Software maker Syapse (Palo Alto, Calif.) is on a mission to bring best-in-practice software to the genomics industry. Syapse has developed a software platform that serves as a functional bridge between laboratory information systems (LISs) and electronic medical records (EMRs). Syapse software allows labs and care providers to provide interactive molecular diagnostic test reports and decision support to providers across the clinical spectrum—from genetic counselors to oncologists or primary care physicians and even directly to patients. The software can aggregate omics, medical history, and outcomes data, and connect to third-party commercial interpretation providers, as well as public and open databases, such as ClinVar, COSMIC, PhenoDB, and OMIM. It can also accommodate clients’ proprietary knowledge and care pathways. DTET recently spoke with Jonathan Hirsch, the founder and president of Syapse, to understand how Syapse’s software can expedite the transition of molecular diagnostics and next-generation sequencing (NGS) into routine clinical practice and how the software can enhance the value proposition of NGS-based testing. The quantity of data generated from NGS-based testing is often cited as a barrier to clinical adoption. How does Syapse help alleviate this data bottleneck? Syapse is, at the end of the day, a software company that is bringing best-practice Web-application software to the clinical genomics industry. Labs are living in a world where Excel spreadsheets, FileMaker Pro, and similar tools are what people use on a daily basis to manage their data. Our goal has been to bring the modern enterprise software revolution, which has changed how every other industry stores, interrogates, and reports on high-volume, mission-critical data, into the medical world. Syapse software can store high-volume, post-analytical omics data, pair it with clinical data, and help with the clinical reporting of molecular tests. It can also aid in clinical decision support based on the tests. How does Syapse’s platform bring together disparate IT systems? You cannot take complex molecular test information, shove it in an electronic medical record, and hope to do anything productive with it. EMR systems are not designed for this. If you think about it, other specialized disciplines, like radiology, have their own systems—their own set of software that acts as their primary workbench. So, in this new area of omics and precision medicine, Syapse is a new class of software that can become the health care provider’s omics data platform and workbench. Syapse takes over where the LIS and EMR leave off and brings data from the laboratory to the point of clinical use. Everyone defines LIS differently, and that is part of problem. In our view, the LIS is just lab workflow. A sample comes in, you put it through a prep process, and then it goes on to the sequencer or some other assay technology. What happens after that? You get your results off the sequencer and out of the analytical pipeline, and typically the lab is taking that information and putting it into a spreadsheet or Word document. Our role in the process picks up after the analytical system leaves off, taking the post-analytical assay results to the point where you have a clinical report physicians will use. No longer will that be a Word document printed out, faxed to the physician’s desk, and scanned into the EMR as an image. We are taking that process and putting a modern piece of software around it so that at every single stage you are preserving the data in a richly structured format. How does this data improve doctors’ understanding of molecular test results? With a faxed piece of paper, you have basically sent the physician a flat piece of information that cannot be reinterpreted or visualized differently for different physician types. However, if delivered through software, you can take that same genetic information, reinterpret it using knowledge that reflects the physician’s world view, update interpretation over time as new knowledge emerges, and enable physicians who are knowledgeable about genetics to drill into details and explore the data. Most importantly, you can add clinical context to the genetic data. If the patient sees their cardiologist, the cardiologist may want to know about risk factors for cardiovascular disease, pharmacogenomics, and other clinically relevant genetic information that may not have been the target of the original test. Who is your client? What is the business case for using this type of software? We have two types of clients: testing labs and care providers. We are seeing tremendous adoption by hospitals, clinics, and other physician groups. Physicians are saying, we want molecular information, but we don’t want that piece of paper and we don’t want it in an EMR. The basic business use case is one of efficiency and automation, which is particularly important given cuts to reimbursement. This argues for automation and reducing manual labor, while increasing volume. If Syapse software can help you do five to 10 times the test volume without increasing labor, you come out on top. Another value to the lab is that physicians are demanding better reporting tools from laboratories, and now you have the requirement for patients to be able to access test results. Perhaps most critically, provider organizations are demanding the receipt of molecular test data as structured data in standard formats, a critical component of the next phase of meaningful use. PDF files and faxes will not cut it. All of these trends are playing in our favor. On the physician and hospital side, what we are seeing is that clinicians are ordering expensive tests, and they want to understand the clinical utility and cost-effectiveness of the data these tests provide. They want to be able to reuse test data whenever possible to get more clinical utility out of that single test. We are seeing a time efficiency argument for physicians as well. Difficult-to-use EMRs have cut into the physician’s available time; they are being inundated by ever more data led by molecular information, and so they seek out other systems to help them efficiently utilize complex omics data. How can this type of platform aid physicians and labs in meeting new requirements for direct patient access to lab results? Our software is very good at not just storing and reporting on complex molecular information, but providing different views of that information to different types of clinicians. That same philosophy and underlying capability then extends to patients. You may want, or now need, to enable your patient to view the results of molecular testing. Syapse software can take the same molecular test data you are reporting out and provide it in different views for the physician and patient. Our software can also package the results with different explanatory language that is more appropriate for patients. This is all at the discretion of labs and physicians as to whether and how they want to implement this using Syapse software, but the writing is on the wall as far as patient access goes. What is Syapse’s role in bringing NGS into routine clinical practice? There are factors that have little to do with us that are advancing the clinical genomics industry, primary among them is that the sequencers are not just getting cheaper, but they are getting far easier to use. Some would say we are already at the point where you can place a sequencer in a molecular pathology laboratory in a hospital and the hospital can do molecular testing internally, just like they do their IHC, FISH, and other standard assays. We are seeing this trend in hospitals across the country. The era of sequencing being done only in specialized, send-out laboratories is quickly coming to an end. We are seeing it become pervasive throughout the medical system, which means that testing is being repatriated and brought back into the hospital labs. Our role at Syapse in pushing forward the clinical use of omics is providing a software ecosystem so that the molecular pathology lab at every single hospital can have the same software power as a large reference lab with infinite software resources at their disposal. The challenge is less in the lab workflow and more in solving the problem of how to bring sequencing results directly to the physician in a way that they can make sense of, and for the provider organization, pairing sequencing data with outcome and cost information. We are shifting to a point where clinical utility of test results is the central problem, not data generation. That is where Syapse provides the most differentiated value: enabling physician utility of testing and building your evidence base for clinical utility. The myriad of available data sets helps in the clinical interpretation of these complex test results. How does Syapse keep up with this rapidly changing knowledge base? We are very customer- and user-focused. We are not going to tell the laboratory professional which data sets and what interpretive resources to use. Our job is to make it really easy to connect to any interpretive systems or public databases that you, as the lab professional or physician, want to use. You can make that determination as to what you feel is the most accurate or applicable resource. Syapse will then provide robust software interfaces and automation to connect to and integrate those interpretive knowledge sets. The other thing we are doing is working with hospitals and labs to enable knowledge-sharing networks, so that collaborating organizations using our software can share interpretive information seamlessly. So far, our customers have told us that this is a great approach to aggregating knowledge so that hospitals and laboratories are working off the same knowledge set that they and their collaborators contribute to, rather than each one reinventing the wheel every time they want to spin up a new molecular test. Side Box: Syapse By-the-Numbers Year Founded: 2008 Medical Concepts in Syapse Data Graph: 20,000 Data Sources Integrated per Customer: 10 Input Data Volume for Molecular Test Report: 500 megabytes to 10 gigabytes Report Generation Time: 1/1000th standard methods, achieved through software automation

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