Illness and Big Data

Liam Wilson our consultant managing the role
Posting date: 4/24/2013 10:24 AM

Richard Barker is director of the Center for the Advancement of Sustainable Medical Innovation, Oxford. He states, 'Illness just became another big-data problem'.

Cameron was Alissa Lundfelt's first child, so initially she didn't realize anything was wrong. He would demand milk constantly, but she thought that wasn't unusual. But when his fingers and toes started to go cold, his eyes rolled back in his head and his skin turned grey, he was taken to the emergency room and diagnosed with Type 1 diabetes. At five months old, he was the youngest person ever to receive this diagnosis in his home state of Alaska.

This meant testing his blood sugar every two to four hours and giving frequent insulin injections, since -- in Type 1 diabetics -- the insulin-producing beta cells in the pancreas are attacked by the body's own immune system, stopping the production of insulin that the body needs.

But even with this regimen, Cameron didn't thrive. When he was two years old, Ian Glass, associate professor of paediatrics and medicine at the University of Washington, and visiting Alaska from Seattle, ordered a test. This revealed that Cameron's diabetes was caused by a mutation in the KCNJ11 gene. Lundfelt went online and read about a group of scientists who had discovered that, in this rare form of diabetes, the beta cells produced plenty of insulin, but it couldn't get out of the cells. All Cameron needed was to take a single pill three times a day to restore his glucose levels to normal.

So diabetes isn't just diabetes: it's a cluster of diseases with different causes and different remedies. This story is just a glimpse of a quiet medical revolution: from defining diseases by the symptoms they cause or the part of the body affected, to the underlying molecular mechanism.

Everything from the situation in the womb to the way someone lives their life can result in a set of molecular patterns that appear as symptoms, which often hides more than they reveal. 

The tools we have to power this revolution are being added to daily. We are testing cancers that arise in the skin, the colon and the lungs and finding that a proportion of all of them have mutations of the BRAF gene, suggesting they will all respond to the same medication. And often we can work backwards from different responses to a drug to find that superficially similar diseases have different mechanisms -- as in many autoimmune diseases, for example.It isn't just genetics that influence the existence of a disease, or the form that it takes. Only one of a pair of identical twins may have schizophrenia, for example. 

Everything from the situation in the womb to the way someone lives their life can result in a set of molecular patterns that appear as symptoms, which often hides more than they reveal.

This redefinition of disease will also set us a fascinating semantic challenge. Your doctor might tell you that your swollen joints are symptomatic of a TLR and IL-1R signalling pathway imbalance: or instead perhaps she will just say you have arthritis type 13-2. Or perhaps your doctor is not aware of this new precision medicine and simply says you've got rheumatoid arthritis. So when you search for "molecular mechanisms of rheumatoid arthritis", you find over 2,270,000 results.

We'll discover a lot about ourselves and our diseases from big data -- assessing the outcomes of different therapies and finding out in retrospect what works best for who. We will then match that against our gene sequences, which may be stored confidentially at birth. If Cameron Lundfelt had been born a few years later, his parents and doctors would perhaps have known before his symptoms had even appeared that he had monogenic diabetes type KCNJ11. And they would have known immediately what to do.


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Weekly News Digest: 14th - 18th June 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics. Gov.uk: Five signs of a good data quality culture Particularly post-pandemic, we all want to know that our data is fit for purpose. In this article from the Government Data Quality Hub, they look at five ways to ensure that your data's quality is right for your's and your users’ needs. This includes: Everyone is involvedData quality is a commitment, not a taskYou know what works for your organisationYou know why quality mattersYou are proactive not reactive We know that committing to a good data quality culture is a continual process. This core advice allows us to take a step back and think about how you can understand your unique challenges and involve the right people, so you can prevent bad quality data before it damages your work. See more on this here. Analytics Insight: 5 types of artificial intelligence that will shape 2021 and beyond We really like this article from Analytics Insight that explores the future of technology, and specifically the rise in uses of artificial intelligence (AI). AI is often seen to be disruptive as there is an assumption that robots could take over and jobs are wiped out, but it’s more likely that humans and machines will work together to streamline processes across a range of industries. The different types of AI to keep an eye on include: Customised technology providerChoosy algorithmHuman-machine interactionReciprocating machinesTheory of mind We’re always excited to learn more about new technologies, click here to read more on this. KD Nuggets: Five types of thinking for a high performing data scientist In this piece KD Nuggets look at how the way our approach to problem-solving may be guided by your personal skills or the type of problem at hand. As a Data Scientist, appreciating different approaches can help you more effectively model data in the business world and communicate your results to the decision-makers. Whether this is model thinking, systems thinking, agent-based thinking, behavioural thinking, or computational thinking, taking the time to understand your approach will significantly help the way you complete the function of your role. To read the full article, see here.  TechRepublic: These 220+ courses will help you master tech skills and prep for IT certification exams We know that there is a digital skills gap. According to Boston Consulting Group, there will be tens of millions of job vacancies by 2030 that will be hard to fill because not enough workers have the required skills, many of which are in technology. One of the best ways to upgrade your skillset is to complete extra training and qualifications to ensure you’re always learning more about your market and providing yourself with the best opportunities to achieve your next career step. ITU Online has over 200 courses covering cloud deployment, cybersecurity and more. Of course, this isn’t the only way in which you can level up your skills, but it’s a good place to start! To read more about this, click here.  We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.    

How Will Embracing Flexible Working Help The Life Science Sector To Grow?

COVID-19 has drastically changed ways of working in the Life Science industry. Overnight, teams moved online, while new research had to be prioritised. Life Sciences were already moving towards more remote working, and the pandemic has only quickened this shift. There is no doubt these changes have fundamentally changed the Life Science sector and how professionals working in this space operate post-pandemic.  However, uncertainty still remains about the viability of remote working for the sector and there is a divide between those able to work remotely and those who need to go into ‘wet labs’. Is remote working a step too far for Life Sciences? Collaboration  2020 saw an increase in collaboration between professionals working across different areas of Life Sciences. Interestingly, organisations who may usually compete came together to share data and work towards a shared goal. Collaboration is essential in Life Sciences, yet for many, remote working reduces spontaneous teamwork and creativity.  New flexible lab spaces may be the future for Life Sciences though. RUNLABS have recently opened their first fully equipped flexible lab space in Paris for scientists and companies working in Life Sciences. This space hopes to builds on the existing collaborative approach in the industry and encourage further cooperative innovation. Efficiency  Many employees noticed a spike in employee efficiency when working remotely. By eliminating commutes and increasing flexibility, employees were able to be more productive with their time. Remote working also allowed organisations to streamline processes and reduce time spent in meetings.  However, insight from McKinsey highlights that research and development leaders estimate productivity has fallen by between 25 and 75 per cent due to remote working. Those in pharma manufacturing have reported lower levels off efficiency, as well as the potential for lower-quality outputs.  Research The pandemic forced remote trails to become a necessity, and since then, they have increased in popularity. While face-to-face research is still preferrable, remote trials can reduce costs and improve efficiencies. Indeed, on-site monitoring accounts for a significant portion of the costs of bringing a new product to market, yet this is no longer necessary in remote trials.   Not only are remote trials more cost-effective, but they can open research to a wider range of patients and can increase the communication between trial participants. Diversity Flexible working can run a risk to diversity and inclusion though. McKinsey also notes that, ‘when faced with a crisis, leaders often revert to relying on the core team of people they already know and trust. This disproportionately affects women and minorities because they are often not part of that group. Differences in perceptions and experiences of inclusion results in individuals or communities being disenfranchised, which can be devastating to careers and create a two-tiered culture.’ We know that 27 per cent of D&I leaders say their organisation have put all or most of their initiatives that embrace diversity and inclusion on hold because of the pandemic. However, remote work unlocks new hire pools and opens up the workplace to a more diverse workforce. Workers are no longer restricted by their geographical location or personal circumstances. Flexible working is an opportunity for Life Science organisations to harness a wider talent pool and increase their diversity. There is no doubt that Life Science is one of the most cutting-edge sectors globally and the pandemic has only cemented this. COVID-19 has shown the potential for remote working in life sciences, and in-person health care professional access may never return to pre-lockdown levels. But, going forward life sciences need to remember remote working is not practical for everyone nor every role. Organisations will need to consider individual wellbeing and role efficiency as they decide their next step.  If you’re in the world of Data & Analytics and looking to take a step up or find the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

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