Products

Over the existence of the past several years, Kreara has built innovative products that enable cutting-edge analysis, relationship building, modeling and accurate predicting, building and deploying of systems-biology models etc. Our products are very user-friendly and adept at dealing with complexity. They help users conduct virtual experiments and use the results in an intuitive manner. Our products include an electronic CRF platform, an electronic randomization frame work, an artificial neural network for cancer prognosis prediction, and a SAS programming quality control framework.

EZECRF

EZECRF is an e-CRF application that allows capture of clinical trial information in a rapid manner using laptops or palmtops and directly populates a central database without the use of intermediate paper CRF. The EZECRF application comprises of computer forms corresponding to each page of the CRF using which, the investigator can enter data directly into the database at the back end. This approach helps reduce the time spent on transfer of paper CRFs to the data management center and also the entry of the data into the database. This further helps do away with errors which occur during the time of data entry.

Kreara has a team of well trained software professionals who are capable of designing and implementing customized CFR Part 11 compliant EZECRF for any clinical study as per client requirement in an efficient and timely manner. The ability to understand and guide technology, together with the awareness of the clients’ goals and objectives, makes Kreara a valuable resource throughout the EZECRF implementation process. A manual describing the installation, maintenance and use of the EZECRF is also provided to the clients as a guidance document in addition to training on use of the application.

EZEQC

Sopanam is an in-house developed web based tracking application with in-built audit trails which helps follow the progress of SAS programming and quality checking tasks. This application is used to assign team members to a particular project and also to assign each SAS program, to be developed as part of the deliverables, to statisticians, SAS programmers and quality checking personnel. The application has a provision for team members to fill in the status of the SAS programming tasks assigned to them. This application is used by the project managers/leaders and the client representative to check the status of the SAS programming tasks at any time by generating reports automatically.

The user friendly interface can be set up separately for different clients, thereby ensuring information security for each client. The tracking system enables easy assignment options, status log-in and also helps concerned personnel follow up progress of projects easily.

EZERAND

Randomization is a process of allocating subjects to different interventions (treatments or conditions). The randomization procedure in a randomized controlled trial (RCT) gives each subject a predefined chance of being assigned to any of the intervention groups eliminating any bias involved and balancing the confounding factors between treatment groups.

Kreara has a team of well qualified statisticians who have sound knowledge in randomization techniques like simple randomization, permuted block randomization and adaptive randomization. The randomization algorithm for any specific project is developed based on the study requirements by taking into consideration various prognostic factors.

A study specific web based randomization application is developed using ASP.Net or VB.Net based on the algorithm, taking into consideration all the statistical requirements. The database for the application is designed using mySQL. This web based application called EZRAND is developed as part of the data management services provided by Kreara. As per client requirements, Kreara develops EZRAND which can either be implemented at the client site or can be deployed at Kreara which acts as a randomization centre with 24*7 on call support.

ANCANZ

This project proposes to implement a generic framework that will implement an ANN for cancer prediction and prognosis. The model will then be programmed using VHDL on an FPGA chip which will then be embedded into a palm device which will be used by the clinician for personalised decision making. Claimed advantages of this product include:

• Ease of optimisation, resulting in cost-effective and flexible non-linear modelling of large data sets.
• Accuracy for predictive inference with potential to support clinical decision making.
• These models can make knowledge dissemination easier by providing explanation, for instance, using rule extraction or sensitivity analysis