February 18, 2020
A guide to big data-powered precision medicine
Since the completion of the Human Genome Project in 2003, precision medicine software started to leak into the real world, gaining approval from more and more organizations. The global precision medicine market was valued at $43.98 billion in 2018 and is expected to reach around $86.25 billion in 2025, growing at a CAGR of 10.1% according to Zion Market Research. Precision medicine is gaining ground with the advancement of such technologies as AI, mobile healthcare, and big data analytics that largely supports precision medicine.
However, the key enabler of precision medicine is the dramatic decrease in genome sequencing costs. Adroit Market Research reports that the cost of deciphering the genome dropped from $10,000 in 2011 to $1,000 in 2019.
The ability to sequence the human genome for creating targeted therapy and predicting patient health outcomes will increase the survival rate and improve life quality of patients with chronic conditions. However, we still have a long road to travel. From EHRs to big data analysis to clinical decision support and interoperability, healthcare organizations need to build a solid technological infrastructure based on healthcare software development first.
NIH defines precision medicine as “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” The White House’s Precision Medicine Initiative defines its mission as follows: “to enable a new era of medicine through research, technology, and policies that empower patients, researchers, and providers to work together toward development of individualized care.”
Precision medicine is based on the ability to manage and analyze big data, including genomics and imaging. The motto of precision medicine is “the right patient, the right medicine, the right time.” In other words, personalized healthcare can exist if providers are able to measure everything that affects a patient’s health:
All this information can give researchers and clinicians an understanding of therapy and interventions most beneficial for a patient. On top of that, precision medicine allows caregivers to streamline diagnostics and risk assessments for particular patients, based on their health profiles and genetic background.
For instance, there are cystic fibrosis treatments that only work for patients who developed the condition due to certain gene mutations. Other people have gene variants that increase chances of suffering from rare side effects under particular treatments. By identifying the gene variants prior to administering therapy, providers can assure patient safety and treatment efficiency.
Precision medicine brings many benefits for patients, but it also opens up opportunities for new revenue streams. For example, Mayo Clinic has launched Helix’s Mayo Clinic GeneGuide kit which allows patients to put saliva into a container and send it to the clinic for analysis. The clinic responds with a report estimating the patient’s risks across 15 health problems. The clinic also offers optional 30-minute consultations with genetic counselors.
Precision medicine holds great promise to reshape the healthcare industry with an increasing number of healthcare organizations adopting precision medicine solutions.
Precision medicine is largely based on genomics, which is considered a field rich in big data. Just one human genome sequence produces approximately 200 gigabytes of raw data. The Global Alliance for Genomics and Health forecasts that by 2025, 100 million genomes will be sequenced, amounting to over 20 billion gigabytes of data.
Cancer is an accumulation of changes in genes which control cell growth. Finding an optimal treatment for cancer patients depends not only on the body part where cancer has developed, but also on the genetic modification resulting in tumors. However, individual genetic tests are still not conducted for every patient, and there is no way for doctors to find the optimal treatment for each individual case. As a result, patients receive a combination of surgery, radiation, immunotherapy, and other types of treatment which work for some patients while causing deterioration for others.
Applying precision medicine and big data analytics, doctors will be able to examine the genetic changes exhibited by each patient and prepare a personalized treatment plan. Additionally, precision medicine implies that doctors investigate how a particular cancer treatment impacts the rest of the body, finding the optimal drug dosage to maximize the positive effect of the drug and minimize undesirable side effects.
Some cancers might never have a cure, but certainly we are going in the direction of achieving a time in which many of them will be a chronic disease.
Ana Teresa Maia
Former Vice-Director of the Centre for Biomedical Research
Bayer’s online service Test Your Cancer encourages doctors to submit samples of bone marrow, blood, and other tissue of their cancer patients. The company extracts the DNA from the samples and assigns every patient a genomic profile while enriching it with other available information. This allows the company to recommend a treatment plan that has worked for similar cases in the past.
Submitting biological samples to Test Your Cancer helps patients get a better picture of their disease. This was what the company literally did while asking patients to translate their thoughts about their cancer into drawings.
Even when medication is prescribed and taken properly, it can still cause adverse effects and instead of feeling better, the patient may end up in a hospital. Most adverse reactions to drugs are traced to protein enzymes in the liver which are responsible for breaking down drugs. Variations in those enzymes are determined by genetics, which means that a patient’s genetic profile is responsible for any exhibited adverse effects of drugs.
Genetic analysis helps reduce adverse effects to the minimum. Before prescribing medication, a healthcare provider orders a genetic test to understand if the patient’s genetic makeup can reduce the effectiveness of the drug.
Combining genetic data with other big data involving population trends enables healthcare organizations to identify patterns and propose more targeted medication to a group of people with similar profiles.
San Francisco-based Syapse, a company specializing in precision medicine, has partnered with pharmaceutical corporation Pfizer. Based on the terms of this partnership, Pfizer will have access to real-world data from Syapse’s network of healthcare organizations. This data will help Pfizer understand molecular testing and the impact of particular medication on different groups of people.
Stem cell manipulation is a part of precision medication. It helps patients to repair tissue that the body cannot repair on its own. Stem cells can be extracted and grown in culture, then forced to differentiate into any necessary cell type and returned to the patient when the process is completed. Tissue engineering becomes even more powerful when combined with technologies such as 3D printing. Then entire organs can be replaced.
Using a patient’s own cells for organ or tissue regeneration eliminates the risks posed by donorship, such as the immune system rejection of the donated organ.
Tel Aviv University was the first to invent a fully personalized tissue implant developed using a patient’s own material. The researchers claim that this technology makes it possible to engineer any tissue implant using just one fatty tissue biopsy. They are able to regenerate a spinal cord after injury and a brain affected with Parkinson’s.
Doctors’ traditional take on patients’ health tends to focus on EHR and physical examination results. Using big data-powered precision medicine for dietary plans implies broadening this perspective and including measurements such as regularity of food intake, sleep, stress levels, and the influence of lifestyle choices on gut microbiome.
Processed by AI algorithms, all this data will result in a personalized diet plans, which will improve patients’ current conditions and prevent (some) potential diseases. At the next stage, the healthcare provider should focus their efforts on constructing predictive models that will monitor patients’ response to food intake.
Personalized diet has captured the attention of EU agencies, giving rise to the INCluSilver project supported by the EU Horizon 2020 program. INCluSilver aims to encourage collaboration between different sectors including healthcare, agro-food, and information technologies to develop innovative ideas with the potential to reach the market. These ideas are focused on personalized nutrition for citizens over 50. Within this collaboration, INCluSilver intends to address the needs of the targeted population segment. The total budget of this project is €2,800,000.
Precision medicine can reduce care costs by prompting more informed decisions related to specific patients and allowing physicians to apply targeted therapy with a greater chance of being effective, avoiding side effects at the same time.
Precision medicine has the potential to transform the entire healthcare ecosystem. By providing cost-effective therapies that actually work, it can reduce healthcare budgets and, importantly for patients, we get disease-modifying therapies that can cure or prevent disease.
Partner at Strategy&, PwC Network
Even though healthcare organizations support precision medicine, it is a demanding area both technology- and resource-wise. Here are some major barriers to consider.
With more apps, devices connected to the internet of medical things, and precision medicine tests entering the consumer market, massive amounts of patient-generated health data are accumulated. With this data, many questions arise, for example, how this data is supposed to travel to a patient’s EHR profile and how to store it there, who will have access to it, etc. But that’s just the tip of the iceberg.
We still cannot sift through all the noise and clearly decide whether data findings are relevant at all times. On the technological side, genome sequencing is still advancing. On the clinical side, there’s no general methodology or best practices around precision medicine just yet.
Even within one health system, genetic tests can be ordered differently among facilities according to their own policies. Multiple labs use forms in various file formats, from PDF to Microsoft Word, and the resulting data gets into separate folders, which means that it should be preprocessed before it’s possible to extract any value from it.
Providers need to think not only about adapting the infrastructure for new data sources but also about creating standards for genomic test reports.
When patient data comes into play, its privacy gets under scrutiny. In order to reach efficiency at both individual and population levels, genomic data needs to be aggregated from a significant number of people within different patient groups. With these large data sets, it is unclear who owns the data legally. Still, if we want researchers to develop targeted medications and physicians to elicit personalized therapies, health specialists need to have access to this data.
As the field of genomics progresses exponentially, many health specialists will encounter the challenge of getting acquainted with precision medicine techniques and keeping their knowledge up to date. That means understanding what genetic variants to test for, when the test should be performed, how to request it, whether a blood sample or a mouth swab is needed, and whether the test result is actionable.
As patients, more and more people will start using direct-to-consumer testing. Although the test providers are doing their best to make the whole process transparent and comprehensive, patients can get confused about their risks of developing a particular disease.
According to ResearchAndMarkets, the precision medicine software market is expected to grow from $1.2 billion in 2019 to $2 billion by 2024 at a CAGR of 11.5%. It is time for healthcare organizations to think about incorporating those high-tech offerings and integrate precision medicine apps into their practices. Here are some implementation tips:
It is risky to choose a technology that is expected to support your organization’s specific needs both now and in the future while improving care. One of the requirements for the selected platform is to be integrated with the EHR. If the organization uses multiple EHR systems, the platform needs to be integrated with all of them. If the EHR system is to be replaced, consider how it will impact the adopted precision medicine platform.
One of the riskiest aspects of the CIO’s job is investing in advanced technology to support organizational needs—needs that evolve and change over time.
Founder and CEO of 2bPrecise
Incorporating precision medicine into your practice is a serious initiative that requires a dedicated team of software engineers and domain experts. It is not something that can be achieved with a one-person team working part-time on the issue. Make sure that decision makers are aware of the efforts required for this project, and that it is in line with the organizational goals.
While choosing the technology to adopt, think about the ways to make the transition to precision medicine convenient to the end user, and make sure that everyone understands the benefits it brings from the care delivery and financial perspectives. A precision medicine solution is a costly investment. Place strategies to ensure that it will actually be used.
Many generously funded and well-executed programs have resulted in disappointing utilization because their communities were not ready to adapt clinical practices in order to adopt precision medicine.
Founder of Translational Software Inc.
One day, personalized healthcare will become the primary option to treat patients. All therapies will be targeted toward a patient’s health profile, residence, lifestyle and socioeconomic environment. Right now, we are not exactly there.
Advancing in the precision medicine research and treatment will require information and technology. There should be system-driven standards and regulations to generalize internal policies across settings. Providers and researchers will need a modernized IT infrastructure to support emerging data flows without compromising security. Insurers will also have to embark on covering tests and treatments that anticipate patients’ needs and consider future risks proactively. When payers, providers, and regulators join their efforts, we will be able to reap all the opportunities presented by precision medicine.
Itransition’s healthtech consultants look at how medical image analysis redefines diagnostics and supports clinical decision-making.
We reflect on the most up-to-date applications of big data in medicine across the care cycle and explore the most relevant know-hows of the technology.
Read about Itransition’s 10+ years long cooperation with a US-based multinational to create their flagship pharmaceutical data analytics products.
We discuss several approaches to healthcare data security during the pandemic and offer some tips to ensure it. Read on to learn more.
Find out how machine learning personalizes patient care, alleviates pressure off doctors, and opens opportunities for innovative medical research.
What’s driving the growth in industrial robotics? We explore the influential factors impacting robots now they can see and learn on the job.
We take a look at varied healthcare mobile apps, connected devices, and overall industry trends to shape the mobile healthcare roadmap.