Dawn Lee

Associate Professor of Health Economics and Health Policy

D.Lee7@exeter.ac.uk

Overview

Dawn is Associate Professor of Health Economics and Health Policy, working with the Peninsula Technology Assessment Group (PenTAG), one of 11 research units in the UK providing expert advice on the clinical and cost-effectiveness of new drugs to the National Institute of Health and Care Excellence (NICE).

Dawn joined PenTAG / Exeter University in Sept 2022 following over 15 years in economic consultancy where she worked most recent as the Chief Scientific Officer for a medium sized health economics consultancy (Lumanity; formerly BresMed). She is a health economic modeler who has conducted over 50 UK Health Technology Assessment submissions and worked in over 30 countries globally, a member of NICE’s interventional procedures advisory committee (IPAC) and the R for HTA group. Dawn’s key project achievements include representing manufacturers at ~30 HTA Committee meetings, working on the first ever immune-oncology submission to NICE (TA268), first ever PD-1 submission to NICE (TA384) and a considerable number following this and the first ITC accepted by G-BA.

Dawn’s main research interests are oncology modelling; particularly immune-oncology and therefore flexible survival modelling and the incorporation of external data within extrapolations, structured expert elicitation and improving diagnostic pathways.

Qualifications

MSc Health Economics and Decision Modelling
MMath Mathematics

Research

Research interests

Dawn’s main research interests are:

Oncology modelling; particularly immune oncology and the various issues that stem from this including flexible survival modelling, incorporation of external data within extrapolations, methods for assessment of tumor agnostic indications, issues around combination therapies
Structured expert elicitation (where she is currently working on development of open-source materials with York University with the aim of facilitating greater uptake)
Increasing uptake of more efficient software for health economic modelling. Ideated and oversaw the development of intRfac : an end-to-end modelling solution using R / R-SHINY to increase the efficiency of model development and ease of quality control.https://bresmed-intrface-hypothetical-car-t-model.shinyapps.io/IntRface_Model-PharmacoEconomics/
Next gen HTx: patient-centered, societally oriented, real-time decision making on access to and reimbursement for health technologies
Improving diagnostic pathways

Publications

Journal articles

Burke C, Crossan C, Tyas E, Hemstock M, Lee D, Bowditch S (2024). A Cost-Utility Analysis of Add-On Cannabidiol Versus Usual Care Alone for the Treatment of Seizures Associated with Tuberous Sclerosis Complex in England and Wales. PharmacoEconomics - open Abstract.

Hart RJ, Hassan F, Alulis S, Patterson KW, Barthelmes JN, Boer JH, Lee D (2024). Modelling Treatment Sequences in Immunology: Optimizing Patient Outcomes. Adv Ther Abstract. Author URL.

Lee D, Burns D, Wilson E (2024). NICE's Pathways Pilot: Pursuing Good Decision Making in Difficult Circumstances. Pharmacoecon Open Author URL.

Lee D, McNamara S (2023). Dynamic Mortality Modeling: Incorporating Predictions of Future General Population Mortality into Cost-Effectiveness Analysis. Value in Health, 26(8), 1145-1150.

Lee D, McCarthy G, Saeed O, Allen R, Malottki K, Chandler F (2023). The Challenge for Orphan Drugs Remains: Three Case Studies Demonstrating the Impact of Changes to NICE Methods and Processes and Alternative Mechanisms to Value Orphan Products. PharmacoEconomics - Open, 7(2), 175-187. Abstract.

Aguiar-Ibáñez R, Hardern C, van Hees F, Lee D, Patel A, Chhabra N, Baluni G, Amonkar M, Lai Y, Xu R, et al (2022). Cost-effectiveness of pembrolizumab for the first-line treatment of patients with unresectable or metastatic MSI-H/dMMR colorectal cancer in the United States. Journal of medical economics, 25(1), 469-480. Abstract.

Grant TS, Burns D, Kiff C, Lee D (2020). A Case Study Examining the Usefulness of Cure Modelling for the Prediction of Survival Based on Data Maturity. PharmacoEconomics, 38(4), 385-395. Abstract.

Bullement A, Meng Y, Cooper M, Lee D, Harding TL, O'Regan C, Aguiar-Ibanez R (2018). A review and validation of overall survival extrapolation in health technology assessments of cancer immunotherapy by the National Institute for Health and Care Excellence: how did the initial best estimate compare to trial data subsequently made available?. Journal of medical economics, 22(3), 205-214. Abstract.

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