happy to answer questions: email@example.com
How To Prepare For Migration
Preparing for migration into a cloud is like most business process changes. Ask yourself: What is the change trying to solve or take advantage of? Who’s going to be in charge before, during, and after the change? What should we do first? Generally, we see clients wanting to improve sales funnel processes, reporting, or gain new business data insights — for all of these, we typically recommend a modern Snowflake data warehouse. Most clients have an existing in-house data warehouse specialist, or they hire us. But first, off, the should get all their data accounted for, so that a cloud migration provider can best understand the types of data that need to be migrated and connected.
How To Migrate Data
Migrating data is generally just Lift and Shift. This means there is little or no change to the data. It is simply moved from one storage solution to another. This must be done accurately, and validated after migration. For more complex data migrations, just ask: firstname.lastname@example.org
Do I need a cloud data warehouse consultant?
At NextPhase.ai, we help all sorts of companies migrate to cloud data warehouses — from global companies to Bay Area seed startups. Our recommendation is to consult a cloud data warehouse specialist, like NextPhase.ai, to help you migrate and get everything functioning perfectly. After you discover the power of this new advanced data analytics system, only then should you consider whether the ROI warrants additional investment — whether that be a full-time Data Warehouse Engineer, training an existing engineer, or simply continuing to work with a third-party like NextPhase.ai.
Do I need a cloud data warehouse consultant near me?
Working with a cloud migration service or partner near you is an advantage for communication and workflow. Generally, close proximity makes those things more efficient. If your preferred cloud migration service is not nearby, make sure you select a cloud migration service that has an established virtual workflow, and who clearly communicates expectations and process. At NextPhase.ai, we work with local and global clients efficiently, and the key is a well-established process and communication plan.
Have questions? Email anytime for a free consultation.
Operating globally, NextPhase.ai has 60+ years of combined consulting experience. NextPhase.ai delivers analytics and data science solutions, which unlock the value of people, process, and technology investments. Leveraging deep knowledge in BFSI, retail analytics, CPG, manufacturing, technology and logistics, we create long lasting value for top companies in the Bay Area and Northern California.