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Healthcare
Big data and Epidemiology The future of medical research.
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Lets build a smarter planet... For ďŹ ve years, IBMers have been working with companies, cities and communities around the world to build a Smarter Planet. We’ve seen enormous advances, as leaders have begun using the vast supply of Big Data to transform their enterprises and institutions through analytics, mobile technology, social business and the cloud. Transformation of the healthcare industry is finally happening, and with dramatic energy, driven by a fundamental shift in the expectations of all stakeholders: patients, governments, payers, employers and providers. In this report we will be looking in detail at the problems current medical research is facing, and how technology can help us be smarter.
Healthcare
Epidemiology The study of the distribution and determinants of healthrelated states or events (including disease), and the application of this study to the control of diseases and other health problems (WHO, 2014).
Let’s go back to 1937. Medicine was cheap, but not so effective. Staying in a hospital would most likely improve your condition as a result of being warm and looked after. Doctors would run tests on you to find out if you had a condition they could actually treat. If you were diagnosed with syphilis for example you would be given a mixture of mercury and arsenic. It would kill the disease but the side effects and detrimental effects of doing so were almost worse. The amount of curable diseases were very small and doctors were really limited with what they could do.
Introduction
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Now, it’s a different world. We have treatments for nearly all the conditions a human being can have. We can’t cure everyone, but we can prolong the life of most. Through evidence based medical research we’ve discovered more than 6,000 drugs. At the same time given birth to one of the most lucrative industries of our time, employing millions of people around the world.
Are our modern lifestyles to blame? The radiation coming off our cell phones? The way we research at the moment can’t give us the insights we need. So what can we do?
However, as we have eradicated smallpox, polio and measles - at the turn of the century we are seeing a rise in the number of cases of Dementia, Alzheimers, Multiple Sclerosis and all types of Cancer. All diseases for which there are no definitive cures, diseases so complex because of a wide range of symptoms and demographics. At the G8 summit in 2013 it was predicted that at current rates dementia would be set to treble over the next 40 years.
Lets build a smarter planet.
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Think Big.
Data is the new oil
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Tesco: A success story
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Tesco’s clubcard increased its number of primary shoppers from 16.3 % to 18.8% over the first year it was launched (Marketing week, 1995). Aside from customer loyalty, what else does Tesco get from its clubcard?
The Clubcard is genius. A goldmine in data collection on customer shopping trends. Its primary data collection use is to find out what you buy, how often and what time of year.
energy (Computerweekly, 2013).
However, over time they have realized many other uses of this data. They now use it to find out where you would have been in store for the items you just bought. They recently saved 20 million euros by cutting cooling costs on their refrigerators. By analyzing which were the busiest times of day to buy items from this section of the supermarket they were able to use less
More and more our shopping experiences are becoming personalized and more efficient as a result of sharing information on our shopping habits.
They are now moving on to cut costs in heating and lighting, and are becoming known in the industry as a ‘Big data’ company.
But what about healthcare?
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Every litte helps: IBM working with Tesco
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Healthcare - room for improvement
Due to structural issues and a resistance to change the healthcare industry has lagged behind other industries in the use of Big Data. For the last 10 years big data and healthcare has been in its infancy. However, with federal governments and other public stakeholders making decades of stored data usable, searchable and actionable, a new era of
open information is now under way. In the UK alone big data analytics across the healthcare sector could deliver additional revenues of ÂŁ14bn from 2012 to 2017 (CEBR, 2011). The U.K government is now planning on digitizing all health data by 2018 (Intellect, 2013). From electronic medical records and medical imaging to tablet computers and telemedicine, the realm of digital has entered healthcare. Not only is digital health here to stay, it is poised to reinvent healthcare as the world knows it. Just as shopping is becoming more and more
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tailored based on analyzing factors such as purchasing trends, healthcare will move away from the current one size fits all approach. However, unlike shopping, analysis of these trends isn’t just about saving money or improving profit margins - it has the potential to save and improve lives.
Medical research today. Late at night, a police officer finds a drunk man crawling around on his hands and knees under a streetlight. The drunk man tells the officer he’s looking for his wallet. When the officer asks if he’s sure this is where he dropped the wallet, the man replies that he thinks he more likely dropped it across the street. Then why are you looking over here? The befuddled officer asks. Because the light’s better here, explains the drunk man.
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Bad Pharma According to Yvonne Vallis, Researcher at MRC Cambridge, The medical research council in the U.K spent £766 million on research last year. Worldwide medical research expenditure is $160 Billion (Medical news today, 2004). Most of which is funded by Big Pharma, with the intention of developing a new patentable drug to take to market. But are we looking in the right place for disease causes and treatments? Adverse drug reactions are the fourth leading killer in the U.S. That’s right, side effects from pharmaceuticals kill more people every year than diabetes, Pneumonia, AIDS and accidents. But are pharmaceuticals always the answer?
Should we be relying on Pharma?
It has been shown that taking high doses of vitamin C intravenously is an effective treatment for Cancer (Linus Pauling Institute, 2012). However because vitamin C is not patentable no pharmaceutical company wants to pay to take it through proper medical trials so that it can get FDA, or equivalent body, approval and actually start helping people. Pharma spends on average $100 - $800 million on the development of a new drug (Drug Discovery, 2006). The cost of research means not only does a treatment have to work, but someone has to be able to make money off it. It’s estimated that 30% of U.S. health-care spending—some $700 billion a year—is spent on treatments that provide no value (WSJ, 2009). How can we know which of the 8 Rheumatoid arthritis treatments on the market work for which patients? Dr Alasdair Coles of Cambridge Neuroscience said
“Treatments are usually prescribed to individual patients on a trial and error basis, the statistical data on treatment success rates for individual prescriptions is usually what dictates which drug is prescribed. How the patient gets on dictates whether they stay on that drug.” This is the most that can be done at the prescription phase. The research and clinical trial phase is where data needs to be collected on which treatments work best and for which patients. However, on further scrutiny more problems were found with current research methods.
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Publication Bias What research we declare.
In 1980 a pharmaceutical company tried to develop an anti-arrhythmic drug called Lorcainide to suppress an abnormal heart rhythm. A study was done with 100 patients. 50 were given Lorcainide, 10 died. 50 were given a placebo, 1 died. The drug was regarded a failure, the trial was stopped and never published. Unfortunately over the next 5 years other companies had the same idea and brought the drug
to market. It took so long to find out that the drug was causing deaths that by the time they did its estimated 100,000 people died from taking it. When the pharmaceutical company that first conducted the tests were asked about it they said they concluded their studies must have been negative by chance (Cowley, 1993).
(Berman, 2013). This should be regarded as ‘research misconduct’. However there is a real lack of transparency as with most product development, it all happens behind closed doors.
Unfortunately clinical trials that go wrong are not usually published. It is predicted that in all fields of medicine about half the trials go missing in action and positive findings are twice as likely to be published
“I could flip a coin 100 times, only disclose the times it lands on heads and make it seem as though I have a double sided coin - Its the same principle.” Dr Alasdair Coles
Problems with medical research
Research Demographics Who we conduct research on.
In June 2013 the American Society of Clinical Oncology presented a clinical trial for a drug called Avastin. The drug was designed to treat brain cancer and within the randomized clinical trial it had done that. However on drug release there was no difference in survival rates between patients that were given Avastin and those that were given a Placebo (Genome web, 2013) This case is said to prove what is wrong with clinical trials in the world today. The demographic of the study did not match the demographic of patients with brain cancer. However, even if the participants of the study were better chosen no group of volunteers could match the biological diversity of
the eventual consumers. Renowned healthcare journalist Clifton Leaf commented “Researchers are coming to understand just how individualized human physiology and human pathology really are. On a genetic level, the tumors in one person with pancreatic cancer almost surely won’t be identical to those of any other.�
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Research Factors What we conduct research on.
The factors we measure when it comes to research make up the data we collect and eventually limit the insights we can then have. We can’t predict how a drug developed for a certain condition effects two people who live dramatically different lifestyles in different parts of the world, unless we can measure it. Recently Big Pharma has been spending billions of dollars on sequencing the DNA of research candidates in an attempt to
develop more insights. However, assumption of differences in genes among individuals as the core biology dictating patient segregation is just that - an assumption with no supporting evidence. Gene expression is a term that describes how our genes are read and the process by which genetic code forms a finished protein. How our genes are expressed changes depending on our environmental factors, this is known as ‘Epigenetics’ (Riddihough, 2010). For a more holistic approach to medical research both of these factors should be taken into consideration.
This is the decade of smart.
Genomics + Epigenetics for success
Genomics Genomics is defined as the study of Genes and their functions (Who, 2004). This differs from Genetics as it also takes into account the interrelation between different genes and their combined function as opposed to scrutinizing individual genes.
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RNA
DNA
Copies Genes
Stores Genes
ENVIRONMENT FOOD EXCERCISE TOXINS EMOTIONS
REGULATORY PROTEIN SLEEVE Genetic “Firewall” controls RNA access to Genes.
EXPOSOME Configures RPS “Firewall” that grants RNA access to genes.
Genomics + Epigenetics for success
Epigenetics Epigenetics literally means “above” or “on top of” genetics. It refers to external modifications to DNA that turn genes “on” or “off.” These modifications do not change the DNA sequence, but instead, they affect how cells “read” genes. (Livescience, 2013) The exposome configures this regulatory protein sleeve making some aspects of the DNA readable (“on”) and others hidden (“off”).
The sections of the DNA the RNA transfers depends on the regulatory protein sleeve. This changes on a second by second basis and is controlled by factors of the ‘Exposome’. Which include our; Environment, Food, Exercise, Toxins and emotions. (Fraga, 2012). Examples of these are; Environmental pollution, our intake of vitamins, our level of Physical activity etc...
DNA is the medium of long term storage of genetic information
This entire process is called Epigenetics, how our lifestyle affects our biology. The significance of its impact is becoming more understood. It is the reason why identical twins aren’t the same, unfortunately it has always been almost impossible to measure. Until now.
RNA copies the genetic code needed for the creation of proteins. (Diffen, 2013)
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Think Big.
Data is the new soil
“Big data is a term describing the storage and analysis of large and or complex data sets.�
Big data in medical research - Genomics is here
Jenny has a higherthan-average risk of heart disease, a lower-than-average risk for Alzheimer’s, and she metabolizes caffeine very slowly. This is what she found out after having her genome sequenced through a Google funded personal genomics start up in Mountain view, California. “23 and me� charge just $100 and all you have to do is send them a saliva sample.
Back in 2007 James Watson sequenced his DNA at a cost of $1 million (Nature, 2007) . Now anyone can have their DNA sequenced and learn more about themselves than ever before. The power held in this data is vital to medical research. Gene mutations are responsible for genetic based diseases. These are becoming more understood, it is predicted that each of us have between 5 and 10 potentially deadly mutations in our genes (Royal society, 2010). Some well-known inherited genetic disorders include cystic
fibrosis, sickle cell anemia, TaySachs disease, phenylketonuria and color-blindness, among many others. Cancers are usually the result of a series of mutated genes. The amount of data being produced by sequencing, mapping, and analyzing genomes propels genomics into the realm of Big Data. Each human genome amounts to 100 gigabytes. Sequencing multiple human genomes would add up to hundreds of petabytes of data, and the data created by analysis of multiple gene interactions in relation to disease magnifies this further.
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ENVIRONMENT
FOOD
EXCERCISE
TOXINS
EMOTIONS
EXPOSOME These are the factors that effect which aspects of our DNA are actually read.
Big data in medical research - Quantified self
Quantified self Otherwise known as ‘Lifelogging’
The changing and varied nature of the Exposome make it difficult to measure. However, over the last five years we have seen an influx of ‘Quantified self’ products enter the commercial marketplace. Products aimed at quanitifying our diet, physical activity, sleep and air pollutants exist and are becoming more widely used. With a variety of sensors and apps we are changing the way we are living, for the better. The data resulting from all of this lifelogging is invaluable. Unfortunately in its current state we have seperate entitites collecting data on specific
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aspects of our lives, such as our sleep patterns. The insights we could gain from combining this data could be very powerful. This interalating data could tell you how your diet effects your sleep and how many seconds that took off yesterdays run. Quantified self is becoming a method to measure all the aspects of the Exposome at a personal level. The NHS actually now have a recommended apps library for personal health management. “Unfortunately the technology at the moment is just reactive, users have to have active involvement which takes time and effort that only athletes and extreme users are currently willing to put in.” Oliver Stokes Principlal of Innovation PDD
Big data in healthcare - Quantified self
A biomarker can be defined as a measurable indicator of health (Parikh, 2007). When you visit the doctor and they take a urine or blood sample they can learn alot about your current biological condition from analysis of these bio markers. Developments from researchers around the world are finding new and interesting biomarkers that could influence the future of quantified self prodcuts. Non invasive bio markers that are currently being researched include heart rate variability. The time between each heart beat gives a quantifiable indictor of quality of sleep, levels of
inflammation / stress in the body and cardiac health (Khoren, 2008). On analysis of this data researchers can predict how likely someone is to have a heart attack 3 months in advance. Breakthroughs in biomarker research could unveil more methods for understanding our physiology and lead to better quantified self products. These products can then measure the factors of our exposome. This data can then be used to understand the lifestyle factors that are common among disease victims.
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But health tracking technology isn’t the only way we can find out this information...
“Patient generated big data will yield clinically useful information. The question is how will this data merge with electronic medical records to give healthcare providers useful insights.” Fabien Schmitt Senior Medical Designer PDD
Big data in healthcare - Population data
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Population data Trends in existing data.
Through analysis of search queries relating to flu symptoms Google are able to predict a flu epidemic 2 weeks before traditional methods used by the centre for disease control (Google, 2014). Microsoft research worked in collaboration with Stanford University to analyse Bing search queries to more efficiently work out common drug side effects. They were able to work out what the most important side effects
were 6 months before traditional methods implemented by the FDA (Microsoft, 2013). They then worked in collaboration with the FDA to impliment this officially and now an entire department of the FDA is dedicated to analysing social media data such as tweets and facebook statuses to work out common side effects of medications and issues to do with food safety, famine and drought. Through the analysis of electronic medical records, one Harvard student was able to find out that patients who were taking a particular mix of an anti
depressant and a cholesterol drug had the side of effect of an increased blood glucose level. What was interesting was that neither drug alone had the side effect. Understanding drug interactions is key to lowering the amount of people that die from adverse drug reactions. Taking account that the average 70 year old in the U.S is on 7 different medications (Altman, 2013). A 7 way drug interaction. Thats alot of data to analyse.
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“In this era of flash photography, we have to really think deeply about personal privacy�
Warren and Brandeis - 1939
Get off my data!
Data sharing safety Why would we share our data?
But what about our personal privacy? With the steady stream of NSA stories in the media we are all aware of our digital privacy, or lack thereof. However it hasn’t stopped us sharing. In Janurary 2014 IBM released a study on more than 30,000 global consumers over the course of 2 years. Showing that more and more consumers are willing to share their personal data, if they recieve some benefit such as a personalised service.
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However this is the biggest obstacle in the rise of Big data. The opportunities are endless, but dated laws such as the Health insurance Portability and Accountability act (HIPAA) are currently thwarting innovation. The IBM study shows that people are willing to share their personal information for a benefit, but short of signing off your HIPAA rights that also protect the data from being shared with insurance companies, there is nothing that can be done. “As a byproduct of Zuckerbergs law, I think people are becoming more accustomed to sharing their personal data.” Oliver Stokes - Principlal of Innovation at PDD One method Stanford Proffessor ‘Russ Altman’ thought of for bypassing laws and regulation could be to have barriers to anonymise the collected data. As long as this process has FDA approval anyones data could be shared in a more secure fashion.
Conclusion
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The way we currently research has gotten us so far. But with the rise of more complex diseases we need to get smarter. Big data could change the way we conduct medical research forever. The problems highlighted with current medical research to do with; publication bias, research factors and demographics could all be addressed through
Big data. Some companies that are already trying to harness the power of big data in healthcare are already making breakthrough discoveries that were not possible before. With developments in Genomics, Health Monitoring Technology and Population data we will have all the information needed to triangulate on medical research and health.
Watson In 2011 IBM’s Watson defeated Brad Rutter and Ken Jennings in Jeopardy without a problem. Watson was mostly given unstructured data to prepare for such a task, yet with every question asked, Watson accessed the data in matter of milliseconds, answering correctly every time. Watson is a cognitive computing system designed for complex analytics, ready to answer the computational calls of Big data.
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References
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David Benady. (1995). Tesco plays its clubcard right. Available: http://www.marketingweek.co.uk/tesco-plays-its-clubcard-right/2014667. article. Last accessed 14 Jan 14. Bill Goodwin. (2013). Tesco uses big data to cut cooling costs by €20m. Available: http://www.computerweekly.com/news/2240184482/ Tesco-uses-big-data-to-cut-cooling-costs-by-up-to-20m. Last accessed 14 Jan 14. Centre for Economics and Business research . (2011). Unlocking the value of big data. Data equity. 1 (1), 5. Intellect. (2013). Digitising the NHS by 2018. Intellect response. 1 (1), 1-10. Melinda Beck. (2009). Injecting value into medical decisions. Available: http://online.wsj.com/news/articles/SB1000142405297020360920 4574314670517418650. Last accessed 19 Jan 14. What’s the Matter with Clinical Trials? | The Daily Scan | GenomeWeb Genomeweb.com. 2014. What’s the Matter with Clinical Trials? | The Daily Scan | GenomeWeb. [online] Available at: http://www.genomeweb. com/blog/whats-matter-clinical-trials [Accessed: 19 Jan 2014].
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References
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WHO | WHO definitions of genetics and genomics Who.int. 2004. WHO | WHO definitions of genetics and genomics. [online] Available at: http://www.who.int/genomics/geneticsVSgenomics/ en/ [Accessed: 19 Jan 2014]. Epigenetics: Definition LiveScience.com. 2013. Epigenetics: Definition. [online] Available at: http://www.livescience.com/37703-epigenetics.html [Accessed: 19 Jan 2014]. DNA vs RNA - Difference and Comparison | Diffen Diffen.com. 2013. DNA vs RNA - Difference and Comparison | Diffen. [online] Available at: http://www.diffen.com/difference/DNA_vs_RNA [Accessed: 19 Jan 2014]. Mario F.Fraga. (2012). Epigenetics: The exposome-genome interface.Instituto Universitario De Oncologia. 1 (1), 1-21. Medical News Today. 2003. Health Research Spending Tops US$ 160 Billion, Yet Investment Fails To Meet The Needs Of Developing Countries. [online] Available at: http://www.medicalnewstoday.com/releases/127893.php [Accessed: 28 Jan 2014].
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Linus Pauling Institute at Oregon State University Lpi.oregonstate.edu. 2012. Linus Pauling Institute at Oregon State University. [online] Available at: http://lpi.oregonstate.edu/fw12/ lipoprotein.html [Accessed: 28 Jan 2014]. The Cost of Clinical Trials Drug Discovery. 2006. The Cost of Clinical Trials. [online] Available at: http://www.dddmag.com/articles/2007/09/cost-clinical-trials [Accessed: 28 Jan 2014]. James Lind Library :: The effect of lorcainide on arrhythmias and survival in patients with acute myocardial infarction. :: Key Passages Jameslindlibrary.org. n.d. James Lind Library :: The effect of lorcainide on arrhythmias and survival in patients with acute myocardial infarction. :: Key Passages. [online] [Accessed: 28 Jan 2014]. A.J. Cowley, A. Skene, K. Stainer and J.R. Hampton. (1993). The effect of lorcainide on arrhythmias and survival in patients with acute myocardial infarction: an example of publication bias. -. 1 (1), 1. Adriane Fugh-Berman. (2013). How Basic Scientists help the pharmaceutical industry market drugs. Perspective. 11 (11), 1-5.
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References
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What Is Epigenetics? Sciencemag.org. 2010. What Is Epigenetics? [Accessed: 31 Jan 2014]. James Watson’s genome sequenced : Nature News Nature.com. 2007. James Watson’s genome sequenced : Nature News. [online] Available at: http://www.nature.com/news/2007/070528/ full/news070528-10.html [Accessed: 4 Feb 2014]. Parikh NI, Vasan RS.. (2007). Assessing the clinical utility of biomarkers in medicine.. Biomark Med. 1 (3), 419. Gregory Khoren Karapetian (2008). Heart Rate Variability as a Non-invasive Biomarker. California: Pro Quest. 141. Google. (2014). Explore flu trends around the world. Available: http://www.google.org/flutrends/. Last accessed 14 Jan 14.
Interviews: Fabien Schmitt - Senior medical designer -PDD Oliver Stokes - Principal of Innovation - PDD Yvonne Vallis - Research at MRC Cambridge Dr Alisdair Coles - Cambridge Neuroscience - Medical researcher for Sanofi Genzyme
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Public Lectures Big data and Big disease mining for medical breakthroughs - University of california http://www.youtube.com/watch?v=p6fwrJCltro Chronic diseases how technology is changing the patient experience http://www.youtube.com/watch?v=Kztk8_yB6vo Genetics, Epigenetics and disease - The royal society http://www.youtube.com/watch?v=SHpfkNRscOc
Documentaries A decade of the human genome - BBC http://www.youtube.com/watch?v=Fgq-XoyorWY Food Matters - Carlo Ledesma, James Colquhoun http://www.foodmatters.tv/
Bibliography
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Bibliography
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Medical journals Egger G, Liang G, Aparicio A, Jones PA.. (2004). Epigenetics in human disease and prospects for epigenetic therapy.. Nature. 1 (1), 1. Serman A, Vlahović M, Serman L, Bulić-Jakus F.. (2006). DNA methylation as a regulatory mechanism for gene expression in mammals.. Coll Antropol. 1 (3), 655. Lu Q, Qiu X, Hu N, Wen H, Su Y, Richardson BC.. (2006). Epigenetics, disease, and therapeutic interventions.. Ageing Res Rev. 5 (4), 449. Holloway AF, Oakford PC.. (2007). Targeting epigenetic modifiers in cancer.. Curr Med Chem. 14 (24), 2538 - 2540.
Websites Dave Asprey. (2011). How your environment hacks your genes for you. Available: http://www.bulletproofexec.com/how-your-environmenthacks-your-genes-for-you/. Last accessed 03 January 2014.
TED Talks Joel Selanikio: The surprising seeds of a big-data revolution in healthcare John Wilbanks: Let’s pool our medical data William Li: Can we eat to starve cancer Ben Goldacre: What doctors don’t know about drugs Ben Goldacre: Battling bad science