Artificial Intelligence (AI) Innovations in Clinical Research

Author: Thalla Sanjeeva Reddy – Clinical SAS Programmer at Genpro Introduction Majority of drugs take about 10 years or more to come to market, cost billions, and have a potential to even demolish an organization in certain cases where the late-stage trials fail after having poured in so much speculation. Also, Patients hardly can wait 15 years […]

Harnessing AI to expedite evidence generation & reporting

Authored by:   MW & Evidence Team at Genpro Research Inc. Given the ever-increasing advocacy and preferences for evidence-based healthcare models, clinicians and the research community have been emphasizing and relying on high-quality evidence. On the other hand, the rapid proliferation of biomedical literature has resulted in the infodemic, posing great challenges for medical and scientific […]

Biostatistics Case Study #01: Interim Analysis using Adaptive Randomization

Adaptive randomization refers to any scheme in which the probability of treatment assignment changes according to assigned treatments of patients already in the trial. The covariate adaptive randomization (CAR) is usually used instead of pure randomization to reduce the covariate imbalance between treatment groups in clinical trials. Allocation probability for the covariate adaptive randomization is […]

Data Monitoring Listings in Clinical Research

Author: Genpro Statistical Programming team. Introduction Clinical trials in the pharmaceutical industry have always its challenges, as providing quality data ethically and fairly for the submission is difficult. Clinical Data Management (CDM) team reviews multiple numbers of reports on a daily, weekly, and monthly basis or at various frequencies to produce quality data. A single […]

The Trial Summary Domain Puzzle


Author: Genpro Statistical Programming Team Trial Summary Domain [TS domain] – A jigsaw puzzle among the SDTM Trial domains where we need to put together the pieces of the study in a structured way to get a complete picture. This domain is often challenging either in determining the number of parameters required or in getting […]

Apple Research & Care Kit

Doctors around the world are using iPhone to transform the way we think about health. Apps created with ResearchKit are already producing medical insights and discoveries at a pace and scale never seen before. That success has inspired Apple to widen the scope from medical research to personal care with the introduction of CareKit — […]

The Classic 3 + 3 Design in Dose-finding Clinical Trials and Its Alternatives

Author: Genpro Statistics Team | Date Posted: 28/July/2021 One of the most important goals of Phase 1 clinical trial is to identify the Recommended Phase 2 Dose (RP2D)/Maximum Tolerant Dose (MTD) with acceptable dose-limiting toxicity of the new drug or combination of drugs for the Phase 2 clinical trial, especially in oncology trials.  Among all […]

Multiple Imputation using SAS and R Programming

Author: Genpro Statistics Team Multiple imputation is highly recommended as a valid method for handling missing data. It eliminates the disadvantages of reduction in statistical power and under estimation of standard errors in single imputation. SAS, an established software having robust tools, and R, an open-source software where users can develop packages, differ in various […]

Handling Missing Values of Continuous Variables in Clinical Data

Author:  Genpro Statistics Team | Date Posted: 06/July/2021 INTRODUCTION Missing values are common in clinical data due to varied reasons. The main disadvantage of missing values is the reduction of statistical power due to reduced sample size and the possibility of biased estimates. Especially when it comes to randomized clinical trials, missing values can lead […]

Components Of Bayesian Approach

Author: Mr. Akhil Vijayan – Bio-statistician at Genpro Research. Bayes theorem is considered as the fundamental theorem in Bayesian statistics formulated by Thomas Bayes. The modern mathematical form and the scientific application was developed by Pierre-Simon Laplace. He explained the principle in words and not by the equation, that is the probability of a cause (given event) is proportional […]