Clinical trial management software tools | Drug discovery data analysis
Managing clinical trials, of whatever size and complexity, requires efficient trial management. Trials fail because tried and tested systems handed down through apprenticeships have not been documented, evaluated or published to guide new trialists starting out in this important field. For the past three decades, trialists have invented and reinvented the trial management wheel.
Allows users to handle basket trials based on Bayesian principles. BasketTrials offers a statistical model for planning, monitoring and analyzing early phase basket discovery trials implicating one drug hypothesized to target tumors with specific genomic or molecular characteristics. It exists both as a web application and a standalone software.
Supports tasks of implementing and analyzing clinical trials. Various approaches to randomization are offered. randPack is a suite of classes and functions for randomizing patients in clinical trials. It offers a class that defines the parameters for a clinical trial, a container for clinical trial randomization infrastructure and patient data, a function to calls to create new instances of the ClinicalTrials class and many others.
Serves for storage, access and change tracking for clinical study data, analyses and related files. PKS provides a solution for standardized and regulatory-compliant routine analyses and automatic generation of Phoenix knowledgebase (PK) output. Researchers can perform two types of work: (1) capture, management, and storage of study data and associated analyses across drug development programs; and (2) analysis, summarization and report of the knowledge relating to both existing drugs and new compounds.
Gathers clinical and genomic data from public knowledge bases ranging from basic to clinical content coverage. SMART Cancer Navigator links patient-specific data from electronic health record (EHR) and genomics laboratories to multiple knowledge bases for interpretation and validation. This application includes three databases (CIViC, ClinVar, and OncoKB) that explicitly linked genomic variants to clinical factors such as prognosis and treatment selection.
Discover our proposed protocols. They are easy to use or edit to meet your needs.