Multi User
With noink we use the concept of a circle of users who can record data on behalf of other members of the circle. Potential triallists, who would normally be overlooked, can now have their data recorded on their behalf by a trusted family member or caregiver.

These people, who would not normally be able to leverage technology can now partake in trials or studies. All recorded data comes with a full audit trail of who recorded what data for whom.

We see this as extending potential cohorts vertically. Older triallists can now provide a wealth of Real World Data on such conditions as Arthritis, Cancers, Dementia, Hypertension, Parkinson’s Disease, chronic organ conditions etc. to name but a few.

For morbidities that present in childhood, a stream of Real World Data can also be provided. This not only includes common NCDs but also the majority of rare genetic conditions such as childhood cancers and metabolic conditions.

With noink you can provide trialists with a platform to manage their entire family’s health.

Multi Lingual
noink also addresses the language barrier within clinical trials. Currently single language trials not only restrict potential cohort size but also the diversity of potential trialists. When we say multi-lingual, we do not mean there are many language versions of the platform that require the data to be processed before use; but rather data capture and processing is language independent in real-time.

Trialists can use the platform in any language available and the data can be processed by Life Science organisations in any other available language. For example, Real World Data can be recorded in Spanish and examined in English.

 Patient diversity is a top initiative for Life Science organisations 
Global R&D Insights in Pharmaceuticals

We see this as extending cohorts horizontally across all age groups with the added benefit of increasing potential cohort size and bringing diversity into cohort populations. noink’s current language capabilities extend to 13 languages. This allows over 3,000,000,000 people (over ⅓ of the world’s population) on all continents to use noink in their native language. For bi-lingual patients this extends to 5,000,000,000 people (about ⅔ of the world’s population).

We have achieved this by the rigorous use of structured data in all Real World Data entry interactions. Coupled with best-in-class AI tools available for Natural Language Processing, this can give any trial a truly global reach.

Alongside language barriers, we recognise regional differences in cohorts, particularly with global languages. To overcome this, noink uses hyper-localisation to tailor any aspect of Real World Data capture effort to a particular country, region or locality. We have over 40,000 localities encoded in the system and different data capture requirements can be refined down to a local level. Decentralised trials no longer need accept a one size fits all model.

Any Condition
To be truly useful as a Real World Data capture platform, noink has been designed to work with any and all conditions. This extreme reuse avoids the need for bespoke software development prior to any clinical trial. Data collection can commence immediately after onboarding of users.

The ability to monitor any condition for themselves, or a loved one, provides extra utility to patients, increasing engagement. Giving patients utility beyond any particular trial or condition reduces the burden of evidence collection currently faced by many trialists.

By providing a platform for what is important to patient’s lives and not just clinical trials, we can change the trialist relationship with Life Science organisations. No longer purely transactional, noink brings Life Sciences and individual triallists closer. This reduces the need for the current strategies in patient engagement such as gamification of mobile apps or overt monetary rewards.

With noink, Life Science organisations can provide trialists with a health tool which goes far beyond the immediate needs of a particular study. Conditions for loved ones not engaged in a trial can be monitored.

Contextual, localised, educational content to assist with condition management can be delivered electronically. This off-study utility, coupled with noink’s time saving functionality, creates a dedicated userbase that is predisposed to assisting your organisation with clinical research.

 Providing trialists with educational information on the condition of interest is the primary driver for increasing patient engagement 
Journal of Therapeutic Innovation & Regulatory Science 2022

Infinite options
Even when noink is being used within a trial, it can be adjusted to extend or reduce the different Real World Data points being collected. This in-flight adaptive data capture is possible via our comprehensive archive of configurable items. These items can be added or deleted in real-time. If a new data item is deemed relevant to a study it can be added by either a trialist or Life Science organisation at the push of a button.

 Greater use of Real World Data has been identified as another top initiative for Life Science organisations 
Global R&D Insights in Pharmaceuticals

All of these configurable items retain noink’s multi-lingual, multi-user & multi-condition functionality and data output remains FHIR® compliant, irrespective of any customisation. This deep well of scientifically approved health data is obtained from clinical grade data sources such as the International Classification of Diseases (ICD-11), World Health Organization’s Model Lists of Essential Medicines (WHO EML) , The United States Food and Drug Administration (FDA) list of approved therapeutics, and many other national and international health bodies.

This strict adherence to accepted healthcare data standards ensures noink is not only capable of servicing the Real World data needs of Life Sciences; but that the patient facing elements bring clinical grade data capture to any trial. noink spans the Efficacy Gap; creating a platform that meets the requirements of pharmaceutical organisations for objective, high-quality data and the needs of Individuals to record data to improve their health.