What if We Could Make a Spam Filter for Clinical Research

What if we could make it possible to navigate away from “the noise” and focus on what is relevant at the point of care?

We have developed a prototype of the Zignifica app doing that – and it is ready for testing.

Do you want to test it?




Imagine you could easily identify clinical research providing trustworthy evidence.
Imagine you could skip papers with results not relevant for patients or where the used method is insufficient.
We are developing Zignifica to do exactly that, and we need your help to test the prototype with studies from the field of pain medicine and pain management.
photo: bigstock.com
photo: bigstock.com

Researchers from Stanford University has estimated that only 15% of resources spent on clinical research provides useful information.

Studies presented in scientific papers may be clinical irrelevant in many ways and for many reasons. The design of a study may not be clinically relevant. The study period may be too short, outcomes may have limited clinical relevance, too small sample size, too many patients excluded, intentions and plan for research not published ahead, and many more reasons.

Results may not be clinically relevant by only being statistically significant, but not clinically relevant. As an example may a reduction in experienced pain intensity be statistically significant, but still too small for patients to feel. Other reasons may be benefit for only few patients, too many side effects, and much more.



Why are so Many Studies Not Clinically Relevant?

You may wonder why clinical research papers presenting results, that are not relevant are published at all. There are many reasons for that. First of all is clinical relevant studies often more time-consuming and more expensive to run. Healthcare professionals and especially academics often have an obligation and even pressure to ongoing publishing scientific papers. Studies may be designed to find results suitable to support and promote the use of particular treatment.


The Guide

Zignifica_mobileWe are developing Zignifica to let you distinguish between relevant and not relevant studies. Zignifica is developed to make an analysis of both method and results in papers presenting data from clinical trials. The result of the analysis are made by the sophisticated Zignifica algorithms and portrayed as two scores. These scores are combined and converted to a Zignifica grading system going from “A” (highly clinical relevant) to “F” (not clinically relevant). Each Zignifica class include several subgroups enabling detailed information e.g. “Br: May Be Clinical Relevant. Results are clinically relevant, but be aware of somewhat weak method/design”

While Zignifica is going to include all aspects of healthcare, the Zignifica Prototype is limited to a few hundred studies in pain medicine and pain management.We have chosen to do this to keep an overview and still be able to test the system and method.

Please note that Zignifica is developed to be useful for both health care professionals and persons without a medical education.


Here is Your 3 Step Plan

  1. Decide if you want to test this Zignifica Prototype and be part in changing access to clinical reseach
  2. If you want to test: Follow the link below. Download the Prototype App and sign up
  3. Look forward to testing this new concept of taking your access to clinically relevant information on pain medicine and pain management to the next level, and to be part of this by providing us with feedback


Download & Sign Up

YES! I Want to Test Zignifica Prototype

3 comments on “What if We Could Make a Spam Filter for Clinical Research”

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