Implementing Laboratory Toxicity Grading in Sdtm

Oncology is one of the main indications in clinical trials nowadays. One specific method to analyse the oncology data is to review the lab results for safety reports. Mostly the lab results are analysed based on the reference ranges. But in oncology studies, it adds another complexity level to review the lab results using toxicity […]

Scoping Reviews: A Bird’s Eye View

Evidence-based Healthcare is the “buzzword” in the recent era. Systematic reviews have gained immense interest to advocate an evidence-based healthcare practice. They are nothing but systematically collected, appraised, and synthesized evidence that helps determining the best choice amongst available treatment interventions for a clinical condition. However, there are several areas where enough randomized controlled trials […]

Conversational Agents In Clinical Trials

Patient enrollment has remained a major challenge for pharmaceutical companies who are conducting clinical trials. Even patients who have the intend to join a trial due to a critical illness finds it extremely difficult to collect information and processes involved in enrolling into a trial. This blog presents the possibilities of building a conversational agent […]

Sample Size Determination and Power Calculation A Comparison Between SAS and R

Author: Genpro SAS/R Programming Team Choosing the proper sample size for an investigation is one of the crucial jobs required of a statistician. Regardless of whether the statistician is deciding the number of patients to select in a clinical trial, electors to finish a political survey, or mice to remember for a lab experiment, the […]

Clinical Trials with Interactive Html Graphics Using R

Author: Genpro Statistical Programming Team These days, an immense measure of information is gathered during any clinical trial and it is basic for pharmaceutical sponsors to comprehend this information in extraordinary detail to settle on precise choices. Analysts and programmers invest a lot of energy examining data and creating reports for clinical trials, both for […]

Enrichment Strategies for Clinical Trials

Author: Athira Sudhakaran  – Biostatistics Lead at Genpro Research.   Enrichment trials use patient characteristics to select a study population in which detection of a drug effect is more likely than it would be in an unselected population. There are three categories of enrichment strategies for Clinical Trial: Strategies to decrease heterogeneity. Prognostic enrichment strategies in […]

Mobile Applications In Clinical Trials

As mobile phones have become the primary device used by patients for communication and information retrieval, Clinical Trial industry is also finding areas where mobile applications could be implemented in our efforts to digitally disrupt. Some of the areas where mobile applications could be used include the following. Medication Adherence One of the biggest challenges […]

Clinical Data and Wearable Device: Future of Data Capturing

Author: Mr. Vinu C Raju – Clinical Statistical Programmer at Genpro Have you ever wondered how your social networking app is suggesting a friend request for a person you met yesterday in a get together?  If so that is the power of machine learning.  The same is been explored in the field of Clinical trials […]

Introduction to Response Adaptive Randomization (RAR)

Author: Genpro Biostatistics Team Randomization have proven to be an efficient way of reducing bias and thus is widely used in clinical trials. Randomization ensures that subject allocation is balanced across treatment group and is not influenced by external forces and thus provides equal chances for subjects to receive the treatment of interest as they are […]

Introduction to Bayesian Sequential Analysis

Author: Genpro Biostatistics Team The increasing interest in Bayesian group sequential design is due to its potential to reinforce efficiency in clinical trials, shorten drug development time, and enhance the accuracy of statistical inference without compromising the integrity or validity of clinical trials. In a Bayesian trial, the prior information, and the trial results, as […]