We apply data science and machine learning to the universe of published data and patient experiences to deliver the right information at the right time to cancer patients.
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About our project
The problem we solve: Cancer patients are the user's of our app. Simply put - they can get information quickly through self directed internet searches, or they can get highly personalized information (if they ask the right questions) during periodic doctor visits - BUT THEY CAN'T DO BOTH. As a result, patients don't have the data/information/tools to: 1) make optimal decisions around which treatment pathway is the best match for their personal goals (e.g. minimizing side effects), 2) know if there are legitimate alternatives to their current treatment plan, and 3) have the ability to quickly identify what clinical trial may be appropriate for their condition.
On the customer side (cancer therapeutics) - companies spend millions of dollars on sub-optimal data products to track market share, identify real world clinical pathways, and currently have no way to collect patient reported outcomes.
About our solution:
qlaro provides a mobile app that derives simple questions from established treatment guidelines for patients to ask their doctors. qlaro then takes the answers of those questions (e.g. My cancer is platinum resistant) to build a unique clinical profile for each patient, and uses data science and machine learning to match the patient with the information and people they need to manage their condition.
qlaro uses the data collected from patients to track patient reported outcomes and create an anonymized population health db that can be sold to healthcare enterprise customers.
Progress to
date:
Over the past year we have been working with a focus group of ovarian cancer patients to identify key product requirements based on the needs of their treatment regimens and resulting side-effects. The patient response has been incredibly positive.
We currently have a product prototype and are building a PoC beta product for a pilot project we are designing for ovarian cancer patients with Kaiser Permanente in Northern California.
We have also secondary sites lined up at UCLA and Stanford to expand our pilot project once we can provide study conclusions from Kaiser. The gynecological oncologists we are working with at all these institutions are very enthusiastic - they see benefits to their practice related to improvements in patient compliance and satisfaction, and the potential for lower office time utilization.
About Our Team
Creator: Larry Cordisco
Location: California
Bio: I have twenty years of experience in the technology and healthcare industries, and over the past fifteen years I have established a successful record investing in these industries as a portfolio manager of a publicly traded mutual fund.
More importantly, I have real world experience managing the care and treatment strategies of close family members who have cancer. Through that experience, I identified an unmet need for a mobile app to guide patients through their entire care experience based on the unique details inside their own clinical record.
Over the past two years I have been working to create qlaro, a highly personalized navigator for cancer patients.
Title: CEO
Advanced Degree(s): MPP, MBA
About Team Members
Larry Cordisco
CTO, PhD - Health Informatics, UCSF Biography: Andy has deep experience as a technologist and health informaticist, and is currently a professor of health informatics at the University of San Francisco School of Nursing.
Title: CTO Advanced Degree(s): PhD - Health Informatics, UCSF LinkedIn:www.linkedin.com/in/avnguyen
The qlaro app makes it easier for cancer patients to make better treatment decisions, improve their quality of life, and find new treatment options and clinical trials. The app generates simple questions for patients to ask clinicians that are derived from accepted treatment guidelines. The app is designed to be a mobile solution that the patient can take into the doctor's office in order to collect data on their condition, and uses the answers to provide patients with highly personalized guidance from diagnosis to survivorship.
The app also has a social networking function that allows patients to either intiate a connection to others, or to have the app suggest connections based on similarities in treatment experiences or where patients currently reside within clinical pathways.
Finally, the data management system that the app is built on allows qlaro to integrate the experiences and data elements of entire patient populations to deliver synthesized observations about the latest trends in cancer care. "Within qlaro, 50% of patients who look like you are moving towards the use of PARP inhibiotors. Would you like more information?"
How We Help Physicians
Our pilot providers are working with us because: 1) they want to track compliance and quality of life metrics, 2) they want to improve patient satisfaction scores, and 3) they want to improve patient utilization metrics for their practice and think the app will hlep patient interactions be more efficient.
Challenge Mission
Key Milestones Achieved and Planned
Our business plan is to establish our product as a guide to cancer patients, engage patients up to 20 times a month by addressing the pain points related to finding the information and connections that help them better manage their disease, and then develop PRO and population data products once we establish a statistical meaningful population data set.
The next 6 months – we are currently working with an Institutional Review Board at Kaiser Permanente to design a pilot program to recruit ovarian cancer patients as the early access users of the qlaro app. We expect this project to be approved in the fall and patient recruitment to begin in early winter. This program will allow us to create patient engagement metrics as well as an early population data set around the use of PARP inhibitors by ovarian cancer patients.
Our 12 month plan is focused on three goals. First, expand app functionality from patients on PARP inhibitors to meet the broad needs of the entire ovarian cancer population. Second, test the recruitment of more users through new channels such as DTC advertising, partnering with patient advocacy and support organizations, and increasing awareness through professional medical organizations such as the Society for Gynecological Oncology. Third, we want to initiate collaborations with three therapeutics companies to develop the initial versions of our PRO and population data product.
By month 24 we would e
Our Competitive Advantages
For users, our competition ranges from self-directed internet searches to any number of point solutions that seek to address episodic pain points experienced by patients during the process of cancer care (e.g. patients like me, antidote) or provide access to better information or treatment trends for patients (e.g. the My LLS app from the Leukemia and Lymphoma Society). Our primary differentiation is 1) how we coach the patient through the care process by providing questions to ask their doctor, 2) our use of the patient's actual clinical data to match the patient with the right information and people, and 3) the breadth of functions built into our solution.
In the healthcare data market we see IMS health and Flatiron Health as our primary competitors. IMS is well known to be expensive, and primarily offers claims data. Flatiron collects its information from oncology focused EMR systems that it provides to community oncolologists. Our conversations with oncologists have revealed mixed reviews which may limit market adoption. In addition, Flatiron's data sets present gaps when patients go to providers not using the Flatiron EMR system, whereas our product follows the patient wherever they go.
Barriers to Entry
We have constructed a proprietary semantic data management system purpose built to address the data variety problem in healthcare. We beleive our solution enables a more accurate matching of patients with information they need, and faster time to market for new features and indications (breast cancer, etc.) We are electing to treat this technology as a trade secret at this time.
More broadly speaking, we strongly beleive that establish patient trust will be a huge barrier to entry in the field of clinical decision support tools for patients. As such, we are incredibly mindful of how we are designing the product to address patient needs.
Traction, Funding and Partners
We have raised $150k from friends and family and are currently initiating outreach to angels to support the MVP to be used in our Kaiser pilot.
Innovation Details
Intellectual Property Summary
We have purpose built a semantic data management system to address the data variety problem in healthcare. This system focuses on optimizing the data hygiene needs so that data science applications such as NLP, SNOMED concepts and machine learning work better. The net effect is we believe our solution works better (data accuracy) and faster (onboarding of new use cases). We are curently treating the key components of this data mangement system as trade secrets.
Clinical Information
We have performed a number of proof of concept trials around reading and quantifying the data contained in electronic medical records and indexing the information in clinicaltrials.gov to make the site more searchable.
Regulatory Status
n/a
How we will use the funds raised
The funds raised will directly suppor the product developmemt for our pilot study with Kaiser Permanente, in which 20 ovarian cancer patients will test the app over three months to measure the accuracy of patient reported data captured in the app compared against their actual EMR, satisfaction improvement of cancer patients using the app, measurement of patients onboard experience and QoL while taking PARP inhibitors, engagement frequency of cancer patients, and patient responsiveness to survey prompts and questionnaires.
Funds will support UX development for iOS devices, the integration of product features realed to quality of life metrics, side effect tracking, treatment comparisons and a clinical trial finder. Funds will also support an in-house clinical analyst for qlaro to interpret patient records, and a research assistant to conduct the internal research study at Kasier.
Thank You
Anybody who has been touched by cancer knows the feeling of helplessness and unknown that associated with fighting this disease. qlaro provides a tool that informs and empowers patients to have more confidence about their treatment decisions, better manage their quality of life, and find the right information faster than is possible today. We designed qlaro to do these things, because we have experienced the patient pain points of not having the right information at the right time.
Investor Info
Market Size
Currently $135B is spent annually in the US on the cancer care of 1.8m newly diagnosed patients and 14m patients living with cancer.
Today large therapeutics companies spend millions of dollars a year on data services and doctor surveys. In total, it is estimated that the healthcare data services generates $10B in annual revenue. We estimate our own TMO for qlaro at more than $5 billion based on our bottoms up analysis of the market for data services: There are more than 400 meaningful companies in the oncology space (therapeutics, diagnostics, providers and payors) x 25 most common cancers (80% of annual dx) x $500k /customer the average customer relationship size.
Projected 3 Year Growth
By year three, we forcast 20 customers will be paying for data sets related to 3 cancers. At an average customer relationship of $250k/cancer data set, the result is $15m of annual revenue. Based on development and maintenance costs for the app and the customer facing data products, the unit economics of this solution support 40% gross margins at this point in the company's lifecycle. We expect to finance our expansion strategy (an app for the 25 most common cancers), through a series of equity raises over the next 3-5 years.qlaro is a free product to patients (the users of our app).
Revenue Model
qlaro is a free product to patients (the users of our app). We will monetize by selling PRO products and population data sets that we create through user engagement. For example, in ovarian cancer, our initial launch market, we will collect data from patients who are being prescribed PARP inhibitors that will allow us to quantitatively measure side effects like fatigue, and the degree to which patients are involved in selecting a treatment regimen among the three approved drugs on the market. Currently, none of this data is captured in physician clinical records. We will also be in the front lines of capturing prescription trends and market share among the approved drugs, as well as patient intent towards future therapies. We intend to charge ~$50k per data set, which allows our customers to purchase only the data products that are important to them at a cost much lower than current market offerings.
Competitors
For our users, qlaro presents a highly differentiated user experience, one that is both highly personalized and holistic. The personalization is a function of applying data science and ML to a patient's acutal clinical record. From a holisitc standpoint, the app incorporates key functions (e.g. general info, treatment comparisons, side effect tracking, social networking, clinical trial finder) in a single integrated solution that addresses patient pain points from diagnosis through survivorship.
For our customers, we provide access to a data set that follows the customer regardless of whatever provider they see.
Traction
We are currently involved in customer development conversations with three large biopharma companies (all with Mkt caps >$15B) about creating data products around patient data sets. All three companies have expressed a strong interest in using qlaro as a vehicle for collecting patient reported outcomes. For two of these companies we are working with the health informatics group, and for the third company we are working with medical affairs.
Due Diligence Docs
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I have twenty years of experience in the technology and healthcare industries, and over the past fifteen years I have established a successful record inves...
We apply data science and machine learning to the universe of published data and patient experiences to deliver the right information at the right time to cancer patients.
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