Email Address: email@example.com
I am an NIHR Advanced Research Fellow working on the development and implementation of (response-) adaptive designs in clinical trials. Currently, I work on the following topics: Adaptive Designs, Dose-Finding Trials, Platform Trials, Bayesian Response-Adaptive Designs, and Quantitative Benefit-Risk analysis.
I provide statistical support in a number of trials, including AGILE-ACCORD (https://www.agiletrial.net/), an early phase trial studying novel therapies for COVID-19 treatments.
If you believe that the trial(s) you are planning can benefit from an adaptive design, feel free to reach me for the discussion - I will be happy to help.
I also consult a number of pharmaceutical companies on the development of novel adaptive designs and support their implementations in ongoing privately funded clinical trials.
- PI: NIHR Advanced Fellowship: Bringing Innovative Methods for Early Phase Precision Medicine Trials Into Practice, NIHR
- Co-I: COVID 19 - AGILE: Seamless Phase I/IIa Platform for the Rapid Evaluation of Candidates for COVID-19 treatment, Wellcome Trust
- Co-I: FORWARDS: Facilitating Opiate Recovery: Withdrawal and Abstinence through Detoxification Support, MRC
- Co-I: TREADON; Clinical effectiveness of exercises and foot orthoses in the treatment of plantarheel pain: a randomised multi-arm multi-stage (MAMS) adaptive trial, NIHR
Link to Google Scholar: https://scholar.google.co.uk/citations?user=nj0wzIUAAAAJ&hl=en
- Mozgunov, P. and Jaki, T., 2020. An information theoretic approach for selecting arms in clinical trials. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 82(5), pp.1223-1247. https://doi.org/10.1111/rssb.12391
- Mozgunov, P., Paoletti, X. and Jaki, T., 2021. A benchmark for dose-finding studies with unknown ordering. Biostatistics. Epub. https://doi.org/10.1093/biostatistics/kxaa054
- Mozgunov, P. and Jaki, T., 2019. An information theoretic phase I–II design for molecularly targeted agents that does not require an assumption of monotonicity. Journal of the Royal Statistical Society. Series C, Applied Statistics, 68(2), p.347. https://doi.org/10.1111/rssc.12293
- Mozgunov, P., Jaki, T. and Paoletti, X., 2020. A benchmark for dose finding studies with continuous outcomes. Biostatistics, 21(2), pp.189-201. https://doi.org/10.1093/biostatistics/kxy045
- Saint-Hilary, G., Robert, V., Gasparini, M., Jaki, T. and Mozgunov, P., 2019. A novel measure of drug benefit–risk assessment based on scale loss score. Statistical Methods in Medical Research, 28(9), pp.2738-2753. https://doi.org/10.1177/0962280218786526