SAS Macro Tool Development A deeper plunge into broad ranges of oncology trials data
Overview
The customer is a global biopharmaceutical company developing innovative medicines in thefields of proprietary commercial products focused on addiction and schizophrenia, along witha pipeline of product candidates in development for schizophrenia, bipolar disorder,neurodegenerative disorders and cancer.
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Challenges
Complex Cloud Environment
Difficulty in analysing input of different database structures from paper CRF, eCRF, inhouse and outsourced data management, and local investigator files
Limited Security Expertise
Existing standard programs were only study/client specific and lacked key variables for broader use
Evolving Threat Landscape
Non-availability of Macros for derived responses and efficacy endpoints on RECIST criteria
Evolving Threat Landscape
Creation of Kaplan Meier graphs for end points was going through a lot of manual programming
Evolving Threat Landscape
Study Integration efforts were experiencing untimely hick-ups because of no standards across studies
Benefits
Leverage the data for clinical and operational decisions to support and deliver value-based healthcare
Improved Security Posture
Enhanced Visibility
Reduced Costs
Compliance Adherence
Benefits
Leverage the data for clinical and operational decisions to support and deliver value-based healthcare
Improved Security Posture
Enhanced Visibility
Reduced Costs
Compliance Adherence
Outcomes
Leverage the data for clinical and operational decisions to support and deliver value-based healthcare
- Maximized the functionalities of end output production to have submission ready outputs like Kaplan Meier graphs for PFS, OS, ORR, DOR endpoints
- Drastic reduction in timeline to derive all the information needed in terms of content and layout
- Creation of a standard norm in terms of handling RECIST data that improved the efficiency and consistency across all projects
- Considerable reduction in programming resources used for manual programming