Staying ahead of diseases with personalized healthcare

It’s an all-too-familiar story: having a close family member or friend go through the ordeal of cancer treatment. The typical scenario would include some combination of surgery, chemotherapy, radiotherapy, or hormone therapy – all considered harsh treatments with side effects that can be life-altering and long-lasting.

Doctors today try to apply leading practices and established treatment protocols when treating cancer, but unfortunately, this all too often reverts to a one-size-fits-all approach that isn’t optimal for every patient.

But, what if cancer treatment could be less painful and long? What if practitioners could tailor a course of treatment based on a patient’s own genomic mutations, health history, or lifestyle, or even predict and arrest the disease before it happens?

We are entering a new era of healthcare, where disease-based care is about to be transformed into a new personalized approach towards healthcare, enabled by big data and Artificial Intelligence, or AI. This is precision medicine – a new and potentially disruptive force in healthcare.

In precision medicine, doctors will study patients’ data, created through medical techniques that are becoming rapidly adopted such as genomics and life sciences, and create a targeted course of treatment designed specifically based on the needs and unique genetic make-up of each patient. This data, coupled with the collective data of patients with similar diagnoses and backgrounds generated in the healthcare system, is the key to unlocking a new, exciting, personal way of delivering healthcare, which has the potential to be more effective and less toxic than traditional methods.

Precision medicine should play a big part in Asia’s developing healthcare systems, more than any other region in the world. We have two countries with the largest populations in the world, as well as some of the most densely populated cities. Tourism is also high, which may make Asia an easy target for communicable diseases. Disease contact tracing using genomics is an exciting new area that precision medicine can certainly help address.

Before healthcare practitioners can make informed decisions about their patients and the best way to treat them, they need data and insights to inform them. The biggest challenge facing personalized medicine has been in the collection, storage, analysis and sharing of this data, in a secure and cost-effective manner. Take, for example, genomics or genomic sequencing. It is computationally expensive, to translate the DNA data from a huge undecipherable mass of base pairs to actionable benefits for the patient.

While much of developing Asia and their public health systems will require some time before precision medicine becomes a reality, North Asia holds strong promise. Countries like Japan, Korea, Taiwan, and China are already digitizing medical records, with massive amounts of research and investment going into genomics, genomic sequencing and data analytics. Oncology and pediatrics could see the early implementations of precision medicine in these countries.

AI Driving the Evolution of Precision Medicine

Increasingly, AI is being applied to these healthcare data challenges to help drastically reduce research time. What took years in the past, may now be achieved in months, or even weeks. Significant developments in AI technology by leading technology companies, including Intel, will help bring about a seismic shift in diagnosis, treatment, prediction, and prevention. Intel, in particular, is launching revolutionary technologies in quantum and neural network processors that will help further accelerate advancements.

For example, the world-renowned Mayo Clinic is a healthcare organization that is using AI to turn the massive data that they’ve collected over the years into clear, actionable information that doctors can apply. Previously disparate medical data, such as X-rays or MRI images, lab test data and e-medical records, are collated into a single place, allowing doctors to have a broad picture of what the patient is facing and make better treatment decisions. Their approach to using AI could be a model that hospitals in Asia could emulate.

In the UK, researchers at the Medical Research Council have been able to predict heart failure in individual patients. A machine learning system analyzes huge datasets to determine the best-match cohort, and then make care/cost decisions in real time, automatically learning from experience and improving accuracy as it gathers data. This kind of predictive work can help doctors develop proactive or preventative care plans.

As AI analytics start-ups and research spreads across Asia, Machine Learning-based analytics is being put into trials around the region to target areas like re-admissions, sepsis prevention, and customer retention, but nothing mainstream yet. Initiatives such as AI.SG, targeting Healthcare, are encouraging start-ups and driving additional investment in the field.

In China, Intel, Alibaba Cloud, and LinkDoc, jointly hosted a competition to detect lung cancer, using AI technology. The goal was to assist doctors in early detection and enable better treatment options for the millions affected. The competition was well-supported with more than 500 participants from enterprises, universities, and academia taking part. The Institute of Computer Science & Technology from Peking University was the winner and more such competitions are planned for 2018.  A similar competition was also held in the US to detect cervical cancer.

For a hospital in Asia, Intel helped develop predictive analytics for a hypertension solution that incorporates clinical and self-reported data to predict risk. Patients use an app that shows them how changes in their lifestyle, as well as medical intervention such as anti-hypertensives, can change their risk profile.

A German biotech company, called QIAGEN, is working with Intel to bring the cost of genome analysis — the bioinformatics done on genome sequencing data — down. Their solutions can pinpoint genetic variations of cancer, allowing doctors to personalize an individual’s treatment and to monitor progress. Slow, complex clinical procedures of the past are replaced with efficient, automated workflows, so that the cost of genome analysis may be reduced to as little as US$22 per patient, per genome. QIAGEN has offices in Asia Pacific assisting many hospitals and clinics already.

Active Sharing Will Speed the Adoption of Precision Medicine

These projects have shown that the potential for precision medicine implemented in Asia may be achieved, in a secure and cost-effective manner. Critical for success is a medical ecosystem where people, policies, and technology interconnect.

A few more countries in Asia have early-stage projects in medical imaging analytics, genomics, and predictive analytics, and Intel has been actively running customer and partner workshops and events for experience sharing.

Given easier access to the right tools, if processes can be shortened and made cheaper, Asian healthcare organizations and researchers can spend less time analyzing results and more time creating tangible breakthroughs. The technology already in-hand can help change how diseases are understood, diagnosed and treated, and help medical professionals stay one step ahead of mutating diseases like cancer while driving progress for the healthcare industry.

 

This article was originally published on enterpriseinnovation.net and has been republished with the consent of the author.

Published on Categories Health & Life SciencesTags , , , ,
Mark Burby

About Mark Burby

With more than fifteen years of experience in healthcare IT, Dr. Mark Burby brings invaluable expertise to Intel as H&LS Sales Director in Asia Pacific. Being a surgeon in London and across the UK after graduating from Cambridge, Mark has gained a keen insight and deep understanding of the multifaceted workflows within healthcare organizations. Combined with his passion for technology, Mark had advised governments and healthcare organizations around their most complex technology challenges specifically on workforce enablement, infrastructure-enabled workflow and clinical collaboration. Prior to joining Intel, Mark led Cisco's Healthcare practice in Asia Pacific and was instrumental in Accenture’s Healthcare practice in Europe and Asia.