IDBS Data Management Blog

Exciting news from the US last week. The CommonWell Health Alliance, a not-for-profit trade association, has been formed with the promise of transforming the face of national healthcare. The headline act is to make health records easier to share and five major providers are coming together to create common standards.

In a bid to promote seamless interoperability and access to patient data across the healthcare system, these electronic medical record providers will promote common standards for sharing health data. It will mean that doctors can not only move patient records from one health system to another but also access relevant health records (pending patient agreement). A pilot program testing CommonWell Health Alliance’s plan will be conducted over the next 12-18 months, after which time the Alliance will be formally established.

Historically, a lack of interoperability among electronic health record systems and poor infrastructure for exchanging information have been the biggest barriers preventing the benefits of computerized health. The creation of the Alliance has been described as a matter of national importance by its founders and not a commercial effort but ‘an obligation’. They are to be commended for the herculean efforts that will be needed to digitize the content of an entire industry.

At IDBS, we are in a good position to witness how the siloing of health data in the US has been a major barrier to delivering connected healthcare. It is important that data interoperability standards are driven from within the industry. The Federal Government also has a key role to play in promoting this collaboration and incentivising interoperability, as it did with HIPAA.

There is more though. We need to aim for HiFi healthcare data sharing and collaboration. Aside from the debate around standards, which everyone agrees are necessary, we need to give focus to the quality of the patient data that is being stored and shared. High-quality, high-context data is a must. This will ensure records are not full of gaps or lacking in vital background details (context). This is a great and necessary first step along the road.

Big Data is a Big Topic, fuelled by the impact of low cost genomic sequencing, adoption of electronic medical records and growth in personalized medicine approaches. From research to the clinic, translational medicine depends on properly integrated, managed and analyzed high quality data. This was the theme for the 4^th annual IDBS Translational Medicine Symposium on Tuesday December 11th.

Held in central London at the prestigious Dorchester Hotel, nearly 90 attendees came to hear the latest news and developments in translational medicine in the UK. It was a packed day with eight speakers plus IDBS CEO Neil Kipling, contributing to a very focused discussion on what IDBS are doing to support this exciting field.

The announcement of a £100m DNA database provided the back drop to look at how capture, management and analysis of data and its context is critical to success in science. Sound familiar? Anyone who has worked with IDBS or has worked in life sciences knows that this is who we are. IDBS is about data. This is why data was selected as the theme of the event. Big Data is a hot topic and many groups are trying to make use of sparsely populated and poor quality patient records – something we know a lot about, and this came through strongly in the presentations.

Speaker highlights included:

• Neil Kipling explained why IDBS is in the translational space and how this is a very personal crusade for him to make a difference to patient treatment and outcomes
• Nick Craddock from the Wales National Center for Mental Health explained how IDBS is supporting a 6,000 person prospective study into mental disorders such as ADHD, Schizophrenia and Biopolar disorder
• Jim McGurk from Daiichi Sankyo highlighted why even well populated clinical trials datasets are hard to integrate, and described an IDBS project to do just that across 17 clinical studies
• Jon Green from the Health Protection Agency described how Next Generation Sequencing is used to analyze bacterial strain outbreaks, such as E.coli, and how he is looking forward to working with IDBS on this
• Robin Munro presented our vision of how Big Data in healthcare can be managed, with a particular emphasis on how E-WorkBook can be used with genetic datasets to improve collaboration
• Mike Barnes covered a long and challenging project at Bart’s Health that he has completed with IDBS to integrate clinical data sets in cardiovascular disease
• Julie Barnes explained how the 200,000 person UKCTOX project on endometrial cancer has developed a great resource for biomarker development at Abcodia, which uses IDBS software for cohort analysis
• Will Spooner from Eagle Genomics talked about end-to-end data management in Next Generation Sequencing
• Yike Guo closed the day with his usual tour de force of Big Data in life sciences and described the E-TRIKS project

Finally, one of the most encouraging comments I heard was from a team at Imperial College. They observed how all the speakers discussed IDBS becoming a part of their project teams, part of the family in many ways, and shared that they got the impression we were a great company to work with because of our commitment to our customers success. This commitment to customer success comes from the top, from Neil Kipling, and makes IDBS who we are. This is what we stand for; excellence in data and in our people.

The recent news of an NHS driven DNA database for 100,000 subjects in the UK is a major statement of intent from the government. Following up on announcements regarding access to patient data via the Clinical Practice Research Database (CPRD) and calls for the NHS to lead the world in genetic medicine last year, this is a further step towards improving patient care with better knowledge of our genomic characteristics.

With 60 million people under one health provider, the NHS has the capacity to curate world-leading data and insight into the best patient treatments and associated genetic characteristics. If successful, this will also be a highly valuable resource to attract drug companies to perform precision clinical trials and studies in the UK, and provide invaluable patient data to newcomers in the market such as nutriceuticals, health app designers and food & drink producers. This resource could drive an ecosystem of small & medium enterprise (SME) and start-ups to build health-based products built on a detailed understanding of patient population and individual subject characteristics.

Key to the success of the project will be:

• Quality of the clinical and genomic data that is collected and stored
• Reproducibility and accuracy of genomic sequencing
• Data analysis and presentation to support research and clinical decision-making, which is critical to ensuring the information is usable by different communities

Genomic sequencing techniques are still rapidly evolving, resulting in challenges in preparing samples for analysis and in consistent data analysis. Having a single/small number of sites will help this tremendously, but end to end data management (from sample to report) is key to reproducibility, audit trails and data provenance.

The ability to stratify patient populations enables pharma companies to run smaller, more efficacious trials because the predicted outcome is so much more impactful. Profiling large patient populations for clinical characteristics and molecular markers will be a huge benefit to pharma and UK-based trials, allowing populations to be stratified to a strong responding set of target patients, which will often be smaller than a standard trial.

£100m shows a strong commitment to create a knowledge resource to be reckoned with, although realistically this budget will quickly be eaten up over the course of five years.

IDBS is supporting this field in a number of major UK hospitals, many of whom recently spoke at the IDBS Translational Medicine Symposium in London. Quality of clinical data, standardization of genetic analysis and challenges in combining clinical and genomic data were all key topics.

A new collaborative data environment that will transform the world

There’s nothing quite like the morning after a good party. It’s a rollercoaster of reflection, recovery and sometimes embarrassment. It’s also often a time of new resolutions. For many of us the New Year provides the biggest ‘morning after the night before’ than most. Our article in yesterday’s  Genetic Engineering& Biotechnology News talks about the morning after the 50 year party enjoyed by the Life Sciences who are waking up to a new world. This world has important new stakeholders, such as patients, it’s more globalized and collaborative. There is payerpower, patient power and new science that is helping to drive the change and it’s demanding action. Translational medicine, personalized medicine, precision medicine, call it what you will, the Life Sciences are now focussed on outcomes and on delivering treatments that fit the disease like never before. Above all it is data driven.

Improve the data quality, improve the decision.

So is all this just Big Data? No. It’s about deep insights into what data need to be collected and smart (not just big) systems that make the data usable, then taking informed action to change practise for the better.

It is well established in Life Sciences and clinical environments that there remain significant gaps in data which make data comparisons, big or not, of limited value. Our work across industry and healthcare environments drives changes in clinical and R&D practise that address the data gaps and focus upon getting collaboration to work across these multiple disciplines. This was put well by Dr James McGurk when he said at IDBS’ Translational Medicine Symposium in London: “The more difficult it is for others to understand your data, the more likely it will be used badly.”

Welcome to a Big New Year!

Are too many square pegs and round holes getting in the way?

With the increasing globalization of bioanalytical (BA) operations, there can’t be many labs anywhere in the world that aren’t looking for ways to improve their productivity and reduce their cost basis. But with few, if any, meaningful gains possible on the operational side, one needs to look elsewhere in the process for these advances.

I’d like to propose that better data management and streamlined reporting are potential candidates for the next quantum leap. Improved ways of capturing and organizing both structured and unstructured data; enhanced workflow and process management; automatically enforced QA and superior reporting capabilities – that’s the holy grail we are all seeking. You only have to look at forums debating bioanalytical issues, such as on LinkedIn, to realize the capabilities that people crave.

A LIMS can, and does, play its part in the BA lab. But for added flexibility, new generation ELNs have much more to offer – provided they operate as needed in this highly specialized environment.

Many are the times that I have seen an enterprise attempting to utilize the instrument-bundled capabilities of an ELN, but it appears they are trying to fit a square peg ELN into a lab system with a round hole. Hammer it home hard enough and you will make it fit … but it cannot deliver all the benefits required to be truly beneficial. What you need is a platform neutral ELN solution that gives total access to your data and integrates intelligently with your existing processes.

Call me biased if you like, but there is already an ELN that delivers all that and more – the highly scalable E-WorkBook suite from IDBS. It improves to let you create your own unique methods, enforce compliance with them, and flag any deviations. But it’s not just me saying it. Ronald Shoup, from AIT Bioscience recently commented, “We adopted E-WorkBook to provide bioanalytical preclinical and clinical study data at a faster pace, with higher quality and at higher efficiency.”

Perhaps the most critical aspect of a bioanalytical study is its reporting. Every lab that submits bioanalytical data to a regulatory agency, in this case the FDA, has to comply with identical guidelines. Yet all labs works differently, which can make the reporting process hugely resource intensive. LIMS can help reduce the burden in key aspects of lab operations and is widely used. However, it has deficits in areas normally associated with an ELN – lab functionality as well as process improvement capabilities without the rigidity you expect from a LIMS. To put it simply, choosing the right ELN solution can help you collate your data across multiple runs into a single report, in an easy to use utility (say, Microsoft^® Word), resulting in time saving. Some labs that have deployed E-WorkBook Suite have estimated savings of up to four weeks. If you’re a CRO imagine the difference that could make to your productivity and your bottom line.

If ELNs are the shape of things to come to improve productivity in bioanalysis – and I believe they are – it makes sense to choose a solution that won’t fall apart regardless of the operation you’re trying to improve.

To find out more about the IDBS E-WorkBook Suite click here.