We have fully built out our technology: a desktop application that instantly anonymizes source EMR, a web application that allows CRCs to upload the anonymized EMR, the back-end which understands and structures all data (including ICD codes, demographics, labs, and clinical notes) and writes to the EDC. Further, our robust quality management system documents our technological and operational workflows and specifies our compliance with HIPAA and 21 CFR Part 11. Since May 2017, we have been working with 2 EDC companies and, as of September, finished integrating with their systems. Our technology will go live on a maintenance study with an oncology CRO in November, and we have a planned pilot with a university hospital system in Sweden starting early 2018. Our business model is revenue sharing with our partner EDCs who charge for our technology on a per-trial, per-month basis.
Biography: BS/MS from Columbia in computer science. Served as a TA for the advanced machine learning course. Software engineer at Department of Defense with a focus on machine learning.
Advanced Degree(s): BS
Our technology helps physicians, PAs & research coordinators reduce repeated manual data entry tasks, identify errors sooner, diagnose clinical issues through our risk-based monitoring platform, and ultimately improve the patient experience by spending more time with the patient instead of at the computer. We have done over 3 dozen demos with research coordinators who have provided invaluable feedback regarding the design and functionality of our product, and they have had active input into creating a system that worked for them and saved them time. While our system does benefit sponsors, CROs, and ultimately patients, it is our end users - the clinical research staff - that we hope will be helped the most by eliminating manual data entry processes and focusing on the patient & clinical experience.
By helping the clinical research staff, we help hospitals as well. Particularly, we are passionate about helping community & rural hospitals attract clinical research despite a smaller staff. By eliminating tasks and allowing staff to focus on patients, we hope that they can undertake innovative clinical research just as effectively. Overall, we hope to enable hospitals and research teams identify adverse events through our risk-based monitoring platform ultimately deliver innovative therapies faster.
We help three primary types of companies in the clinical research ecosystem: sponsors (pharma), CROs, and EDCs.
We help sponsors and CROs reduce trial time, monitoring expenses, delays due to protocol issues, ultimately to actualize the promise of real-time monitoring. By removing manual data entry processes at the site level, issues are identified as patients visit the clinical site, not weeks or months later. Our goal is to reduce trial delays and expenses tactically, while enabling faster strategic data-driven decisions around site compliance, safety & efficacy.
Milestones achieved include building out our EMR processing & structuring API/backend, successfully partnering & integrating with 2 EDCs, incorporating language translation at ingest, and building out our quality management system and HIPAA/Part 11 compliance. Our next milestone is successfully executing our pilots with each EDC partner, which we estimate will occur in Q1 or Q2 2018.
We currently know of no other competitors, however it is possible for other market entrants. Our technology is fairly novel in that it solves multiple bottlenecks that prevent true remote, real-time monitoring: ability to work with any EMR provider/schema; elimination of a need to go through IT, build a high-footprint HL7 interface, or pay for data from the EMR provider; anonymizing the EMR source; automating the CRF-write process in a user-friendly way (by providing linkback for easy verification and edit tools for the rendered CRF); and enabling remote SDV for the CRA with side-by-side source and CRF analysis.
Further, we believe our novel strategy of growing with our EDC partners instead of trying to compete against them allows us to more seamlessly and quickly integrate into trials and avoid experiencing a lot of pain while learning about the clinical trial ecosystem and peculiarities.
While we have filed a utility patent on our technology, it is common knowledge that software patents are notoriously difficult to defend. We believe that our proprietary technology, which to date lacks clear competitors, as well as our process for ingesting EMR data and automatically writing to the EDC, is very difficult to replicate. Further, our relationships with existing EDC companies help us greatly accelerate our time to market and put us in a position to solidify early-mover advantage - as we have learned in clinical trials, technology is only a small piece of the puzzle. There are several interrelated entities that must all work together to achieve a successful outcome. The EDC is the center in terms of housing and analyzing all data & reporting for a trial - by plugging into their existing infrastructure, we are able to leverage it as if it were our own. This is a huge advantage over other tech companies that may be employing a traditional go-it-alone strategy.
We have bootstrapped our company to date. We are looking to raise another $50k of funding to cover our initial costs related to the pilots.
We estimate that our total market opportunity is $150M in the US. On average, we expect to charge a blended average of $1,000 / month / trial. Across all trial stages (preclinical to late stage) and types (academic vs. industry), we estimate there are 15,000 trials per year in the US and that the average trial takes 10 months.
Projected 3 Year Growth
Over the next 3 years, we aim to partner with 30 EDC companies who work on an average of 100 trials/year. This represents an annual revenue runrate of $27M and 20% market share (we assume we share 10% of revenues with our partner EDCs). In our first year, we hope to have completed trials with 3 EDCs (already signed with 2), with many more EDCs being signed up during our second year. During our third year, we hope to significantly grow our presence within each EDC by working across all trials that are going through their respective systems.
As mentioned above, our revenue model is to charge license fees on a per trial, per month basis to sponsors & CROs through the EDC. We assume that, based on what EDCs currently charge for their usage and add-on services, we can reasonably charge $1,000 per trial per month. To incentivize our partners, we share 10% of revenues with them on a long-term basis to help grow both businesses.
We currently know of no other companies with this particular offering. Most EDCs these days have their own eSource and wearables platform, which permit the clinical site to upload documents to the platform and enable crude remote monitoring. But there is little workflow and technical intelligence built into this - most importantly, this represents an additional cost for the clinical site (in terms of increased work) with no benefit, and therefore does nothing to solve the problem of material time lags between data creation (at the time of patient visit) and analysis (when the data is entered into the EDC and available for sponsors / CROs to validate and analyze).
We reached out to over 20 EDC companies and had interest from 12 of them. We then chose 2 EDCs whom we thought would be good initial partners as we developed our technology and introduced it in the clinical setting. Our product is fully built out, and we are now preparing to launch on 2 trials (one with each EDC), including a maintenace study with a large oncology CRO and a multi-site study with a university hospital system in Sweden. Finally, we have a strategic partnership with an international European CRO who provided us details about their workflows and the scope of the problem from an operational perspective, and with whom we expect to be launching trials with in Q2 2018.
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