About our project

The problem we solve: Only 15% of medical research provides useful information. For physician, patients/caregiver it is not clear which medical research is trustworthy and meaningful. Patients and Providers cannot be sure they have access to the best treatments and there is a substantial risk of both suboptimal and over-treatment.

About our solution: A SaaS solution that helps providers find relevant clinical research and identifies the clinical significance of it using proprietary classification systems/models. Our solution analyses clinical research based on 50+ data markers and determine the clinical significance (rather than the statistical significance) of it. When somebody searches for clinical research using other search tools, they will ‘just’ get results based on matching keywords. Whereas Zignifica ‘adds’ data/information to each research paper in terms of clinical significance. We also add ICD-10 codes to each paper we analyze in order to allow for integration with EMRs (and improve general searchability). We leverage AI (NLP / IBM Watson) to capture the data that is used for these algorithms. Our algorithms are based on what is taught in Med School, with the difference that we fully process these automatically leveraging AI technology and do an evaluation based on an easy to understand classification system.

•Development of Algorithms & Classification system for Diabetes, Cardiovascular, Oncology, COPD, Osteoporosis and Chronic Pain.

•Provisional Patent.

•Prototype in app stores with positive feedback on concept as well as willingness to pay.

•Started development of MVP.

About Our Company

How We Help Patients

For caregivers and patients it is typically impossible and in addition very frustrating to identify clinically meaningful clinical trials. Zignifica helps patients and caregivers to find relevant clinical research and provides a classification system (from A through F) to easily understand the clinical significance of that research.

How We Help Physicians

Zignifica helps providers find relevant clinical research (leveraging AI and Machine Learning) and easily understand the clinical significance through a proprietary and industry-first classification system, so they can spend less time on doing research and more time seeing patients while delivering better care at the same time.

How We Help Partners

We want to partner with Health systems in the USA and in Europe to trial our MVP in a primary care setting. Initially this will be through physicians logging into the solution, but can be followed by API based solution that will integrate with EMR to identify relevant and trustworthy clinical research for patient/treatment.

Challenge Mission

Innovation Details

Intellectual Property Summary

We have a provisional patent for the system to Evaluate and Report Clinical Usefulness of Findings in Clinical Research.

Clinical Information

Not Applicable

Regulatory Status

Not Applicable

How we will use the funds raised

Expand our alghorithms with additional research areas, to build our MVP as well as our Full Commercial Version and onboard 9,000 physicians by end of 2018.

We have just started our seed funding campaign for $850,000 which will provide a 12 month runway. This funding will be split as follow: Product Development: 61%, Marketing & Sales: 19%, Infrastructure/Support: 15% and Operations: 5%.

Thank You

Help us in our quest to make trustworthy clinical research available at the point-of-care for providers, patients and caregivers.

Thank you!

Kim Kristiansen, MD - Co-Founder & CEO

JG Staal, Co-Founder & COO

Investor Info

Market Size

Total addressable market is $1.1 billion based on markets in USA, Canada, Europe and Australia.

Projected 3 Year Growth

2018: $2.0M

2019: $7.5M

2020: $19.2M

Revenue Model

We sell our solution to physicians in Canada, USA, Europe and Australia. Our initial focus will be on primary care.

Our recurring revenue comes from a monthly subscription fee per physician.

Competitors

Unlike other clinical research tools, Zignifica allows, as an Industry-first, the ability for the physician to identify trustworthiness of research and relevance of research to a specific patient/treatment. We focus on clinical significance, rather than statistical significance.

Traction

We have received initial positive feedback on our prototype (available in AppStore and Google Play) on both the concept as well as the willingness to pay.

Due Diligence Docs

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Supporters

• 
  Alex Fair, MS
  11/02/2017 - Liked the project.
• 
  Francie Grace
  10/27/2017 - Liked the project.
• 
  Mark Jamilkowski, FSA
  10/25/2017 - Liked the project.
• 
  Inger Nørhede
  10/25/2017 - Followed the project.
• 
  Kim Staal
  10/25/2017 - Liked the project.
• 
  Kim Staal
  10/25/2017 - Followed the project.
• 
  Evan McDade
  10/25/2017 - Followed the project.
• 
  Miranda Menk
  10/25/2017 - Liked the project.
• 
  Miranda Menk
  10/25/2017 - Followed the project.
• 
  Ms. Barbara Rapchak
  10/24/2017 - Liked the project.
• 
  Katherine McEvoy
  10/24/2017 - Followed the project.
• 
  Katherine McEvoy
  10/24/2017 - Liked the project.
• 
  Sara Kristiansen
  10/24/2017 - Liked the project.
• 
  Akshay Kumar Vikram
  10/24/2017 - Followed the project.
• 
  Akshay Kumar Vikram
  10/24/2017 - Liked the project.
• 
  Kelcey Gosserand
  10/24/2017 - Followed the project.
• 
  Kelcey Gosserand
  10/24/2017 - Liked the project.
• 
  JG Staal, BS, Executive Master
  10/23/2017 - Followed the project.
• 
  Greg Aldin
  10/23/2017 - Liked the project.
• 
  Sharad Mishra
  10/18/2017 - Followed the project.
• 
  Sharad Mishra
  10/18/2017 - Liked the project.
• 
  Dimas Francisco
  10/17/2017 - Liked the project.
• 
  Kim Kristiansen
  10/17/2017 - Followed the project.
• 
  Kim Kristiansen
  10/17/2017 - Liked the project.
• 
  Inger Nørhede
  10/17/2017 - Liked the project.
• 
  Kim Taylor
  10/16/2017 - Liked the project.
• 
  Fredy Staal
  10/16/2017 - Liked the project.

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