Diversity Matters — How to Embrace Variation in the Design of In Vivo Studies

Dr Natasha Karp, is is Director of Hit Discovery and Biostatistics at AstraZeneca, where she leads an international team of data scientists supporting preclinical research. She is an active researcher publishing on challenges in preclinical science, with a recent emphasis on meta-research and practical ways to enable and nudge scientists toward better research practice.

With a multidisciplinary background spanning a Biochemistry degree, a PhD in Chemistry, commercial R&D roles, and postdoctoral appointments, Natasha transitioned into a researcher focused on elevating research quality through robust experimental design and data analysis.

Most recently, her work has prioritized equity in research, culminating in the Sex Inclusive Research Framework (SIRF)—a toolkit that helps evaluate proposals and guide researchers to assess when and how inclusion is feasible and appropriate. She also conducts qualitative research to understand scientists’ intentions around inclusion and the cultural and knowledge barriers that influence practice. Her work bridges scientific rigor and culture change, translating evidence into tools and habits that make preclinical research more reliable, inclusive, and decision-ready.

Inherent in research is the simplification of a complex world into a testing space to explore cause and effect. Across preclinical research, questions are increasingly being raised about whether this testing space has become too narrow. Within genomic studies, such as genome-wide association studies (GWAS), significant concerns have been raised about the lack of diversity in underlying datasets. Similarly, across in vivo, in vitro and clinical research, sex bias has been highlighted as culturally embedded in our working practices.

In this seminar, we will explore these issues and focus on practical steps that can be taken in in vivo research to embrace variation in experimental design, with the aim of improving generalisability and reproducibility.

Selected references: 

1. Karp NA, et al. The Sex Inclusive Research Framework to address sex bias in preclinical research proposals. Nature Communications. 2025;16:3763. doi:10.1038/s41467-025-58560-5.
2. Karp NA. Navigating the paradigm shift of sex inclusive preclinical research and lessons learnt. Communications Biology. 2025;8:681. doi:10.1038/s42003-025-08118-4.
3. Karp NA, et al. A multi-batch design to deliver robust estimates of efficacy and reduce animal use – a syngeneic tumour case study. Scientific Reports. 2020;10:6178. doi:10.1038/s41598-020-62509-7.

• Recognise the limitations of excessive standardisation
• Understand why biological variation matters
• Consider sex appropriately in study design
• Identify opportunities for planned variation
• Design more generalisable and reproducible studies

• More standardisation is not always better
• Biological variation can strengthen study design
• Sex inclusion improves generalisability
• Planned variation can improve reproducibility
• Robust design can support Reduction