Clinical data management software is now as integral to the medical facility and laboratory as lab coats and test tubes, explains Frank Millard
Data is key to clinical results, assessments and records as well as general the administration of the laboratory. The coding and verifying of medical records, research data and drug testing is an intensive process dependent on strict accuracy and easy access to large amounts of data, which is constantly being updated.
Software has all but rendered the manual input of data in laboratories obsolete. For example, data gathered in clinical trials can be stored in a data management system, mitigating against human error and improving efficiency and levels of accuracy critical to a laboratory environment. The evolving industrial internet of things (IIoT) means systems can be used side by side and communicate with each other. However, laboratories that have evolved piecemeal often still include a mixture of different systems and even manual element.
Digital solutions are helping everyone in the life sciences improve efficiency by providing the ability to go paperless, says Patricia Santos-Serrao, director of product strategy (clinical and regulatory) at MasterControl. “Quality management, data capture and other processes that used to be slow and error-prone have been dramatically accelerated by freeing them from their reliance on manual, paper-based processes.”
Real-world laboratories face a growing amount of data originating from multiple instruments and equipment. “When in the past results were often manually reported, the amount of data is not compatible anymore with such practices,” says Dr Pierre Rodrigues, founder and general manager at Agilebio. “The stack of computer files and documents tend to disperse on as many computers as scientists have. Apart from scientific calculations and analysis, digital solutions can help centralising, unifying and indexing these documents so the information can be crossed, returned and preserved when needed.”
Matt Botterman, Global FreezerPro business manager, also emphasises the advantages of careful digitalisation: “Digital solutions allow instant communication across laboratories where all levels can see what is happening in real time. They also offer a reliable way to hold records over long periods of time. In industries such as biobanking it’s critical to be able to hold consistent records and be able to easily search through them. Paper records do not allow this searchability. Digital solutions can also improve security through password access or encryption of the data.”
Here's four reasons why digital solutions are key:
1. Connectivity
We are now in the fourth industrial age, meaning that technology is increasingly connected, with the attendant technical complexities and solutions that one might expect. Equipment or sensors can now be connected directly using internet and cloud networks, but equipment and software are often purchased at different times for different reasons.
“Connectivity in the labs is still quite heterogenous and mixes quite a lot of technologies partly because of the longevity of such devices,” comments Rodrigues. “Labs invest significant amounts of money in such machines and tend to keep them in place for decades. We can see top-notch recent genomics machines side by side with a 30-year old spectrometer.”
Cloud-based servers can ensure records can be accessed anywhere in the world. “This is particularly useful when looking at samples in the office, in the lab and at the freezer,” says Botterman. “Equally, it allows us to back up the data to a secondary server on a different continent – this is very useful in disaster planning.”
Alan James, managing director, Clinical Systems, warns that although there are benefits to using the internet and intranets for communication purposes, such uses, especially the internet, pose very real threats of cyber-attack. “Research and medical laboratories are under constant threat of attack and we are aware of several such attacks which have been successful,” he reveals. “Consequently, we advise our customers to keep their raw data collection, collation and storage as isolated as possible from the internet and to ensure frequent and multiple, physically remote, back-ups of their raw data.”
2. Accuracy
Lab software can help in avoiding errors by implementing rules and limits. In that respect it can be safer than paper, says Rodrigues. Botterman is in accord: “By fixing formats for input, errors can be limited. It’s possible to use a range of words or terms that can mean similar things but can also be mis-interpreted. A digital format can remove this ambiguity.”
The whole purpose of the GxP (good practice) guidelines issued and enforced by regulatory authorities such as FDA (Food & Drug Administration), EMA (European Medicines Agency) and OECD (Organisation for Economic Development & Co-operation), is to ensure accuracy of medically related data, says James. These were introduced following the thalidomide tragedy back in the 1950s and 1960s.
“Accuracy starts with the methods used to control software design and development. This means that every single line of code we write is documented, peer reviewed, tested, regression-tested and quality assured before undergoing validation by our customers. The software design includes appropriate data checking at all stages of the clinical workflow. This can be automatic checking, or it can be some form of manual process such as duplicate data entry and independent results authorisation.”
3. Data storage
“The more data you have, the more difficult it is to manage,” says Botterman. “Software allows you to easily manipulate and filter this.”
When a lab stores results in its lab notebook, the users can link and deposit files that will become readily available and shareable as needed. With a proper server set-up on premises or the cloud, the data can be secured and backed up, so less prone to destruction or loss. Analysis depends on the type of data, but extractions to usual formats such as Excel facilitate reports as needed.
James says there is a high level of flexible and adjustable data handling and reporting within Clinical Systems’ ClinAxys II, for example. This includes facilities for a laboratory to tailor reports to meet the requirements of their customers, to send reports automatically at certain stages of the workflow by email, to import data from other laboratories providing specialist testing,to prepare and export data extracts for analysis using any third-party tools.
4. Security
Two major elements of data security are remote storage and encryption. These are essential in maintaining complete trust in information received and transmitted.
“Life sciences companies have been some of the last to embrace cloud technology because of the sensitive nature of the data involved (such as patient health records, clinical trial information and proprietary drug research),” says Santos-Serrao. “What we’re learning, though, is that cloud-based systems are proving to be far safer than on-premises systems. Cloud providers such as MasterControl have dedicated teams who continually monitor the systems to ensure that the data and the software are secure.”
This is an industry under constant threat of cyber-attack, says James. This can be financially motivated or just plain malicious. “Therefore, we do everything we can to keep unauthorised people out of the data our software manages and to advise customers on how to protect that data from corruption. For good reasons – commercial and medical – communications can be extensive and global, and we advise that every precaution be taken in addition to those that we take ourselves.”
The future
“Whether we like it or not, the future is paperless,” asserts Santos-Serrao. “Our world is becoming increasingly more digital, so companies are trying to help customers make that transition by providing a completely connected, cloud-based platform. Technologies such as artificial intelligence (AI) and machine learning (ML) are accelerating innovation in the life sciences so quickly that it’s hard to keep up – and you definitely can’t compete if all your data is trapped in paper.”
Rodrigues agrees that although many labs are still using old methods with paper and loose files, increasingly mobile apps can assist and speed up processes without the need of big computer screens. “The future must provide smoother and logical data entries.”
