Menu
Precision medicine increases the efficacy of medical intervention by providing the right treatment to the right patient at the right time. Precision medicine not only results in better patient care, but also reduces some of the economic burden associated with challenging diagnostic odysseys and ineffective treatment plans. The advancement of healthcare technology has made the idea of precision medicine a reality.
One of the biggest leaps in precision medicine was the identification of actionable genomic variants, or biomarkers, for the targeted treatment of cancer. About a year ago, we celebrated the 20th anniversary of the initial Human Genome Project publication, which allowed us to see the entire sequence of the human genome for the first time. Initiatives to close the gap in understanding the human genome continue today. For example, the All of Us project aims to collect over 1 million genomic sequences to increase the diversity of the current genomic knowledgebase. This research allows us to use machine learning and analytical algorithms to analyze genomic data and identify causative variants which can be used to select patients for targeted therapies.
Understanding our genomic blueprint made it possible to turn the idea of precision medicine into reality. Today we have access to precision immunotherapies and CAR-T cell treatments that can be used as alternatives to, or in combination with, traditional oncology care. Pembrolizumab is a prominent example of an immunotherapy for cancer patients with PD-L1 variations. Patients are tested for the specific PD-L1 biomarker to be considered a candidate for Pembrolizumab treatment. Another example of precision medicine in oncology care is CAR-T cell therapy, in which a patient’s own immune cells are modified with specific chimeric antigen receptors to help them destroy cancer cells in their own body. There are currently six FDA- approved CAR-T cell therapies for the treatment of lymphomas, leukemias, and multiple myeloma, and hundreds of ongoing clinical trials to target other types of cancers. You can learn more about CAR-T cell therapy from the American Cancer Society here.
However, cancer is an extraordinarily complex disease - to identify the most effective treatment, providers will have to move beyond a one gene to one drug mentality and rely more on comprehensive multimodal patient data. Patient genomic profiles can vary greatly -, a recent study found over 5000 unique mutations in 628 cancer-associated genes across 54 tumor types1. Multimodal patient data aims to go beyond genomics, to consider more comprehensive biomarkers from imaging, proteomics, transcriptomics, epigenomics, and phenotypic and medical health information. By combining these -omic profiles we get a holistic view of the individual and we can create more fractionalized and specific cohorts of individuals with better-defined disease states. These highly specific disease states can be used by pharmaceutical companies to develop new, more targeted, therapies, increasing efficacy and resulting in better patient outcomes.
Similarly to how genomic information became actionable, the use of other -omic data will also require extensive data collection and knowledgebase creation to identify relevant variants for specific disease states. Through machine learning, we will be able to extract trends from relevant cohorts to provide data beyond what is available in current reference databases, to generate knowledgebases with more global inclusion, diversity and knowledge. Providers will be able to leverage this data to classify patient profiles and to confidently identify treatment plans using predictive outcome capabilities created from similar patient profiles. Advances in cloud-data storage and machine-learning algorithms make this future more of a possibility. The field of precision medicine continues to evolve but remains steadfast in its goal to provide the right treatment to the right patients at the right time. Increases in the analysis and utilization of multimodal patient health data will help healthcare institutions achieve that goal.
References
As an early adopter of our innovative technology, Protean BioDiagnostics’ President/CEO explains how his lab has already benefited from analyzing complex datasets with SOPHiA DDM™ for TSO500.
“Precision medicine is changing quickly. It’s getting more complicated. But it’s amazing to see how far we’ve come in a short time working with SOPHiA GENETICS,” explained Dr. Anthony Magliocco, President and CEO of Protean BioDiagnostics during a virtual discussion. “Our expertise is in tissues management and integration of data. We have to work with other experts and collaborate with them to fill gaps in our ability.” For this reason and others, Protean has worked with SOPHiA GENETICS to fill those gaps and further enable research possibilities for the clinical research experts they serve.
Protean BioDiagnostic’s vision is to bring precision medicine to all patients, regardless of where they live. That includes empowering community cancer centers and smaller labs (sometimes in very remote areas) that traditionally lag behind in developing digital workflows. Their patients could greatly benefit from the latest and greatest technologies. This is where the two companies have common goals, to evolve the landscape of medical research through Data Driven Medicine.
“SOPHiA DDM™ is a knowledge management system. It's able to help us curate the data and is continuously updated with connections to world databases. It’s a very important tool for us and our partners to simplify the analysis of complicated data. It allows our customers to better analyze the results from genomic profiles as well as clinical trial matches, which I feel is an often-unmet need in research,” said Dr. Magliocco.
Not every hospital system or regional lab has the storage capabilities for large sets of data that are generated with more comprehensive panels and testing. For this reason, the two companies’ shared goal of providing smaller labs advanced tools comes with options for cloud storage that are highly protected. Data storage security is a major priority for SOPHiA GENETICS users. We ensure that they are getting HIPAA and GDPR compliant storage capabilities no matter how large or small their lab may be.
“I’ve known SOPHiA GENETICS for a long time,” said Dr. Magliocco. Protean BioDiagnostics had an existing bioinformatics partnership with the SOPHiA GENETICS team and they signed on as an early adopter of SOPHiA DDM™ for TSO500 within the past year. “I became more interested recently with the work they’re doing with large panels. You're dealing with DNA and RNA and now you also have to deal with other markers in the DNA like tumor mutational burden and micro satellite instability. To be able to visualize it and report it back quickly and accurately makes this a very powerful tool. I’m also impressed by the experience of their bioinformaticians and their approach. They’re always trying to move forward. You know that the product will not be the same in a year or two, that it will improve. It’s a true partnership. I’ve been privileged to make suggestions from a user’s experience, and they actually make those new features available.”
The aim of improving technologies for SOPHiA GENETICS partners is to offer deeper, more accurate analysis. Larger panels may cast wider nets, but optimization with patented algorithms through our universal platform gives more actionable insights without sacrificing data quality.
“The real problem is integrating the data, putting it together, and giving it back to them in a way that's manageable so that it can actually guide treatment,” said Dr. Magliocco. “With the Bioinformatics provided by SOPHiA GENETICS, you’re able to pull together tens of thousands of variants, sift through them all, and get the ones that are meaningful. They highlight the significant data with reporting in a way that makes sense, while still allowing you to ‘open up the hood’ and look further, to see where this reporting comes from. They simplify the reporting, but I know that the complex data is still there if I have to go back and look for more answers. This is a great tool for further research.”
SOPHiA DDM™ for TSO500 is a fully integrated bioinformatic workflow (FASTQ to Report) for Illumina TruSight™ Oncology 500 panel. The SOPHiA DDM platform combines analytical performance with streamlined interpretation of complex genomic variants in the context of comprehensive genomic profiling.
Contact us today to book a demo and learn more.
As the demand for genetic testing continues to grow, more institutions are looking for ways to incorporate next generation sequencing (NGS) to augment their in-house capabilities. Increased access to genomic testing can help fulfill the promise of making precision medicine accessible to all, but the upfront investment required for institutions to start their own sequencing labs remains a barrier. To overcome this challenge, institutions can send their samples to service laboratories for testing and analysis, and this has traditionally been known as using a send-out service.
When using a traditional send-out service, samples are sent to a reference lab and the institution receives a report with the relevant findings. Outsourcing to reference labs does increase access to NGS tests, however, it can come with its own challenges. With traditional send-out services, institutions can struggle with turnaround time and a lack of data ownership or customizable reports. Turnaround time is crucial when trying to make decisions in a short timeframe. Access to the original sequencing data allows institutions to not only increase their knowledge of genomic data interpretation, but also enables the ability to aggregate data for further analysis that may be relevant for their region or field. The reporting needs of each institution can vary greatly, and not all reference labs can provide the flexibility in reporting needed to meet these needs.
SOPHiA Integrated Solutions presents an alternative to using a traditional send-out sequencing service. With SOPHiA Integrated Solutions, users send their specimens or nucleic acids to one of the sequencing partners within our global network. The chosen partner performs the wet-lab and sequencing work, and then the original sequencing data is securely transferred to the user via SOPHiA DDM™. This allows the institution to do their own interpretation with the help of powerful algorithms within the SOPHiA DDM™ platform. Through SOPHiA Integrated Solutions, institutions maintain ownership of the data which can be used for future aggregated analysis. The SOPHiA DDM™ platform also provides access to reporting tools with unlimited customizable reports so information can be communicated clearly and efficiently.
Undergoing a double mastectomy as a preventative measure can be a very difficult and personal decision. It was one that the whole world experienced with Oscar-winning actress Angelina Jolie when she quite publicly made her decision known in 2015. Through genetic testing, Jolie discovered she was predisposed to developing breast cancer, just like her mother and aunt. This clinical test gave her a new level of awareness about her health and changed her life forever. In this case, the doctor was in the position to provide her with preventive measures. However, Angelina Jolie is not an isolated case.
Women with close relatives who have been diagnosed with breast cancer are at a higher risk of developing the disease, and about 5-10% of breast cancer cases are thought to be hereditary. For those patients at increased risk of developing the disease, a comprehensive test for detecting mutations on BRCA1/2 and other well-known genes linked to breast cancer is crucial and will determine risk level. But most women are uninformed as to whether they are at risk for developing breast cancer.
The vast majority (90-95%) of breast cancer cases arise in women with no apparent close family history, making it more difficult to assess if they should be tested or not. This means there is an opportunity to improve the ways that they can learn about their predisposition. Thanks to technological advances and innovative data-driven medicine approaches, risk assessment measures now exist for all women. Through a simple test, the evaluation of the risk—a person’s predisposition to develop breast cancer—can be researched within a few weeks. In addition to Breast Cancer, many other hereditary cancers can be further analyzed.
Empowering informed decision-making
SOPHiA GENETICS is listed amongst the 50 smartest companies worldwide by the MIT Tech Review. Our mission is to democratize data-driven medicine globally. The company is already working with more than 780 healthcare institutions in 72 countries. Our AI-based platform, SOPHiA DDMTM, is already used to help healthcare professionals better detect and understand genomic predisposition of developing cancer even faster. Through an innovative multi-data source approach, SOPHiA GENETICS helps experts make sense of clinical research data, empowering more informed decision-making.
SOPHiA GENETICS developed a robust genomic application that analyzes the most frequently mutated genes starting from a blood sample. The presence of inherited mutations in these genes implies an increased risk of developing breast cancer. A positive result, however, doesn’t mean they will ultimately develop cancer. Follow-up care after a positive test result might include taking specific measures to modify the type and frequency of screening and define the appropriate preventive strategy. This depends on many factors including age, medical history, prior treatments, past surgeries, and personal preferences.
Women who don’t carry an inherited mutation rely exclusively on mammogram screenings as their preventive measure. Mammograms are often recommended to women around the age of 50, and participation rates in mammography screening programs are low. Women shouldn’t have to wait until then to know if they’re at risk for developing breast cancer. In fact, about half of all breast cancer patients develop the disease outside of the period of ages 50-69 and could greatly benefit from earlier detection. Today, we know that age alone is not enough to accurately estimate breast cancer risk.
Better screening—for everyone
Men can also be at risk for breast cancer. Examinations for men are often uncommon unless there’s apparent reason to screen. It’s important that men are just as knowledgeable about their genomic profiles as women. Recent studies have shown that men with BRCA mutations may have eight times as many cancers than what would be expected in the general population. Luckily, genomic profiling options offered by SOPHiA GENETICS can detect BRCA and many other gene mutations (variants) that give experts further insight into cancer research.
The path to your personal care starts with preventative measures that go beyond traditional means. Thanks to new technologies propelling data-driven medicine, a new era of preventative care could help clinical researchers stay a step ahead of cancer.
CLICK HERE TO GET IN TOUCH WITH ONE OF OUR EXPERTS TODAY
*This article was originally published in the Boston Globe as part of their annual Breast Cancer Awareness special coverage
Data Driven Medicine
Did you know that the “DDM” in SOPHiA DDMTM stands for Data Driven Medicine? You may have heard this phrase before. It’s become a common phrase across the industry as medical research evolves in the digital age. DDM is a term used widely these days, but one that SOPHiA GENETICS has championed from the start. Data Driven Medicine is clinical research that can expand the way we approach traditional medicine, powered by deeper data analysis.
The diagnostic journey can be filled with many unknowns for both patients and physicians. These unknowns are hiding amongst a massive expanse of medical data within each of us, waiting to be discovered, to further inform our personal healthcare. Having the most comprehensive amount of medical data properly analyzed and pre-classified in one single space, allows clinicians to arm themselves with the most pertinent information for their patients, ultimately aiding in the fight against concerning diseases.
SOPHiA DDMTM plays a crucial role in advancing medical research. It is an artificial intelligence-powered software as a service (SaaS) platform that’s currently used in hundreds of labs around the world to compile large sets of varying medical data from multiple sources.
Data optimization
Many larger hospital networks are already using instruments that produce these large amounts of medical research data. But many of those tests being run in the labs are becoming more in-depth, more precise, which means professionals are dealing with incredible amounts of new data each day at increasing rates. For this reason, fast and accurate analysis is essential in order to process more and more relevant information for patient research. This level of efficiency can also allow smaller labs to take on much more comprehensive testing, utilizing fewer resources than traditionally required.
Clinical research depends on accurate, reproducible results. What’s often overlooked is how much more productivity can be enabled within a lab when experiments produce consistent levels of accuracy with faster turn-around-times. This takes a lot of fine-tuning of clinical instruments, which can be yet another taxing and time-consuming process. The simple solution is optimized workflows that can quickly discover what users are searching for among their medical data. With SOPHiA DDMTM, variants of interest are discovered by elite algorithms and preclassified for the user so that they don’t have to go digging and sifting through all of the available data. Think of it like trying to find a treasure buried on a beach. It would be a lot easier to use a metal detector than to pick through each grain of sand.
The SOPHiA GENETICS factor
Since our beginnings, SOPHiA GENETICS has taken a global approach to supporting medical research. This means we designed our technology to be able to support many forms of medical data input, making us the universal platform of choice for more than 780 healthcare institutions worldwide. With Radiomics, we’ve taken our first steps toward true multimodal research.
If you’d like to learn more about the SOPHiA DDMTM platform, you’re in luck! You can book a demo right here through our website, or you could come and see us at the upcoming HLTH conference in Boston from October 17-20th.
So many labs had to turn their focus away from researching highly specialized areas of disease toward detecting, monitoring, and preventing the spread of SARS-CoV-2. While this change has been vital to help discover life-saving solutions like the vaccines, it’s also a focus-shift of resources that could make a mark in the realm of oncology research. That is, if labs are unable to dig themselves out from under those constantly growing piles of medical data.
How COVID-19 affected cancer testing
According to a survey conducted by the Association of Molecular Pathology (AMP) that included 163 laboratories worldwide, almost 70% said they had to decrease or stop the development and validation of certain tests for cancer research in 2020. Of those respondents, 48% reported it took much longer to receive any results from molecular cancer testing. Much of these roadblocks were due to shortages of reagents to perform tests, staff shortages, and overall limitations that were only made worse by the pandemic. The impact this may have on cancer research and treatment is not yet fully known. The total implications may not be felt within the industry for years to come. What is known is that cancer did not take a break during the pandemic and there’s much to be analyzed that had not been.
Studies cited in a Harvard Gazette report show that there’s been a sharp decline in routine screening – some reports decreasing by 85-90%. Fewer people are visiting their doctors in person. This means less people are catching the early signs of cancer that their physician could help discover in routine examinations. Some projections show that in the next five years, the death rate related to cancer could be 4-17% higher because of the limitations brought on by the pandemic. This is where data-driven medicine could come to the aid. By reducing the number of resources required to perform in-depth molecular analysis through NGS, labs may be capable of keeping up with growing demands for cancer screening.
How can a streamlined workflow solve for lab efficiency?
Each laboratory can only be stretched so thin when it comes to how many people or machines they have on hand. But analysis could be streamlined in ways that enhance the output from sample data. Next Generation Sequencing creates new paths for discovery in oncology and there are tools that bring further insights from that data. SOPHiA GENETICS has a large portfolio of solutions that can be utilized with SOPHiA DDM™. With accurate biomarker detection down to the exonic level, improved uniform coverage leaves less likelihood that you’re missing an important component that will better inform your results
SOPHiA GENETICS also offers a solution with Paragon Genomics for SARS-CoV-2 research and surveillance. By applying what we already know about optimizing analysis for oncology, the most relevant and essential data can be brought to the surface for faster and more precise reporting.
You can also read more about how our genomic experts have worked with international partners to offer new guidelines in amplicon-based SARS-CoV-2 genotyping.
Let’s say you have just had an amazing dessert prepared by a friend. You’d love to recreate this experience yourself. But instead of giving you a recipe with standard measurements you’re able to recreate in your own kitchen, they give you instructions like pouring a handful of sugar, half a glass of water, and three fork lengths of butter together in a bowl. Get the portions wrong, and the result may not be so sweet. Baking can be boiled down to a science if most recipes and ingredient measurements are standardized. The same concept can be applied in your genomic research labs.
Breakthrough research depends on replicable laboratory procedures and reliable analysis. Testing should follow universally embraced protocols in sample collection for the resulting data to be considered valid. The analysis and interpretation of data, no matter the lab of origin, must follow common metrics.
Standardization helps find variants
To measure results from one individual against those of a control group and those with similar genomic profiles, data analysis must be unconditionally repeatable. Standardized data enables variant detection and identification, batch analysis and genetic assessment. Valuable insight has a positive impact for researchers today and clinicians and patients tomorrow.
It’s hard to avoid normalization when talking standardization. Normalization, also known as min-max scaling, sets data values between 0 and 1. You normalize data if features that need to be compared have different origins. Normalization, however, does not account for outliers. And in genomic research, outliers are the very data points researchers are looking for.
Standardization, also called Z-Score Normalization, scales data to have a mean of zero and a predetermined standard deviation. Standardized data is not bound to a specific scale and ensures that, if various datasets are compared, they’re measured by the same deviation without compromising reporting quality to better identify relevant variants.
Standardization supports universal learning
Consider what’s happening inside all of us at a molecular level. It took decades to compile data for the Human Genome Project. In the past decade we’ve started to see how genomic ingredients create a unique recipe for each person.
To understand cancer, inherited diseases, or even COVID-19, we must understand the recipes, but also where they are mutating. We’ve seen medical research advance rapidly, especially with the efficiency required for COVID-19 response. Labs use different machines for analysis, different sample sources and different algorithms to discover new variants. But if they standardize data, research can produce desperately needed solutions in record time by peers working in labs across the globe.
Standardization is the future of Data-Driven Medicine
In order to advance the research being conducted for disease prevention, detectability, or the spread of a virus, data must be standardized so that scientists working in a European lab could easily share their data with other scientists in Asia or North America, while observing applicable laws. Without standardization of data, language barriers would be the least of our concerns when it comes to understanding the work performed by our international peers. Data standardization can be like a universal language that connects all research with one comprehensive purpose – to eliminate data corruption or “bad data” and preserve the work of thousands to be built upon for the future.
If you’d like to learn more about how SOPHiA GENETICS can help you create a more efficient workflow in your lab, you can contact us today.
How data accuracy can be improved with better algorithms
Your favorite song is playing on the car radio, but as you drive along, the frequency seems to hit a snag as hisses and pops infiltrate the music. The same song could sound much clearer on a slightly different radio frequency. It just might take some fine tuning. The process of tuning into a specific “clean” frequency is not unique to music on the radio alone. Medical research must be reproducible without the static.
How do we “tune” into data accuracy?
Some of the most concerning diseases of our time can now be studied in ways that scientists had only dreamed of decades ago. Through the evolution of Next Generation Sequencing, data becomes the lifeblood of new clinical research capabilities.
If you think of data accuracy like that radio signal, what you’re trying to do is tune into the right frequency, searching for your intended disease-causing variant. Ideally, your end result is to hear a perfect signal coming through a mess of static. It’s that signal that gives you the most accurate reading for what you’re searching for among the messy noise that’s naturally present in any given sample you may be testing. In order to finetune the end result, you must eliminate what is known as background noise. For NGS, this is a combination of the biases inherit to design. It looks like peaks of signals when visualized. Background noise could come from any outliers and excess datapoints that don’t apply to the research.
How can data be made better?
The new age of Next Generation Sequencing comes with massive amounts of data being analyzed each day at record levels. The amount of background noise in those datasets also increases on a major scale, making it more difficult to reach levels of accuracy that support your research.
Every single step of an experiment can introduce noise to the mix. Luckily, when data is muddied with irregularities captured throughout the analysis, it can also be cleaned. With advanced algorithms and exceptional analytical performance, it’s easier to identify variants of interest or to overcome any corruption of the data quality/accuracy. This is thanks to the ability to look past the “static” of background noise and zoom in on variants of interest with a higher resolution, sometimes down to 2-5 exons.
How can we further data analysis? It’s clear that the initial data capture is far from the final step in your research. In addition to the existing interpretation functionalities such as ACMG automated variant classification, virtual gene panels, and cascading filters as part of our platform, SOPHiA DDMTM for use with KAPA HyperExome offers extremely accurate detection of biomarkers in a single workflow. The solution and our platform include the Familial Variant Analysis (trio analysis) to automatically filter variants based on different inheritance modes. If you’d like to learn more about what we offer, contact us today.
SOPHiA GENETICS products are for Research Use Only and not for use in diagnostic procedures unless specified otherwise.
SOPHiA DDM™ Dx Hereditary Cancer Solution, SOPHiA DDM™ Dx RNAtarget Oncology Solution and SOPHiA DDM™ Dx Homologous Recombination Deficiency Solution are available as CE-IVD products for In Vitro Diagnostic Use in the European Economic Area (EEA), the United Kingdom and Switzerland. SOPHiA DDM™ Dx Myeloid Solution and SOPHiA DDM™ Dx Solid Tumor Solution are available as CE-IVD products for In Vitro Diagnostic Use in the EEA, the United Kingdom, Switzerland, and Israel. Information about products that may or may not be available in different countries and if applicable, may or may not have received approval or market clearance by a governmental regulatory body for different indications for use. Please contact us at [email protected] to obtain the appropriate product information for your country of residence.
All third-party trademarks listed by SOPHiA GENETICS remain the property of their respective owners. Unless specifically identified as such, SOPHiA GENETICS’ use of third-party trademarks does not indicate any relationship, sponsorship, or endorsement between SOPHiA GENETICS and the owners of these trademarks. Any references by SOPHiA GENETICS to third-party trademarks is to identify the corresponding third-party goods and/or services and shall be considered nominative fair use under the trademark law.