Using Big Data to Personalize the Healthcare Experience in Cancer, Genomics and Mobile

7/27/2019 Using Big Data to Personalize the Healthcare Experience in Cancer, Genomics and Mobile

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Welcome. I am delighted you all could join us.


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Personalized Medicine.

People have been talking about Personalized Medicine and changing healthcare from

reactive to proactive for decades.

Now with rapidly evolving new technology , including cloud computing, computers

are able to generate, store and analyze large volumes of data.

There are three main trends in harnessing these large amounts of data or Big Data

to make leaps into personalizing the Healthcare experience.

Genomics sequencing and ultimately analyzing the human genome, and the effect

of the genome on individual diseases

Cancer/Clinical Trials using EMR/EHR, along with mobile data, pharma data, and a

number of types of data to look at the bigger picture of an individuals healthMobile Health Smartphones have permeated society, and now they are moving to

healthcare. Individuals are utilizing smartphones to monitor and improve health

outside the hospital.


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First off we have Genomics.

What is genomics?

It is the study of the human genome. With the influx in technology, cloud

computing allows researchers to store and analyze huge sets of data, like thehuman genome.

The primary focus of current genomics is on sequencing the genome affordably.

However there are researchers and companies also looking at analyzing the genome

and applying the information to causes for diseases.


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The history of genomics research can be traced back to 1956, when Rosalie Franklin,

Watson, Crick and Wilkins discovered the structure of DNA and recreated the double

helix model.

Recently, researchers have used Big Data technology to sequence the human genome

and better understand the role genomics plays in health and disease.


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Research in the field of genomics has come a long way in the past 60 years. The most

significant effort in studying the genome and its effect on disease, was the Human

Genome Project which changed sequencing form a manual process to an automated

computer based one, that used the existing technology. Not only was it monumental

in the study of genomics but also stands as an early example of data sharing between

public and private entities.

The project began in 1990, and was completed 13 years later in 2003. Goals of the

project included: sequencing, storing and improving tools for genome analysis. After

successfully sequencing the genome the project will transfer the work to the private

sector.

The Human Genome project was a project sponsored by the US Department of

Energy and the NIH. The project developed the technology to identify, analyze, andsequence all 20,000-25,000 genes in human DNA.


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By the time the Human Genome Project was completed the cost to sequence the

Human Genome was $40 million, down from $95 million just two years before.

Academics and companies have been working hard to make sequencing affordable

and therefore available to the public. Today the Human Genome can be sequenced

for around $5000 consistently and accurately.


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Today the cost is around $5000 per genome which is not affordable for the average

patient. And genomic information can go a long way in personalizing medicine.

However, it is clear that this is the future of medicine, and I along with many experts

in the field are predicting that we will reach the $100 genome in the next couple of

years.


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Here are some of the companies that are not only working on making sequencing an

affordable and routine part of healthcare, but also analyzing the genome. They are

closing the gap between sequencing and analyzing taking the sequenced genome

data and tuning it into information.

NextBio

Bina Technologies

Portable Genomics

These companies work sequencing the genome and storing the information alongside

other data, in order to analyze and personalize medical treatments and trials.


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Beginning with Bina Technologies. Bina has created a platform that allows users to

take genomic sequence data, move it, and analyze it. They use a hybrid architecture

that keeps some data on the premises and some in the cloud, pushing computation

back to where the data is in order to reduce the data 1000 fold and speed up

sequencing time and facilitating movement of the data. They are not working on any

specific disease, but on creating a platform that can be used for large data sets like

genomic data. Bina illustrates the power of genomics to improve population health.

Portable Genomics uses a mobile visualization platform for genomics that is related

to the consumers well-known iTunes platform. The visualization concept brings

genomics to consumers and professionals in a very simple way, immediately

understandable and useable in personalized and preventative medicine.

They are currently focusing on chronic diseases. Portable Genomics exemplifiesbringing the power of information to the individual,

Lastly we have NextBio, which uses a cloud platform that sits on top of existing health

systems to aggregate the medical data. It is the epitome of a One Stop Shop for

genomics, with a particular emphasis in Cancer. Their platform enables genetic

counselors, pathologists or the tumor board to make decisions regarding patient

personalized care.


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How is genomics contributing to the Personal Healthcare ecosystem?

Personal genomics is a key enabler for predictive medicine, for which a patients

genetic profile can be used to determine the most appropriate medical treatment.

People dont come in the same shapes or sizes, so medicine should accommodate

that. By combining sequenced genomic data to EMRs and other medical data,

physicians and researchers will get a better picture of disease in an individual.

Subsequently, treatments will reflect an individuals illness, and not a one treatment

fits all for diseases.
http://en.wikipedia.org/wiki/Personal_genomicshttp://en.wikipedia.org/wiki/Personal_genomics


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In addition to genomics in personalizing healthcare, cancer and clinical trials are

personalizing the healthcare experience.

Combining clinical trial data and genomic data, researchers have shifted focus on

diagnosing and treating cancer based on the cell mutation and not on the area of the

body from which it stems. For example treating the kind of mutation that causes

breast cancer, instead of treating all breast cancers as breast cancer.


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Many of the deaths from cancer are due to inefficient drug treatments.

As we can see by the pie chart, cancer drugs are ineffective for 75% of the

population.


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However we can see that this inefficiency is not only the case in cancer, but across

the board for a number of diseases. (Or alternately we can see even among

inefficient drug treatments cancer treatments remain the most inefficient)

Despite the fact that pharma spends 50 billion dollars per year on R&D to find drugs

that work, we still see high levels of inefficiency.

In an attempt to make cancer and other treatments more effective for individuals,

small start-up companies have turned their attention to using Big Data and data

analytics to personalize treatments.


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Here are some of the companies focusing on personalizing treatment for Cancer:

Explorys

Ayasdi

GNS


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Explorys is a cloud-based platform for storage and analysis of all clinical, financial, and

operational data related to patient care. To give you an example of size, it has 14

integrated delivery networks, with 200 hospitals, 40 Million patients and 100 billion

data elements. It works in Clinical Trials, the idea is to aggregate patient information

and analyze it on a real time basis.

Ayasdi uses a more esoteric topological analysis, a math of shapes, on their Iris

platform, to visualize data in a multidimensional graphic to easily show outliers and

high or low-response groups in the data, even without pre-specifying the

characteristics of those clusters. Their research is furthest in Cancer, where they have

developed a Cancer Genome, and have used their platform to find new biomarkers in

Cancer.

GNS Healthcare uses standard math and statistical principles to create what if,scenario models. Their REF next generation machine learning cloud platform engine

extracts predictive models from the data to determine comparative effectiveness and

create simulations across an entire patient population and on an individual level.

They have established themselves in many aspects of healthcare and are now taking

their expertise to genomics.


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By personalizing cancer treatment to the type of cell and not the area of the body,

cancer deaths should decrease exponentially.

A possible example is pharmaceutical developers, who integrate population clinical

data sets with genomics data, to better drugs approved in the first place and more

importantly, to get the right drug to the right person at the right time.


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In addition to genomics, cancer and clinical trials, mobile health is a driving force in

personalizing the healthcare experience. In the current digital health revolution

mobile phones and social media have redefined how we communicate, and online

games have redefined the gaming community drawing in a much larger audience.

Now healthcare is seeking to harness this power to improve health.


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Cheaper, faster, better technology is enabling most of us to connect with each other

anytime, anywhere; while specialized networks have changed the way we live, work

and play.

Mobile is ubiquitous; a 2013 Pew pool reported that 135.5 million American adults

own smartphones up from 80 million in 2010 with more exponential growth

expected. Mobile access anytime, anywhere through smart gadgets is putting cheap,

connected mobile computing power in the hands of millions of consumers and

healthcare practitioners.

Gaming has become an increasingly acceptable part of society, and now health apps

are utilizing this to improve and make managing chronic conditions or complicated

regimens easier.

Social applications of the apps include not just networking but crowdsourcing in

healthcare. Similar in concept to Weight Watchers and Alcoholics Anonymous we see

the online social networks that gives peer-to-peer support as a means to gather

motivation and support health related activities.


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Today there are over 96,000 health apps for mobile devices. Dr. Eric Topol Professor

of Genomics at The Scripps Research Institute, and author of The Creative

Destruction of Medicine: How the Digital Age Will Create Better Healthcare, shows us

what can be done with just a few of these mobile health apps.


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As the info graphic shows, of the 312 million people living in the US, mobile health

apps can help over 124 million people with hypertension, 105 million obese adults,

21 million people with sleep apnea, 79 million pre-diabetics and 81 million adults

with cardiovascular disease. These are huge numbers and this just addresses chronic

disorders.


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The potential for health apps and games are clear. Of smartphone users, 44% are

looking at using health apps in the future and see it as a way to better adhere to

treatment regiments. Of non-smartphone users, there is still an interest in using

mobile apps to improve health.


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Here are some of the companies that are harnessing the power of mobile to improve

and personalize healthcare:

Brain Resource

AchieveMint

Aetna CarePass, Ginger.io and OneHealth


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How is Mobile contributing to the Personalized Health ecosystem?

Mobile offers a way for individuals to not only keep track of their own health, but to

collect information in real time. Patients can monitor their own health and be

motivated to make healthy decisions about eating and exercising, along with

managing medication adherence. Now patients can literally take their health into

their own hands


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As of date, patients arent seeing Genomics, Mobile. Cancer and Clinical Trial research

in their trips to the hospitals. Comparatively few people have their genome

sequenced or their personal health data in their hand. Although mobile health apps

are catching on and there are exciting examples and success stories in Cancer and

Clinical trials using genomics data, these are just aprecursors of the future. But to

truly make a lasting impact on healthcare, and centering medical care on the patient,

companies and entities are going to have to engage in data sharing.

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An answer to this bottleneck is data sharing.

The scientific community, researchers and even companies are incentivized and

compensated based on their individual results, publications, and products. Data

sharing is an idea that promotes opening up data and technologies by sharing ideas in

order to improve the product. There are a number of successful examples of such

data sharing, including the Human Genome Project which I talked about earlier. The

Project illustrates data sharing between public the government - and private

company- entities.

Other examples of data sharing exist between start up companies and academia, they

include:

Harvard Medical School & GNS Healthcare

Ayasdi & UCSF Medical Center NextBio & Emory University

Oregon Health and Sciences University & Intel

MD. Anderson and Oracle

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These are just the beginning steps in sharing data. We need data and sharing on a

much larger scale and data sharing to improve the healthcare experience in the

United States.

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How can you as an individual participate in data sharing? The answer is Citizen

Science. Different from Data Sharing, citizen science is a form of crowdsourcing

dealing with the collection and analysis of parts of the data.

There are two layers to citizen science, collection of data from individual citizens and

analysis of data by individual citizens. In healthcare, anyone can donate their data

like their genomic data or EMR data for clinical trials, or collect data on themselves

through mobile apps.

Stephen Friend, White House Champion of Change and President, Co-Founder &

Director of Sage Bionetworks succinctly and accurately explained Citizen science is

the equivalent of a night science raid on nature. They can grab something and come

back with results.

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Are you doing your part in data sharing? Would you like to share your data? Would

you like to join the citizen science movement to catalyze the personalization of the

healthcare experience? Here are three great ways to get involved:

1.Stephen Friends company Sage Bionetworks is the epitome of data sharing.

Working in an open environment and promoting collaboration across disciplines

members can combine their knowledge and expertise to make new discoveries.

2.uBiome lets you donate your xxxx for science

3.Online there are a number of sites like ScieStarter with games like Fold-it that allow

individuals to take part in the analysis of data

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Data sharing and citizen science is driving this revolution, and promoting the

aggregation of genomics, cancer research, drug research and mobile health to

personalize the healthcare experience.

The future of Healthcare is moving to the individual. From genomics to cancer and

clinical trials, to mobile health. No longer will our health data be slipped into Medical

records in drawers in the far reaches of the hospital. No longer will we have to wait

long hours in an Emergency room. These elements of health are finally making

Personalized Healthcare a part of healthcare in the near future. In the next five years,

we will be holding our health into our own hands being treated with more accurate

and efficient treatments using new data streams and taking a holistic view of the

patient. Using Big Data to personalize the healthcare experience.

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Sharing song with the hands slide

Come together at the end

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Using Big Data to Personalize the Healthcare Experience in Cancer, Genomics and Mobile