Non Clinical Statistics III

Discussion of Design and Analysis of Animal Experiments
Edgar Brunner
Universitätsmedizin Göttingen, Germany

In this talk, some aspects of particular topics in designing and analysis of animal experiments are discussed. They are important in applications for funding. Below are the keypoints.

• Replication of the Exepriment

o Different laboratories

o Separate experiments vs. stratification and pooling

o Impact of the mother in case of experiments involving young animals

• Randomization and Blinding

o Onsite-randomization vs. central randomization

• Sample Size Planning

o Quite rarely used

o Discussion and definition of a ‘relevant effect’

o Effects based observed in a preliminary study – often based on a few observations

o Relation to effects in human trials may be a problem

o Type-I Error adjusting for multiple / co-primary endpoints

o Power adjusting for multiple / co-primary endpoints

o Switching from non-normal data to rank procedures

• Analysis

o Data base cleaning

o Principle ‘analyze as randomized’

o Pre-testing assumptions on the same data set is not recommended


Festing, M.F. (2007). The design of animal experiments. Chpt.3 in: Handbook on Care and Management of Laboratory and Pet Animals. Ed. Y. B. Rajeshwari. ISBN: 8189422987.

Exner, C., Bode, H.-J.,Blumer, K., Giese, C. (2007). Animal Experiments in Research. Deutsche Forschungsgemeinschaft. ISBN 978-3-932306-87-7

Statistical evaluation of the flow cytometric micronucleus in vitro test – same but different
Lea AI Vaas1, Robert Smith2, Jeffrey Bemis3, Javed Ahmad2, Steven Bryce3, Steven Nicotra4, Christine Marchand5, Roland Froetschl6, Azeddine Elhajouji7, Ulrike Hemmann8, Zhinying Ji4, Damian McHugh9, Julia Kenny10, Natalia Sumption10, Andreas Zeller5, Andreas Sutter11, Daniel Roberts12
1Research & Pre-Clinical Statistics Group, Bayer AG, Berlin, Germany; 2Covance Laboratories Ltd., Harrogate, North Yorkshire, UK; 3Litron Laboratories, Rochester, NY, USA; 4Department of Genetic Toxicology, Bristol-Myers Squibb, Syracuse, NY, USA; 5Pharmaceutical Sciences, pRED Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland; 6Federal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany; 7Preclinical Safety (PCS), Novartis Institutes for BioMedical Research (NIBR), Basel, Switzerland; 8Sanofi-Aventis Deutschland GmbH, Frankfurt, Germany; 9Philip Morris Products S.A., Neuchatel, Switzerland; 10Genetic Toxicology and Photosafety, GlaxoSmithKline, Ware, Hertfordshire, UK; 11Bayer AG, Pharmaceuticals, Investigational Toxicology, Berlin, Germany; 12Genetic and In Vitro Toxicology, Charles River, Skokie, IL, USA

In vitro genotoxicity testing is part of the safety evaluation required for product registration and the initiation of clinical trials. The OECD Test Guideline 487 gives recommendations for the conduct, analysis and interpretation of the in vitro Mammalian Cell Micronucleus (MN) Test. Historically, in vitro MN data have been generated via microscopic examination of cells after exposure to a chemical following scientifically valid, internationally accepted, study designs, that is labour intensive and time consuming. Flow cytometry is an automated technology capable of scoring greater numbers of cells in relatively short time span and analysing genotoxic effects of clastogenic and/or aneugenic origin. However, when acquiring data using flow cytometry, neither the number of cells being evaluated nor the built-in relative survival metrics (cytotoxicity) have undergone critical evaluation for standardization. Herein, we addressed these topics, focusing on the application of the in vitro MN assay scored by flow cytometry (e.g. MicroFlow®) for regulatory purposes. To do so, an international working group comprising genetic toxicologists and statisticians from diverse industry branches, contract research organizations, academia, and regulatory agencies serves as a forum to address the regulatory and technical aspects of submitting GLP-compliant in vitro MN flow cytometry data to support product development and registration.

We will briefly present our motivation and the envisaged initial goals with a focus on the suitability of built-in cytotoxicity metrics for regulatory submissions. Based on a data set collected from multiple cross-industry laboratories the working group additionally evaluates historical control data, recommendations on appropriate study designs, and reviews statistical methods for determining positive micronucleus test results.

Mouse clinical trials of N=1: Do we reduce too much?
Hannes-Friedrich Ulbrich
Bayer AG, Deutschland

In 2015 the IMI2 7th Call for Proposals requested for ‚A comprehensive ‘paediatric preclinical POC platform’‘ for the development of treatments against cancer in children; ‚mouse N=1 trials‘ had to be part of it. The project (ITCC-P4) was launched in 2017.

Four years later the terminology has evolved to ‚mouse clinical trials‘ (MCT). They are experiments where one PDX model (a derivative of a particular patient’s tumor) gets implanted into a number of mice to grow and to be treated by different substances: one mouse per substance [and occasionally more for the vehicle — ITCC-P4 plans with three]. The number of PDX of the same human tumor type is supposed to be „large“; the series of randomized per-patient-tumor experiments are forming a trial. As compared to more ‚classical‘ PDX trials where replicates of mice (usually 6) per substance were used to explore substance differences for one PDX only, mouse clinical trials focus on population response for the considered tumor type. This design is still quite new, „becoming wildly used in pre-clinical oncology drug development, but a statistical framework is yet to be developed“ (Guo et al, 2019). Not too much is published yet on whether the reduction to N=1 is reasonable as compared to an imaginable series of ‚classical‘ PDX trials.

Based on data of the already finished OncoTrack IMI project (on colon cancer) we explore the magnitude of differences between the two approaches using resampling techniques.

In this talk we will report the results of this comparison. Statistical models will be described; criteria for comparing these approaches will be discussed.


• IMI2 ITCC-P4 Project Description

• Guo S et al (2019): Mouse clinical trials in oncology drug development. BMC Cancer 19:718, DOI 10.1186/s12885-019-5907-7

• Williams JA (2017) Patient-Derived Xenografts as Cancer Models for Preclinical Drug Screening, DOI 10.1007/978-3-319-55825-7_10

Statistical Review of Animal trials in Ethics Committees – A Guideline
Sophie K. Piper1,2, Dario Zocholl1,2, Robert Röhle1,2, Andrea Stroux1,2, Ulf Tölch2, Frank Konietschke1,2
1Institute of Biometry and Clinical Epidemiology, Charité – Universitätsmedizin Berlin, Charitéplatz 1, D-10117 Berlin, Germany; 2Berlin Institute of Health (BIH), Anna-Louisa-Karsch Str. 2, 10178 Berlin, Germany

Any experiment or trial involving living organism requires ethical review and agreements. Beyond reviewing medical need and goals of the trial, statistical planning of the design and sample size computations are key review criteria. Errors made in the statistical planning phase can have severe consequences on both the results and conclusions drawn from a trial. Moreover, wrong conclusions therof might proliferate and impact future trials—a rather unethical outcome of any research. Therefore, any trial must be efficient in both a medical and statistical way in answering the questions of interests to be considered as “ethically approvable”.

For clinical trials, ethical review boards are well established. This is, however, not the case for pre-clinical and especially animal trials. While ethical review boards are established within each local authority of animal welfare, most of them do not have an appointed statistician. Moreover, unified standards or guidelines on statistical planning and reporting thereof are currently missing for pre-clinical trials.

It is the aim of our presentation to introduce and discuss

i) the need for proper statistical reviews of animal trials,

ii) a guideline of mandatory ethical review criteria, involving blinding and randomization, and

iii) the need to distinguish the planning of exploratory studies from confirmatory studies in pre-clinical research.

Our statistical criteria for ethical reviews of animal trials have been implemented in a form sheet that has been used from the Landesamt für Gesundheit und Soziales (local authority of animal welfare) in Berlin since 2019. It is online available at