Use Cases

Decentralised Clinical Trials (DCT)

A shared infrastructure for optimising clinical trials. Public health researchers are choosing to switch from standard face-to-face data collection methods to remote data collection in support of continued research.

Human – The Preventative Health Trial

Privacy-enhancing technologies add value along the whole clinical trials process: From onboarding and authentication over consent to verified clinical endpoint data.

The human health wallet empowers the individual with their unique persona for managing health, work and life digital experiences.

By connecting these life digital experiences on one common network, free from ‘trusted’ 3rd parties, where individual privacy and ownership rights are respected, clinicians can gain human-centric insights about people, places, and things, so as to create more personalized solutions.

For Business – a shared infrastructure for a faster, safer and smarter personalized services without compromising confidentiality.

For Humans – a unique machine readable persona to safely access personalized products, services, and marketplaces.


  • Automate workflows and create operational efficiencies
  • Power Web3 solutions with a single source of truth
  • Get compliant solutions to market faster
  • Deliver personalized experiences


Collecting trusted, verifiable data directly from patients.

  1. Reusing past clinical trials data for effective trial protocol design
  2. Navigating insights from past trials
  3. Creating synthetic control arms





  1. Patient-centric health wallets – set-up and hosted by specialists (custodial or non-custodial) that support computer readable health personas
  2. Control and consent is with the patient – No sensitive private data is held on a public ledger (such as Ethereum based solutions)
  3. Single sign-on interoperability – All activities, whether voice or phone, are timestamped and recorded as anonymous transactions, auditable by permissioned authorities.
  4. Integrated marketplace supported by tokenisation – enables real-time settlement and minimises disputes and abuse
  5. Shared infastructure with configurable trials – consolidating multiple trials in different attributes in multiple locations

Unique benefits

  1. KATLAS role-to-role protocols (@R2R) – allow participants to play multiple roles with plug-in services for assisted pathways.
  2. Wallet protocols operate with open APIs – to smoothly enable cross-chain interoperability.
  3. Control and consent is with the patient – No sensitive private data is held on a public ledger (such as Ethereum based solutions)
  4. Project Managers can create bespoke T&Cs – to manage the economics and governance of their trials. Ensuring real-time rewards for particpation.
  5. Plug-in modules – for monitoring regulatory and sustainability KPIs and providing predictive analytics.

KATLAS Web 3.0 as-a-service is a shared digital infrastructure. Unlike Apple, Meta, Google, and Amazon, KATLAS offer a common (public) utility operating as a ‘bridge’ between private systems, a customer-centric solution for SMEs to move away from managed services to self-managed services using assisted pathways.

Scalable: The infrastructure is not limited to one ecosystem. KATLAS supplies a configurable architecture, consisting of unlimited private protocols operating across a public infrastructure, whether that be ethereum, polygon, solana, cardano or other US and EU compliant blockchains.

Opportunity: By adopting a shared infrastructure, SMEs can secure confidential information in all transactions in their trial activities; are not constrained by walled gardens but instead benefit from the joint security and safety for all participants.

Shared membership: 

Create or join shared ecosystems of democratic business models for shared ownership, participation and technology support. With the KATLAS platform you can create bespoke tokenised projects across complex environments with complete inetroperability.

Related Use Cases

KATLAS provide the essential plumbing for Artificial Intelligence and Machine Learning systems to deliver reliable data for automated decision making.

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