Enabling privacy-preserving predictive analytics on pharmaceutical data
This is a part of a series highlighting the work of developers on the Oasis Network through a new program run called the DevAccelerator Program. Go here to learn more about the program and apply.
Tell us a little bit about yourself and the Castalise team
I’m Mahmoud Dgheim, CEO and Co-founder of Castalise Tech alongside Firas Kaakour. I assumed the role of product owner for the past 4 years in the blockchain space.
Firas Kaakour is the COO and Co-founder. He has held multiple roles in marketing, procurement and supply chain management in the pharmaceutical industry for the last 9 years.
Tell our audience about Castalise
Castalise is a consent management Software as a Service for healthcare businesses and pharmaceutical companies enabling access control, policy management and data processing over data silos. Castalise allows pharmaceutical and biotech companies to run machine learning pipelines within a secure and privacy preserving environment.
When and why did you first get excited about blockchain technology?
We joined the blockchain world at the same time around 2016 while researching and following blogs about cryptography and specifically bitcoin in the middle of the ICO craze, where we initially lost a lot of money but learned a lot :)
Our first quest was building a peer to peer blockchain based file sharing network built on top of the Interplanetary File sharing system (IPFS) to authenticate and encrypt data at rest. We wanted to help users manage sharing sensitive data over a decentralized and distributed internet.
What drew your interest to tackling a difficult and unique problem such consent management in the pharmaceutical industry?
Data and digital is a top priority for pharmaceutical firms. As a result, machine learning and artificial intelligence have become a crucial topic at the forefront of their compliance concerns. However, most of the efforts are still channeled towards drug discovery and rightfully so.
Pharma companies are still reluctant when it comes to adopting AI based predictive tools in fear of jeopardizing data security and privacy.
While AI based predictive tools proved the ability to unlock a wealth of value out of medical data and research and most importantly secondary objective clinical trials, it also needed a thorough and costly compliance work.
By creating a trusted environment where pharma companies can leverage such predictive tools while ensuring confidentiality, privacy and compliance over sensitive data, data owners can unlock tremendous value out of their own data locked in silos.
Eliminating frictions for the adoption of AI technology in the healthcare sector will not only save money, human resources and ensure compliance but also create a chain reaction of discoveries over critical topics like cell and gene-therapy.
What made you interested in building on the Oasis network?
Creating a trusted execution environment is the game changer provided by the Oasis protocol, where blockchain and AI technologies merge, making privacy-preserving cloud computing a reality. Castalise is leveraging the innovative architecture of the Oasis network where large amounts of computation needed to run machine learning models were previously impossible over the blockchain.
Any big milestones coming up for Castalise that our readers should know about?
Castalise is finalizing the beta version of the software which will be ready to be tested in pilot mode very soon. Innovation will not only stand at ensuring consent management over computation but will also evolve to reach full sovereignty over the user’s data. Castalise team is ambitious to work on expanding its horizon by also developing more features to support real time data flow.
How can others try out Castalise? Learn more about what you’re up to?
A request form will soon be available on the website for interested stakeholder to try out the demo and exchange insights on www.castalise.com
Anything else you’d like to share?
Let’s go big on data privacy creating a better internet. We would like to thank the Oasis team for their ongoing support and guidance.