The TREC 2019 Precision Medicine Track repeats the general structure and evaluation of the 2018 track. Our team participated in both tasks of the track, relative to scientific abstracts and clinical trials. 40 topics where patient data are given (demographic data, disease, gene and genetic variant) were available for this competition. The aim was to retrieve scientific abstracts and clinical trials of interest regarding a topic, modelling the description of a clinical case. In the first task, we aim at retrieving scientific abstracts introducing some relevant treatments for a given case. Our system is first based on the collection of a large set of abstracts related to a particular case using various strategies such as search with keywords within abstracts, search with normalized entities within annotated abstracts and the linear combination of various queries. We then apply different strategies to re-rank the resulting scientific abstracts set. In particular, we tested two strategies to re-rank the abstracts set in order to have a large variety of treatments returned in the top articles. Almost two thirds of the top-10 returned documents are judged relevant, while nearly a quarter of the relevant treatments is returned in the top-10 abstracts. The second task aims at retrieving some clinical trials for which patients are eligible. Criteria used to determine the eligibility of patients are those found in the topics. Information such as trial location or status of clinical trials, which are important from a patient's point of view, are questionably not used in these topics. Several strategies have been tested, relaxing of constraints (data required or not), expansion of information requests thanks to synonyms or regex, and retrieval status value boosting for some criteria or fields. After judging, for almost half of the topics, a minimum of 50% of the documents retrieved are relevant, up to 90% for 10 of the 38 topics provided. Almost two thirds of the top-10 returned documents are judged relevant, while nearly a quarter of the relevant treatments is returned in the top-10 abstracts. Our best runs achieve highly competitive results depending on the measures, with on average being ranked #2 or #3 according to the official results for the literature task.