How genetic testing will help personalize your medicine

How genetic testing will help personalize your medicine
How genetic testing will help personalize your medicine

For much of modern medical history, treatment has centered around the average patient. Discovering treatments which work for most people, most of the time has been a necessary starting point. However, treating every patient according to an average is rarely the most effective treatment method and can potentially even cause harm in some cases.

When the U.S air force first designed its planes, it based every measurement of the cockpit — from the shape of the seat, to the height of the windshield, to the distance between seat and pedals — according to the average of dimensions from hundreds of pilots. Nevertheless, unexplainable crashes kept occurring.

A young researcher tasked with studying the conundrum discovered the flaw: no individual is average. By replacing the average-sized designs with new versions that could be adjusted to the individual, the problem was solved. Now we are discovering that the flaw of averages — and the need for personalization — is equally important in medicine.

We now know that certain ethnic groups are more susceptible to genetic conditions and respond differently to treatment. Likewise, women can present with very different symptoms to men for the same disease. Genetic testing moves vastly beyond even these differences — opening up treatment possibilities tailored to each specific individual.

Safer prescription and administration of drugs

Individual genetic makeup can uncover the difference between an effective drug and a severe allergic reaction. The study of how genes affect drug response is known as pharmacogenomics.

Genetic differences can determine which drugs are selected for treatment. One drug, ivacaftor or Kalydeco, is used to treat cystic fibrosis — it’s a first-line treatment, but only for the 5% of CF sufferers who have a specific genetic mutation.

In other cases, genetic testing is used to determine safe dosage levels. Thiopurine drugs are used to treat leukemia but can cause dangerous levels of bone-marrow suppression. The dosage window between effective treatment and toxicity is small. Individuals with a certain TPMT gene mutation are ten times more sensitive and have a ten times smaller window — genetic testing can identify them and protect them from these toxic side-effects.

Advanced cancer treatments

There are over 100 types of cancer and over a third of people will be diagnosed with one of them at some point during their lifetime. As the second biggest killer after heart disease, few people escape its effects — either via themselves or by seeing their loved ones affected.

Cancer is caused by mutations within a cell’s DNA which cause it to grow abnormally and uncontrollably. Some of these genetic mutations are caused by exterior damage — sun and smoking, for example — while some are present at birth. Genetic testing of an individual can evaluate their risk of developing certain types of cancer, but tumours can also be genetically tested to determine their makeup.

One of the first examples of personalized medicine, dating back to the 60s, involves a breast cancer hormone therapy known as tamoxifen. It targets estrogen receptors present on the cancer cells. Some breast cancers do not exhibit these receptors — rendering tamoxifen useless in these cases.

Understanding not only the genetic makeup of the patient, but of the tumour itself, has led to new classifications of tumours and new treatment opportunities. Whereas historically cancers have primarily been classified by the point they originate from on the body — lung, breast, pancreas — classifying them according to certain genomic markers opens up new avenues for effective treatment.

Early risk detection and intervention

Almost all disorders — whether genetic or acquired — are most effectively treated with early intervention. Genetic testing can be performed in utero, at birth and later in life.

Some disorders are easier to test for — those directly caused by a single gene or small number of genes, such as cystic fibrosis, sickle cell anaemia and muscular dystrophy. Where available, early intervention can be started as soon as the diagnosis is made, reducing the severity of the symptoms and improving quality of life.

Other more complex diseases can have dozens of gene variants associated with increased risk — over 90 gene variants have been linked to an increased risk of breast cancer. Genetic testing cannot directly say whether or not an individual will be affected in their lifetime, but high risk individuals can be better informed and prepared.

As modern genomics continues to advance, the progression towards personalized medicine will only accelerate. The potential benefits in terms of treatment efficacy, risk assessment and harm reduction cannot be understated.

The accumulation of this level of personal medical data, however, comes with its own set of challenges. Private genetic information can have significant consequences in the wrong hands — for example, when it comes to health insurance coverage. Patient security from both a technological and legal standpoint needs to be a priority, and here novel technologies such as blockchain can play an important role and create unprecedented value for the precision medicine ecosystem.


Shivom combines blockchain, A.I., DNA sequencing & cryptography to enable secure and personalized medicine. The Shivom platform works on principles of collaboration & integrity, allowing people to own, manage and monetize their data. By creating a web-marketplace, a network of genomic counselors, and a not-for-profit drug research unit, Shivom will build a global healthcare ecosystem, reaching even low-income countries where such services have not been previously available.

Importance of an Open Marketplace to Drive Healthcare Improvements

The rise of the precision medicine era made it clear that R&D is all about interconnectivity and data sharing. Data sharing ensures that precision medicine is brought to patients and healthy individuals faster, cheaper, and with significantly less severe adverse effects, leveraging information from the interaction between labs, biobanks, business management, Clinical Research Organizations (CROs), investigators, patients and a variety of other stakeholders. However, nowadays data sharing is often hindered, particularly in countries where health data is centrally managed and controlled by governments.

Moving genomics data and associated health information into routine healthcare management will be critical for integrating precision medicine into health systems. The Shivom genomics ecosystem can promote participants long-term investment in their own health and commitment to medical research. By contributing their data to a global genomics database, individuals enable various research studies, either by donating temporarily the data to academic institutions or selling access to the data to organizations for drug discovery, among other use-cases.

A number of initiatives across the globe aim to improve access to precision medicine personal health by providing health apps based on genomic and other health data, attempting to tackle the same problems from different angles, often unwittingly directly or indirectly in competition with one another. This stifles research and innovation and prevents medicine and healthcare in moving forward at the pace that it should.

Our aim is not to compete with existing efforts, but to provide an open marketplace for new ideas and applications that enhance the wellbeing of our members. Shivom’s vision is to become the number one genomic and healthcare data hub on the planet. To do so, it will require open collaboration, networking and partnerships rather than direct competition with existing third parties. This is why a lot of our time and efforts are spent on generating new partnerships that will allow us to expand our future service offerings and increase the value to both our donors and customers.

Potential areas of services in this marketplace include among others, health apps, nutritional and fitness advice, ancestry information, treatment plans, genealogy, disease predisposition, high throughput data analytics, pharmacogenomics, and lifestyle management. For example, a company that provides nutritional advice based on the genome data of their customers can consider joining our marketplace to offer the same service to all members of the Shivom network. Other examples of apps may relate to taste perception, drug metabolism, caffeine or alcohol tolerance, behavior, physical appearance, and many more.

Applications and services built on top of our marketplace will form an important part of the genomics ecosystem. Our partners may already have, or want to develop their own apps. Looking into the future, with new scientific discoveries, additional apps and services will be added as the community grows and attracts more projects to its orbit. Looking to the future as more personalized biological information becomes available, we aim to offer services that are based not only on genomic data, but also other ‘omics’ information. When combining genomic data with other molecular data, such as epigenomic, metabolomic, transcriptomic, microbiome data, and clinical information, the resulting uniquely rich dataset enables integrative analyses to be carried out at unprecedented depth and scale and facilitates new insights into molecular disease processes. Integrating data from different technologies is a rare case where 1+1 equals more than 2; the more data is combined, the more useful it is for research, and the more valuable the scientific insights. Linkage of multiple data sets at the individual level will allow for Big Data to be truly transformative.

By implementing on open, collaborative web marketplace will allow Shivom to reach grand scale faster, utilizing the magnifying power of network effects. Our aim is to build a large community, and to get people engaged across the globe. By using the latest technologies, we plan to make this ecosystem highly user friendly and convenient such that anybody will be able to use it. By utilizing blockchain technology and next-generation cryptography, we will build trust around the ecosystem, shattering consumer hesitations about personal data storage online and in the hands of corporations. By being user-centric, Shivom is focusing on the rights of the user/donor and the customers that use this data for health care initiatives. [Join the Shivom vision by signing up for our alpha trial!]

— By Dr.Axel Schumacher(CEO of Project SHIVOM)
 — Dr.Natalie Pankova(CSO of Project SHIVOM)

Health Data to Empower the Individual

Each person has their own idea of what should be private and what can be shared with others.With the emergence of various global social media platforms (e.g., Facebook, Twitter etc..) people are more open to the sharing of their personal details. Even patient organizations (e.g. PatientsLikeMe) now provide the means to share in-depth information about health status and help to identify research opportunities for motivated individuals.

However, platforms that enable disclosure of private information such as health data need to be managed in a way where people can be sure that their information will be kept safely, confidential and used wisely, now and in the future. Similarly, patients/data donors need incentivization to use these types of platforms, i.e. they need to feel that they are getting value in return.

The Shivom platform makes it easy for everybody to monetize their genome and to support scientific research. Sharing data generated from human research participants must be done in a manner that appropriately protects participant interests. With blockchain technology (link to blockchain for genomic and health data blog), smart contracts are revolutionizing how data can be managed, taking up the role of classical ‘honest brokers’ which ensure the appropriate use of genetic information and effectiveness, accessibility, and quality of genetic services.

The Shivom platform provides a way for people to securely use their genomic data, by uploading data from multiple genetic testing services, and eventually by using Shivom’s own DNA kits, and providing them with incentives for sharing that information for research purposes. Once people have uploaded their genome sequence or after they got their DNA sequenced with one of our kits, they get access to various health-related apps and services across the entire platform, to manage their health.

Each individual can learn just what they want to learn about themselves. Sometimes, people want to know only parts of their potential future, in particular only information that has actionable consequences. This empowers donors to take control of their health by improving access to actionable information and by making more healthy lifestyle choices, including the ability to modify their disease risk.

By allowing allow every individual to share their genome through the Shivom platform, we are also aiming to eliminate genomic and healthcare data siloes, which hinder research and innovation. Maintaining a genome and associated clinical information on a blockchain can make information widely available while guaranteeing its authenticity and integrity. The decentralized nature of the blockchain allows any approved participants to join an information exchange pool, without the need to build data exchange routes between affiliated organizations. Patients can transmit genomic data or quantifiable lifestyle information to other stakeholders as they see fit. At the same time, the patient can keep sensitive information, for example, predisposition to substance abuse, hidden from stakeholders. As a result, outcomes research and precision medicine initiatives can be better supported. This framework also allows other stakeholders, such as employers or insurers to incentivize the individual’s lifestyle changes.

In this way, blockchain technology will also help people keep sensitive information, such as disease predispositions, mental health or substance abuse data from parties that patients may not want to access their health records (e.g. insurers), while ensuring that R&D efforts and treatments are still made possible. It allows patients to engage in more shared decision-making about their health with the healthcare providers of their choosing, enabling a greater patient-focused and patient-drive healthcare ecosystem.

— By Dr.Axel Schumacher(CEO of Project SHIVOM)
 — Dr. Natalie Pankova(CSO of Project SHIVOM)

Addressing Pharma’s Largest Drug Development Challenges

We live in a world where health care spending is upwards of trillions of dollars, and makes up nearly 18% of GDP in some countries. Yet at the same time pharmaceutical sales are sliding and healthcare improvements overall have stagnated. What is the root of this paradox? One answer is the substantial difficulty with which it has become to innovate in the drug development space.

Challenges in pharmaceutical drug development are vast, namely,

  1. An aging population that suffers from numerous “complex” disease such as atherosclerosis, diabetes and Alzheimer’s disease to name a few. These disease are not associated with one genetic susceptibility variant, but rather with numerous genetic associations, as well as various epigenetic or environmental factors such as diet, exercise, smoking habits and more. This makes it difficult to understand the direct mechanism of disease, and therefore challenging to identify a successful treatment. This is further complicated by a heterogeneous patient population where individuals present with various degrees of pathology, and the inability to model these diseases adequately in a preclinical setting.
  2. A slowdown in innovation, with reliance on similar compounds to those already on the market, targeting similar known mechanisms, or being of similar chemical structure to a drug that’s already successful. These follow-on drugs are known as “me too” compounds, and typically don’t generate a large amount of interest from pharma and investors as they are unlikely to become “blockbuster” drugs.
  3. The above result in increasing costs to produce a novel compound. It now costs over one billion USD to produce on compound from discovery to commercialization. And the chances of success are low, less than 1 in 10 000 that a discovery compound will be successful, particularly one that will bring in significant revenue — a blockbuster drug. Additionally, patent expiries of previous blockbuster drugs are driving generics onto the market, hampering large pharma’s efforts to maintain let along increase their revenues.

Together this points to the growth in R&D spending overpowering the growth in sales.

How can genomics help pharma address these challenges?

Most novel research is now done by start-up companies which subsequently form partnerships with large pharma. This includes biomarker and diagnostic companies, many of which focus on utilizing unique genetic variants to create tests for disease susceptibility, clinical trial enrolment and drug response. More infrastructure is being put in place by regulatory agencies to incorporate analytics and diagnostic tests into routine health care to make precision medicine a health care reality. This means increased opportunities for genomics to play a role in drug discovery and drug development, and with over 3 billion DNA base pairs in the human genome, the prospects for identifying new variants that play important roles in disease are promising. This opens opportunities for discovery of entirely new disease mechanisms and thereby development of novel lead compounds, rather than “me too” or generic products, new patents for pharma, and an overall increase in innovation.

Genomics will help address the challenges in the heterogeneity of the patient population, where drugs that work for some patients often don’t work for others, and non-responders are often cycled through multiple treatment routes until an ideal treatment is found, or in some cases not found. This can lead to multiple rounds of side effects and wasteful drug spending. With genotyping, potential responders to a specific treatment can be identified and stratified ahead of time. This also alleviates numerous challenges in clinical trial design, where multiple failures increase the roadblocks to bring new treatments to market. Finally, with genomic testing, pharma can focus on early preventative care for complex disease, identifying unique susceptibilities to disease before it becomes too late to treat.

Shivom’s role in addressing these challenges:

Shivom will propel precision medicine and preventative health by amassing genomic data from unique patient populations which will generate value for pharma’s drug development programs. In order to address current issues with patient heterogeneity and inability to tailor treatments for unique patient groups, Shivom is targeting emerging healthcare markets like Asia, Africa and South America where numerous unique patient data is plentiful. Emerging markets are also now very attractive to big pharma as they look for ways to grow their sales. However these markets pose their own challenges, including those in the genomics space. Namely, a very limited number of individuals having been sequenced to date.

Shivom has developed a partnership with the Andhra Pradesh Province in India with commitment from the government to sequence their 60 million person population. With this, and other large genomics data sets, Shivom looks to partner with pharma and biotech companies to analyze these genomes for variants that may be associated with disease, including the 7000 rare disease, 95% of which don’t currently have a treatment.

By utilizing blockchain technology, Shivom will also help bring together disparate information from across fragmented markets, diverse health care systems, and complex regulatory systems to integrate data together into one interoperable platform.

In doing so Shivom will drive precision medicine forward and bring health care into a new era.

By Dr.Natalie Pankova(CSO of Project SHIVOM)

The need for Inclusion of Ethnic Minorities in Genetic Research

Genomics is quickly becoming integrated into our health-care systems, and uncovering diagnoses for many diseases that were previously genetic mysteries. However, current genomic databases despite being extremely valuable for research, often lack a diverse representation of ethnic groups from around the globe. The lack of diversity limits the ability of ethnic minorities to benefit from advances in healthcare. Genomic databases mostly contain data from individuals of European descent. As a result, those genome-catalogues do not represent the global population, but merely the ‘white’ Caucasian population.

Why is this important? To understand how diseases are influenced by our genes scientists must determine how often certain genetic variants occur in healthy people. If the variant is very common in the population, it is unlikely to be harmful; simply because disease genes are unlikely to be transmitted over generations. Collecting all this information determines what is ‘normal’ in a given population and which variants may cause complications.

Indeed, people from African and Asian ancestry are currently more likely than those of European ancestry to receive ambiguous genetic test results after genome sequencing, or be told that they have variants of unknown significance2. That lack of coverage means that that some populations are still being left behind on the road to precision medicine and geneticists will continue to miss important information about disease biology. For example, many African Americans are being misdiagnosed with a disease called Hypertrophic cardiomyopathy, an inherited heart condition that can cause sudden cardiac death. The reason is that those people were under-represented in the databases that were used for comparison. Variants that doctors thought caused the disease, and were regularly used to provide patients with positive diagnoses, were actually found to be common among healthy African Americans3 for whom these variants were normal. Patients were sent home with diagnoses of hypertrophic cardiomyopathy who didn’t actually have the disease. For others, healthcare providers are unable to provide them with a proper diagnosis, or prescribe unnecessary preventative treatments. Such situations happen often in minorities, a problematic situation because individuals from these groups often present with genetic conditions unique to their communities.

There are many reasons for this situation, some populations are easily bypassed. For example, people may have limited access to modern medical centers (like in rural areas), or decide not to contribute their samples to research due to cultural or historical reasons. Obviously, we must diversify genomic databases so that everyone can benefit equally from the genetic revolution.

To move the field forward, we at Shivom started a large-scale project in collaboration with local doctors and medical centers in the Punjab province in India to sequence population subgroups that are typically not showing up in the established genomics databases. The study cohort will primarily be composed of individuals from a remote rural area, from underprivileged/poor individuals in several urban regions (those that have no housing and/or medical support), and patients of several hospitals, e.g., with severe inborn diseases. The northern part of India has more than 220 ethnic groups living in very diverse topographies. The economic burden in dealing with health issues could be reduced by precision medicine, which could be achieved by use of detailed genetic information. The Shivom Project will lead to a new understanding of the different ethnic groups of Asia, a region with the highest diversity of ethnic groups, and which puts this part of India in a unique position for the mapping of the human genome.

Getting reliable genomics and phenotypic/peripheral health data from low-income countries will dramatically change health outcomes and prepares the global community to deal with neglected diseases and even disease outbreaks. Acquiring large amounts of genomic data from patients and healthy people in Africa, Asia, the Middle East and other regions will become increasingly vital to correctly assess and annotate disease variants. Long-term, all human groups need to be well presented in genomic databases.

Together, by sharing underrepresented anonymized genomic information, we are making genome sequencing more useful and actionable for researchers and healthcare professionals — to benefit all people, all over the world.

— By Dr.Axel Schumacher(CEO of Project SHIVOM)


1. Popejoy, A. B. & Fullerton, S. M. Genomics is failing on diversity. Nature 538, 161–164 (2016).

2. Petrovski, S. et al. Unequal representation of genetic variation across ancestry groups creates healthcare inequality in the application of precision medicine. Genome Biol. 17, 157 (2016).

3. Manrai, A. K. et al. Genetic Misdiagnoses and the Potential for Health Disparities. N. Engl. J. Med. 375, 655–665 (2016).