I founded Translational Software in 2009. Before that, I had a brief stint in a genetic testing laboratory and a 14-year career at Microsoft.
I graduated from the University of Bridgeport with an undergraduate degree in Economics and an MBA with concentration in Information Technology.
The company has kept me more than busy, but before founding TSI, I was on the board of trustees of the MOHAI (Museum Of History And Industry) in Seattle. I was chair of the exhibits committee as the new South Lake Union museum was planned, which was an incredibly rewarding experience.
If you were explaining Translational Software to someone who is not familiar with the organization, how would you characterize its primary areas of expertise? What solutions does the company provide for its customers? We are at the nexus of science and technology. Our Chief Science Officer spent ten years at the University of Washington developing databases for drug-drug and drug-gene interactions, and I spent 14 years at Microsoft learning how to make technology accessible. Our goal is to use technology to make the wealth of scientific knowledge that is becoming available simple to use for ordinary clinicians. Today our primary area of focus is in pharmacogenetics, but we have development in progress for other areas such as cystic fibrosis and tumor profiling.
Simply as a definition, what is pharmacogenetics? What will be its role in healthcare going forward? Pharmacogenetics is the study of how genetic variations among individuals affect the efficacy or toxicity of medications. From a practical standpoint, enabling clinicians to understand the role of pharmacogenetics allows them to prescribe drugs more safely and effectively. We are working toward the day when understanding the implications of a patient’s genome is the standard of care for prescribers.
How can genomics data be utilized by clinicians at the point of care? How have advances in recent years made the widespread use of such data more feasible? Today we interject ourselves into the laboratory process to provide a higher level of analysis for the test result. So rather than getting a report with A’s, G’s, C’s, and T’s or a person’s metabolic status, we report clearly what the guidelines are for prescribing specific drugs appropriately for that person’s genotype. Over the past several years, an enormous amount of investment has gone into improving the level of automation in clinical processes. So medical record systems will provide the foundation over time that will enable us to bind this more tightly into the clinical workflow.
Translational Software has developed a proprietary cloud-based platform/PGx portal that integrates genomics-based clinical decision support with laboratory and clinical information systems. Can you tell more about this and its applications? You can think of this as a technical platform and then a set of applications. The technology platform allows us to integrate with any laboratory information management system (LIMS); process inputs from all major genetic testing platforms; analyze the data to understand the patient’s clinically relevant genetic types (genotypes, haplotypes, etc.); and report on the data in a way that is customized to the recipient based upon the clinical context (e.g., cardiologist, psychiatrist, pain clinic, etc.).
The first application that we put in place was pharmacogenetics because we have world-class expertise in-house for providing insight to clinicians. With this in place, we are gradually expanding our knowledgebase and tweaking the technology to address screening for heritable disease, analyzing tumors for relevant targeted therapies, and other areas. So far, the results have been encouraging: expanding the core platform into these areas is significantly easier than building separate purpose-built systems.
How do recent developments advance personalized medicine more generally? What are the leading drivers of personalized medicine today? Innovations in testing technology and techniques are certainly advancing personalized medicine at an accelerating rate. The sheer accessibility of data makes it faster and cheaper to discover or verify new relationships between molecular profiles and clinical outcomes. By far the greatest driver for adopting personalized medicine is cost. If you can avoid re-doing a stent, or causing a major adverse reaction, or reduce an elderly patient’s mental fog to make him or her more manageable, it makes a huge difference in cost—and, of course, in the quality of life for the patient.
Will increasing public awareness of this kind of medicine play a role in its growth in the near future? Does the informed medical consumer have a part to play? It certainly does not hurt when precision medicine is mentioned during the President’s State of the Union address, as it was last year! And now that many treatment centers are actively advertising personalized medicine as a differentiator, it is creating a virtuous cycle of awareness. But realistically, doctors are trained to be conservative, and precision medicine was not a part of the core curriculum of most clinicians practicing today. So informed consumers will pay a role in asking the right questions.
What obstacles to the routine clinical use of genomics and molecular diagnostics still remain? Are reimbursement issues part of the equation? The biggest obstacle in actual practice is integrating with clinical systems so that doctors can order the right test and interpret results from the systems that they are already using. This is a huge area of investment for us. Reimbursement issues are the “Catch 22” that is holding back the industry right now. On the one hand, some payers are holding labs to stringent evidentiary standards, but labs do not have the profitability or the patentability that drug companies have, so there is nobody to pay for the clinical trials. This situation is slowly working itself out, but the time that it is taking means a lot of lost opportunities for cost savings and enhancing patient care.
You worked for many years at Microsoft before founding Translational Software. Technologically and organizationally, how does this background help you to succeed in your current role? What we are doing is similar in that it is always an arduous process to make software for complex processes straightforward to use. What is very different is that Microsoft programmers probably use the product they develop, whereas we build for clinicians that may not understand the genetic underpinnings of the end product. Building effective communication and collaboration between the developers and PhDs to solve these problems is a really hard problem, but it is incredibly rewarding when you finally get it right.