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The Role of a Statistician In a Pre-Clinical Study

Statistical Consultancy Team

Pre-clinical trials, involving experiments in-vitro (literally ‘in glass’, i.e. in the laboratory, typically involving cells) and in-vivo (‘in animals’) are an essential part of drug development as it is a regulatory requirement  to investigate the safety of new drugs in-vitro and/or in-vivo before they are tested in humans. These trials can also be used to investigate the potential efficacy of new compounds.

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Topics: Pharmacokinetics and Pharmacodynamic, Randomization, Specialist Biometrics CRO, Pre-Clinical Study, Biostatistics Consulting

Comparing treatment response curves: a practical example in rheumatoid arthritis

Statistical Consultancy Team

Nowadays, more and more studies are being designed to collect information on treatment response at several time points during the treatment period of the study. Although the primary endpoint is often the comparison at the end of the study of the absolute response or of the change to baseline between study treatments, analyses involving intermediate time points in the assessment of treatment effects, e.g., repeated measures modeling, are now widely used.

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Topics: Programming R, SAS Programming, Therapeutic Areas, Biostatistics Consulting, Phase 3 Studies, Rheumatoid Arthritis (RA), PROC NLMIXED, PROC IML

Utilizing a Bayesian Informative Prior to Reduce Sample Size in Clinical Trials

Statistical Consultancy Team

Bayesian_Informative_Prior_to_Reduce_Sample_Size_in_Clinical_Trials

Bayesian statistics in clinical trials are becoming more widely used in the pharmaceutical industry. By gathering data from historical studies, it is possible to reduce the sample size of the current trial by using an informative prior in the Bayesian analysis. This blog explores five cases in different indications that have historical data on placebo subjects from the literature, and calculates the effective sample size using an informative prior. In some cases, the effective sample size is substantial, but in others there are no sample size savings despite abundant data in the literature.

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Topics: Bayesian Statistics, Bayesian Methods, Statistical Programming, Biostatistics Consulting

7 Frequently asked Questions on Clinical Study Design

Statistical Consultancy Team

Quanticate has released several white papers around Clinical Study Design in the area of Bayesian Statistics and a focus on Phase 1 studies. Our statistical consultancy team was pleased to receive feedback and questions from our clients and piers on these papers which we would like to share with you all below.

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Topics: Bayesian Statistics, Bayesian Study Design, Phase I Study Design, Phase I Studies, Interim Analysis, Bayesian Methods, Clinical Study Design, Biostatistics Consulting

How a Centralized Approach to Data Impacts Clinical Study Design

Statistical Consultancy Team

 

In today’s environment, one of the keys to accelerating drug development decisions comes from ready access to historical data. The introduction of the Centralized Service Provision (CSP) enables data across study phases and programmes to be accessed as easily as within the same study, due to the commonality of structure.

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Topics: Standardization, Clinical Study Design, Centralization, Biostatistics Consulting, Visualization

PK data analysis and reporting: SAS or Phoenix WinNonlin?

Statistical Consultancy Team

SAS [1] is regarded as the industry standard for clinical data analysis and reporting; however, Phoenix WinNonlin[2], which is a powerful tool tailored to the specific demands of PK data, is widely accepted as the industry standard for PK data analyses. This widespread separation of responsibilities, and the resultant transfer of data between software applications (and in many cases departments), has the potential to not only cause significant reporting delays, but can also lead to incohesive clinical study reports (CSRs) containing tables, listings and figures (TLFs) derived from various different sources.

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Topics: Pharmacokinetics and Pharmacodynamic, Clinical Study Report, SAS Programming, Biostatistics Consulting, PK Analysis

Bayesian Methods and a review of the European Statistical Forum

Statistical Consultancy Team

A member of Quanticate's Statistical Consultancy Team writes about their attentedence and presentation at the European Statistical Forum, Milan Nov, 2011.

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Topics: Regulatory Requirements, Bayesian Statistics, Bayesian Study Design, European Statistical Forum, Bayesian Methods, Survival Analysis, Interim Analysis, Biostatistics Consulting, Clinical Trial Phases

An Introduction to Industry Training Course Review - Statisticians in the Pharmaceutical Industry

Statistical Consultancy Team

A Member of Quanticate’s Statistical Consultancy Team writes about their experiences whilst attending the course entitled “PSI Introduction to Industry Training Course”.

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Topics: Statistical Programming, Pre-Clinical Study, Biostatistics Consulting, Statisticians in the Pharmaceutical Industry (PSI)

The Use of Propensity Scoring in Pooling Data across Clinical Trials

Statistical Consultancy Team

A member of Quanticate's statistical consultancy team presented a poster on “Using a Propensity-Pairing Algorithm to Reduce Bias due to Imbalances in Covariates: A Case Study Pooling Data from 5 Kidney Transplant Trials” at a conference for statisticians in the pharmaceutical industry (PSI).  This work uses a range of statistical methods including stepwise logistic regression, conditional logistic regression, principal component scores and mixed modeling.

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Topics: Randomization, Specialist Biometrics CRO, Biostatistics Consulting, Propensity Scoring

Biomarkers in Drug Development

Statistical Consultancy Team

The identification of novel and effective biomarkers in drug development is considered a key feature in the optimization of the drug development process. But what exactly is a biomarker? As defined by Grutolla et al. [1], a biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Examples include concentrations of particular proteins in the blood or bone marrow, liver function tests or PET imaging as indicators of disease state or therapeutic benefit.

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Topics: Bayesian Study Design, Phase I Studies, Biomarkers, Specialist Biometrics CRO, Biostatistics Consulting, Phase I Study Design, Drug Development

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