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Optimizing and automating drug effect evaluation on disease model

Terrmin

HT23

Beskrivning

Background
Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. Tuberculosis had a death rate above 10% in 2019 even though it is a disease that is both diagnosable and treatable. The burden of tuberculosis is linked to poverty and therefore it often occurs in low- and middle-income countries. The long standard treatment of six months and a wide spread of drug resistant tuberculosis increases the need of new drugs to treat it. To facilitate the development of new drugs the use of model informed development can be used quantify the exposure response relationship. This can be done via linking a pharmacokinetic model linked to a pharmacodynamic model. To evaluate an exposure-response can quickly become complex and many steps needs to be performed which in extent become time consuming.

Aim
To optimize and automate the quantification of exposure response for drug treatment and disease models in order to contribute to a more efficient and streamlined drug development process

Methods
This is a computer-based model development with parts of optimization and automation of which an exposure response should be quantified and the development should be automated to the maximum identifiable extent. Models will be built in NONMEM 7.5 based results from an in vitro drug efficacy assay. Automation and analysis of the workflow will be built in R.

Huvudområde

Farmaceutisk vetenskap

Ämne

Farmakometri

Typ

Beräkningsstudie

Företag

Uppsala University

Ort/Plats

Uppsala

Handledarens namn

Albin Leding and Ulrika Simonsson

Handledarens e-post

albin.leding@farmbio.uu.se

Institution

Institutionen för farmaceutisk biovetenskap

Program

Masterprogram i läkemedelsutveckling

Kurs

Degree Project in Pharmaceutical Modeling within Pharmacometrics 45 c - 3FB029

Omfattning/hp

30hp