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Technology is moving us, finally, towards the vision of personalised medicine

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We attended this year’s SapphireNow event (SAP’s customer and partner conference) in Orlando and were very impressed with some of the advances SAP and their ecosystem are making in the field of healthcare.

Why is this important?

Healthcare for many decades now has been stagnant when it comes to technological disruption. Go to most hospitals today and you will still see doctors using paper and clipboards for their patient notes. Don’t just take our word for it, in her highly anticipated 2015 Internet Trends report Mary Meeker clearly identified that the impact of the Internet on healthcare is far behind most other sectors.

But this is changing, and changing rapidly. The changes coming to the healthcare sector will be profound, and will happen faster than anyone is prepared for.

DNA sequencing cost per genome

And one of the main catalysts of this change has been the collapse in the cost of gene sequencing in the last ten years. See that collapse charted in the graph to the right. And note that the y-axis showing the cost of sequencing is using a logarithmic scale. The costs of sequencing are falling far faster than the price of the processing power required to analyse the genetic data. This means the cost of sequencing is now more influenced by the cost of data analysis, than data collection. This has been a remarkable turn of events, especially given the first human genome was only published fourteen years ago, in 2001.

The advances in the data analytics picking up pace too. In memory databases, such as SAP’s HANA, and cognitive computing using devices like IBM’s Watson, are contributing enormously to this.

To get an idea just how much the analytics is advancing, watch the analysis of data from 100,000 patients by Prof Christof von Kalle, director of Heidelberg’s National Center for Tumor Diseases in the video below. Keep in mind that each of the 100,000 patients has 3bn base pairs in their genome, and he’s analysing them in realtime (Prof Von Kalle’s demo starts at 1:00:03 in the video, and lasts a little over 5 minutes).

As he says at the conclusion, two years ago a similar study conducted over several years by teams of scientists was published as a paper in the journal Nature. That’s an incredible rate of change.

IBM are also making huge advances in this field with their cognitive computing engine, Watson. In a recent announcement, IBM detailed how they have teamed up with fourteen North American cancer institutes to analyse the DNA of their patients to gain insights into the cancers involved, and to speed up the era of personalised medicine.

Personalised medicine is where a patient’s DNA is sequenced, as is the DNA of their tumour (in the case of cancer), and an individualised treatment, specific to the genotype of their cancer is designed and applied.

This differs from the precision medicine offerings being offered today by Molecular Health, and discussed by Dr Alexander Picker in the video at the top of this post.

Precision medicine is where existing treatments are analysed to see which is best equipped to tackle a patient’s tumour, given their genotype, and the genotype of their cancer. One thing I learned from talking to Dr Picker at Sapphirenow is that cancers used to be classified by their morphology (lung cancer, liver cancer, skin cancer, etc.) and treated accordingly. Now, cancers are starting to be classified according to their genotype, not their morphology, and tackling cancers this way is a far more effective form of therapy.

Finally, SAP and IBM are far from being alone in this space. Google, Microsoft and Apple are also starting to look seriously at this health.

With all this effort being pored into this personalised medicine, I think it is safe to say Ms. Meeker’s 2016 slide featuring health will look a little different.

UPDATE – Since publishing this post SAP have uploaded a video to YouTube showcasing their internal application of Molecular Health’s solution for employees of SAP who are diagnosed with cancer. You can see that below:

Full disclosure – SAP paid my travel and accommodation to attend their Sapphirenow event

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Apple launches ResearchKit – secure, private, open source medical research

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ResearchKit

Apple announced a new initiative at its Spring Forward event yesterday – ResearchKit.

What is ResearchKit? Apple’s SVP of Operations, Jeff Williams, described it as a framework for medical researchers to create and deploy mobile apps which collect and share medical data from phone users (with their permission), and share it with the researchers.

Why is this important? Previously it has proven difficult for research organisations to secure volunteers for research studies, and the data collected from such studies is often collected, at best, quarterly.

With this program, Apple hopes to help researchers more easily attract volunteers, and collect their information far more frequently (up to once a second), yielding far richer data.

The platform itself launches next month, but already there are 5 apps available, targeting Parkinson’s, diabetes, heart disease, asthma, and breast cancer. These apps have been developed by medical research organisations, in conjunction with Apple.

The success of this approach can be seen already in this tweet:

https://twitter.com/wilbanks/status/575125345977810945

I downloaded mPower, the app for Parkinson’s to try it out, but for now, they are only signing up people who are based in the US.

As well as capturing data for the researchers, mPower also presents valuable information to the user, tracking gait and tremor, and seeing if they improve over time, when combined with increased exercise. So the app is a win both for the research organisations, and for the users too.

Apple Does Not See Your Data

Apple went to great pains to stress that the user is in complete control over who gets to see the data. And Apple themselves doesn’t ever get to see your data.

This is obviously a direct shot at Google, and its advertising platform’s need to see your data. Expect to hear this mantra repeated more and more by Apple in future launches.

This focus on privacy, along with Apple’s aggressive stance on fixing security holes, and defaulting to encryption on its devices, is becoming a clear differentiator between Apple and Android (and let’s face it, in mobile, this is a two horse race, for now).

ResearchKit Open Source

Finally, Williams concluded the launch by saying Apple wants ResearchKit on as many devices as possible. Consequently, Apple are going to make ResearchKit open source. It remains to see which open source license they will opt for.

But, open sourcing ResearckKit is a very important step, as it lends transparency to the privacy and security which Apple say is built-in, as well as validating Apple’s claim that they don’t see your data.

And it also opens ResearchKit up to other mobile platforms to use (Android, Windows, Blackberry), vastly increasing the potential pool of participants for medical research.

We have documented here on GreenMonk numerous times how Big Data, and analysis tools are revolutionising health care.

Now we are seeing mobile getting in on the action too. And how.

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Big Data and analysis tools are facilitating huge advances in healthcare

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SAP's Genomic Analyzer

As we noted recently here on GreenMonk, technology is revolutionising the healthcare industry, and the pace of change is astounding with new products and services being announced daily.

We were recently given a demonstration of two products currently being developed by SAP (Genomic Analyzer, and Medical Research Insights), and they are very impressive products.

The Genomic Analyzer (pictured above) can take large numbers of genomes and interrogate them for various traits. This may sound trivial, but this is a serious Big Data problem. In a talk at SAP’s Sapphirenow conference in June, Stanford’s Carlos Bustamante outlined the scale of the issue when he noted that in sample size of 2534 genomes takes up 1.2tb of RAM and consists of over 20bn records.

The industry standard for storing genomic data is in a variant call format (VCF) text file. This is then interrogated using either open source or some specialised commercial software analyse the genomic data. Researchers frequently have to write their own scripts to parse the data, and the parsing takes a considerable amount of time.

SAP's Genomic Analyzer results

On the other hand, SAP’s Genomic Analyzer, because it is based on SAP’s in-memory database technology, can take record sets of 2,500 genomes in its stride returning multi-variant results in seconds. This will allow previously impossible tests to be run on genomic datasets, which opens up the potential for disease biomarker identification, population genetics studies, and personalised medicine.

SAP are actively looking for research partners to work with them on the development of the Genomic Analyzer. Partners would typically be research institutions, and they would receive login access to the analyzer (it is cloud delivered), and the ability to create and run as many query sets as they wish.

SAP’s Medical Research Insights application again takes advantage of SAP’s Hana in-memory database to take in the vast swathes of medical data which would typically be housed in siloed data warehouses (EMR’s, scans, pathology reports, chemo info, radio info, biobank system, and so on). It can be used to quickly identify patients suitable for drug trials, for example or to surface new research when relevant to patients.

The Medical Research Insights solution is currently being developed as part of a co-innovation project with a large cancer institute in Germany, but will ultimately be applicable to any hospital or medical institution with large disparate data banks it needs to consolidate and query.

SAP are far from alone in this field. As well as developing innovative medical applications themselves, many in their Startup Focus program are also furiously innovating in this field, as previously noted.

Outside of the SAP ecosystem, IBM’s Watson cognitive computing engine is also tackling important healthcare issues. And like SAP, IBM have turned Watson onto a platform, opening it up to external developers, crowdsourcing the innovation, to see what they will develop.

The main difference between IBM’s cognitive computing approach, and SAP’s Hana in-memory database is that Watson analyses and interprets the results on behalf of the researchers, whereas Hana delivers just the data, leaving the evaluation in the hands of the doctors.

And news out today shows that Google is launching its Google X project, Baseline Study so as not to be left out of the running in this space.

There’s still a lot of work to be done, but the advances these technologies are starting to unlock with change the healthcare industry irreversibly for the good.

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Technology in healthcare, a post-Sapphirenow update

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As noted here recently, technology is completely revolutionising the healthcare industry.

And that was brought home to us forcefully when we attended SAP’s 2014 Sapphirenow conference last week. I had fifteen meetings scheduled at the event, and while there wasn’t much mention of healthcare during the keynotes, seven of my fifteen meetings were healthcare related. In previous Sapphirenow conferences, there might have been one.

The meetings were with a range of organisations. Some were larger organisations like MKI, Stanford University (specifically their Center for Computational, Evolutionary and Human Genomics (CEHG)), and unsurprisingly SAP. MKI talked about their use of HANA, R, and Hadoop for genomic analysis. Stanford’s Carlos Bustamante talked about the research being done by the CEHG, in conjunction with SAP, on understanding different genomes and their health-related phenotypic consequences, while SAP discussed their Care Circles initiative, as well as their Genome Sciences projects.

One interesting data point that emerged from Prof Bustamante was that one dataset of 2534 individual genomes contained in excess of 20 billion records and it consumed 1.2 terabytes of RAM. This is big data. Especially when you consider you are interrogating it against matrices of other data points (such as age, nationality, gender, etc.).

CoreyMobile screen

Three of the companies I met were part of the SAP Startup Focus program. This is a program aimed at start-up companies with offerings in the big data, realtime or predictive analytics spaces. The program helps them develop their product on SAP’s in-memory HANA database platform, and also helps them with go to market strategies.

The three healthcare startups were Convergence CT, Phemi, and Core Mobile. ConvergenceCT makes software for hospitals which can take in data from multiple data sources (EMR systems, labs, radiology, etc.) and produce insights via predictive analytics, and reporting dashboards. Phemi, similarly takes in healthcare info from the various disparate hospital data sources, and then has a number of apps sitting on top of the data delivering results and outcomes. While Core Mobile has mobile apps for doctors, patients, and carers to help optimise care processes, and share patient information with authorised recipients.

So lots of interesting things happening in this sector right now and much of the innovation is down to SAP’s decisions to 1) turn it’s HANA database into a platform, and 2) to initiate the Startup Focus program. Now that IBM is going the platform route with it’s Watson cognitive computing engine, we’re likely to see a lot of healthcare innovation emerging there too.

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Technology is completely revolutionising the healthcare industry

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Healthcare is changing. Recent advances in technology are completely revolutionising how we approach the prevention, diagnosis and treatment of illness. And this is just the beginning of what will be a technological revolution in healthcare.

Smartphone use is growing at an enormous pace. They now account for 87% of the total mobile handsets in the US, for example. And with the smartphones has come hundreds of new apps related to health and fitness. These apps do everything from monitoring sleep and movement (steps), to keeping track of glucose levels, blood oxygen, and even ovulation.

Fitbit Dashboard

The relentless rise of wearable connected devices is also having a big effect on people tacking their health and fitness. These small devices (such as the Fitbit Force, the Jawbone Up, and the Withings Pulse) are light and easy to wear, and they communicate with apps on the smartphone to monitor and record health-related information.

The next evolution of wearables, where they are built-in to the clothes you wear, has already begun. If these devices become as ubiquitous as smartphones, they will help us make far better informed decisions about our health and fitness.

Then you have major players like Apple going on a hiring spree of medical technology executives to bolster its coming Healthbook application, as well as its rumoured iWatch wearable device. Samsung too have wearable fitness trackers and announced their own Healthcare platform “to track your every move” today.

Going further back the stack, and we see IBM using its artificial intelligence play Watson to make inroads into the health industry (see video above). IBM has been partnering with WellPoint Inc. and Memorial Sloan-Kettering Cancer Center to help clinicians better diagnose instances of cancer in patients.

And more recently IBM has announced that it is working with New York Genome Center to create a prototype that could suggest personalised treatment options for patients with glioblastoma, an aggressive brain cancer. From the announcement:

By analyzing gene sequence variations between normal and cancerous biopsies of brain tumors, Watson will then be used to review medical literature and clinical records to help clinicians consider a variety treatments options tailored to an individual’s specific type and personalized instance of the cancer.

And IBM aren’t stopping there. They announced last month that they were opening up Watson as a platform so developers can create apps that can utilise Watson’s cognitive computing engine to solve all kinds of difficult problems. And earlier this month IBM announced that several “powered by Watson” apps have been developed, including one to help dermatologists better diagnose skin cancer.

And IBM also announced the acquisition of Cognea. Cognea offers virtual assistants that relate to people using a wide variety of personalities—from suit-and-tie formal to kid-next-door friendly – think Siri, or better yet Cortana for Watson!

Then, newer in-memory database technologies such as SAP’s HANA, are being used to crunch through datasets so large they were previously to big to query. For example, SAP announced today a partnership with the Stanford School of Medicine to “achieve a better understanding of global human genome variation and its implications in disease, particularly cardiovascular disease”. From the release SAP goes on to say:

Researchers have already leveraged SAP HANA to corroborate the results of a study that discovered that the genetic risk of Type II Diabetes varies between populations. The study looked at 12 genetic variants previously associated with Type II Diabetes across 49 individuals. With SAP HANA, researchers in Dr. Butte’s lab were able to simultaneously query all 125 genetic variants previously associated with Type II Diabetes across 629 individuals. Using traditional methods, this analysis on this amount of data would have taken an unreasonable amount of time.

So, the changes which technology are bringing to the healthcare industry now are nothing short of revolutionary. And with the likes of SAP’s HANA, and IBM’s Watson, set up as platforms for 3rd party developers, the stage is set for far more innovation in the coming months and years. Exciting times for healthcare practitioners, patients and patients to-be.