BIzNet

BizNet-CTM, developed by Sarjen Systems Pvt. Ltd., is a comprehensive suite of solutions designed for Clinical Research Organizations (CROs), Pharmaceutical, Biotech, and Medical device industries. According to the vendor, this software enables clinical research professionals to capture accurate and complete data into electronic Case Report Forms (eCRF) in accordance with the trial protocol.

Key Features

Accurate Data Capture: According to the vendor, BizNet allows users to capture accurate, legible, error-free, and complete data into eCRF, aligning with the trial protocol.

Electronic Data Capture: BizNet facilitates the electronic capture of data directly into eCRF, eliminating the need for paper-based Case Report Forms (CRF).

Flexible eCRF Design: BizNet provides the flexibility to design eCRF according to the Electronic Data Capture (EDC) requirements, ensuring the capture of key data from the trial protocol and source documents.

Multi-Site Collaboration: BizNet allows multiple users across different sites to easily access and share data, facilitating collaboration in multi-site clinical trials.

Improved Data Quality: The vendor claims that BizNet helps reduce errors and improve data quality, potentially leading to faster and more cost-effective clinical research.

Barcode Generation: BizNet generates barcodes for Investigational Product (IP) dosing and sample collection, which can enhance tracking accuracy and prevent sample mix-ups.

Efficient Subject Management: BizNet offers project-wise subject management, enabling efficient tracking and management of subjects participating in the clinical trial.

Randomization and Treatment Assignment: BizNet supports randomization or treatment assignment of subjects in clinical trials, ensuring unbiased allocation of treatments.

Real-time Data Capture: BizNet enables real-time data capture, ensuring timely availability of data for analysis and decision-making.

Custom-defined Alerts: According to the vendor, BizNet provides custom-defined alerts during data entry, aiming to facilitate clean data capture and help users avoid surprises or discrepancies at the end of the study.