Risk management
New technical, clinical or post-market information can change the known risks and controls.
MICT is a medical-technology institute focused on bringing clinical research, post-market evidence, data engineering and expert evidence analysis into one operational environment for medical devices.
Our CRO is the clinical-evidence service arm of the institute.
MICT CRO supports medical-device evidence generation across the product lifecycle: preclinical and performance evidence planning, clinical investigation, data management and biostatistics, clinical evaluation, regulatory evidence support, real-world evidence, PMS, PMCF, vigilance, usability and scientific writing.
The demonstration platform uses role-based access, IRC-linked devices and PostgreSQL-backed records.
A Contract Research Organization (CRO) performs contracted scientific, clinical, data, statistical and documentation work for a manufacturer or importer.
A company has developed a blood-pressure monitor but does not have a complete in-house team for study design, statistics, clinical reporting and post-market follow-up.
The order below is intentionally chronological for learning.
New evidence can change risk, documentation, regulatory strategy and clinical conclusions at any point.
New technical, clinical or post-market information can change the known risks and controls.
Regulatory needs should be considered from early development.
As evidence grows, data must remain structured, controlled and traceable.
Nearly every lifecycle stage creates documents that must clearly explain methods, evidence and decisions.
Every important claim or conclusion should be traceable to its source.
Projects involving patient or user information require controlled access and appropriate data protection.
We first clarify the IRC/device, intended purpose, responsible organization, target population and the decision that the evidence must support. Only then are data sources, endpoints, methods, responsibilities and documents selected.
The demo contains hundreds of PostgreSQL participant records, longitudinal metrics, subgroup results, data-quality indicators and a live feedback & safety registry. Authorized users inspect those records first; expert evidence analysis is then executed as a separate interpretation layer.
Open PMCF demonstration