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An amazing experience to share with you…

Kheizurane Elmekki's picture

First of all, let me introduce myself: I am Kheizurane El Mekki, a 24-year old Tunisian girl. After finishing my high school in Tunisia, I decided to move to Switzerland in order to study Mathematics at Ecole Polytechnique Fédérale de Lausanne (EPFL), 14th university in the world according to the QS world university ranking of 2015/2016. No time to feel homesick when you study Mathematics at EPFL! 3 years later, I got my Bachelor degree and started my Master in Applied Mathematics in Statistics and Probabilities. Of course, you cannot expect being an engineer without an internship! After a tough period looking for the internship that might reach my expectations, I finally found the perfect one: 6 months internship at Merck Institute for Pharmacometrics at the EPFL Innovation Park.

Perfect is the word I used when I first read the internship description and I am still using it. The first day, I arrived with my mathematical background, my general knowledge in R and my tremendous intellectual curiosity. Later on, I understood that the internship falls within the DDMoRe project and aims to first transcode 4 models from commercial software (e.g. NONMEM) to a public platform (MDL-IDE) and then upload those models to the DDMoRe repository. The project seemed very exciting but when you have never heard about PopPK/PD, NONMEM, Monolix or even the SAEM algorithm before, you understand that you will have to learn a lot of tools and concepts before tackling the project.

Thankfully, I had the opportunity to be supervised by the competent senior scientist Nadia Terranova and the head of Pharmacometry Pascal Girard. During my 6 months internship, I got familiar with M&S, broadened my knowledge in pharmacokinetics and caught up with the tools developed within DDMoRe. More specifically, I had the opportunity to use the DDMoRe user-friendly language MDL. The aim is to encode a model in a unified standard language and converted it afterwards to the required languages in order to fulfill the M&S tasks, without any tool specific recoding. I feel very delighted today saying that, thanks to the DDMoRe project and the excellent supervision I benefited from, I learnt new tools such as Simulx and was able to encode population models in Monolix and MDL.

I would also like to add that, when you really care about a project, working under pressure and meeting the tight deadlines is no longer an issue. In fact, knowing that one of the main ideas behind uploading the models to the DDMoRe repository is to share them with other modelers and promote their re-usability pushed me to work even harder to achieve my goal and deliver the models on time. I definitely recommend the use of the DDMoRe repository and sincerely hope that users will continue populating this library with models exhibiting interesting mathematical and biological features.
Finally, I want to thank all the team of the Merck Institute for Pharmacometrics who had allowed me to share this dazzling experience with them and more particularly my supervisors who initiated me to the DDMoRe project.

Kheizurane El Mekki -  Student Mathematics Merck

Further reading: Ribba, B., Holford, N., Magni, P., Trocóniz, I., Gueorguieva, I., Girard, P., Sarr, C., Elishmereni, M., Kloft, C. and Friberg, L. (2014), A Review of Mixed-Effects Models of Tumor Growth and Effects of Anticancer Drug Treatment Used in Population Analysis. CPT: Pharmacometrics & Systems Pharmacology, 3: 1–10. doi: 10.1038/psp.2014.12