Clinical trials
Medicines development makes use of the scientific method, whereby hypotheses are proposed then tested. An abundance of quality data enables reliable hypotheses, while even more data are needed to prove the hypotheses. Collaboration between disparate stakeholders in the medicine's development process requires the secure and transparent sharing of data. Patient privacy and intellectual property must be upheld while at the same time data must be made available for clinical research organizations, vendors, peer reviewers, and regulators
Key Challenges
Legacy Tools
Majority of healthcare organizations possesses legacy IT infrastructure that are insufficient to facilitate the high level of collaboration needed amongst the disparate stakeholders in the medicine development process
Siloed Data
Prevents physicians, pharmaceutical companies and manufacturers from accessing and interpreting important data sets, instead encourage each group to make decisions based upon a part the information rather than the whole
Data relevant to and necessary for medicines development remains locked away due to privacy issues, with the consequence that medicines development becomes unnecessarily slow and expensive
Data relevant to and necessary for medicines development remains locked away due to privacy issues, with the consequence that medicines development becomes unnecessarily slow and expensive
All pharmaceutical companies hold personal data about individuals. It’s easily recognized that companies which deal with the public, engage in medical research or undertake clinical trials, will process greater amounts of personal data. Protecting health data privacy is important, not only because of patient confidentiality, but possibly used for clinical test & research projects that may expose patient data to 3rd parties
Clinical testing costs as much as $2.6 Billion per drug, and the cost of drug development has increased by over 400% in less than two decades. On average, it takes at least 10 years for new medicine to complete the journey from initial discovery to the marketplace, with clinical trials alone taking 6 to 7 years on average
Clinical trials : Bottlenecks (3-6 years on average)
New medicine
Clinical trial application
More research needed
Department of health(Regulatory agency)
Medical Experts
Scientific Experts
Trial begin in humans pending ethics approval
How to boost collaboration between hospitals and pharmaceutical companies to accelerate this phase
Solution overview
Terracuda.Ai platform solution to support the acceleration of clinical trails through an open collaborative ecosystem for the life science domain
Research Institutes
Clinicians / Researchers
Solution Module
Terracuda.Ai Platform
Edge / Cloud security hardware deployment
Libraries of distributed datasets & Models
Blockchain + FL management & orchestration SW
Community Module
Open model sharing for the pharmaceutical / Biotech community
For data scientists / developers to compete, learn, build / models
A marketplace to share, exchange and license ML models
The Terracuda.Ai platform solution consists of 2 modules. The solution module is composed of the hardware and software stack providing the management and orchestration software that integrates both blockchain and federated learning. Included are also open accessible libraries of distributed datasets and models in solving scientific issues in the healthcare domain
The community module is a place where anyone in the healthcare community (Researchers, data scientists, physicians, students) can come together to collaborate, and learn models, in advancing the healthcare industry through accelerated clinical trials while preserving privacy and data security.
This platform will empower academic and pharmaceutical industry researchers together in a federated research environment , in order to gain better insights from the breakthrough in healthcare network that will ultimately result in better treatments for patients, that is accelerated and produced at a lower cost.
Biotechnology and pharmaceutical companies can apply the Terracuda.Ai platform to understand why drug efficacy varies from patient to patient, enhance the drug development process, and quickly identify the best drug for the right patient at the right time
By overcoming privacy & confidentiality concerns through blockchain enabled federated learning, organizations can build partnerships and consortia's and retain their competitive edge