BACKGROUND: The emergence of drug-resistant clones of Plasmodium falciparum is a major public health concern, and the ability to detect and track the spread of these clones is crucial for effective malaria control and treatment. However, in endemic settings, malaria infected people often carry multiple P. falciparum clones simultaneously making it likely to miss drug-resistant clones using traditional molecular typing methods. OBJECTIVES: Our goal was to develop a bioinformatics pipeline for compositional profiling in multiclonal P. falciparum samples, sequenced using the Oxford Nanopore Technologies MinION platform. METHODS: We developed the 'Finding P. falciparum haplotypes with resistance mutations in polyclonal infections' (PHARE) pipeline using existing bioinformatics tools and custom scripts written in python. PHARE was validated on three control datasets containing P. falciparum DNA of four laboratory strains at varying mixing ratios. Additionally, the pipeline was tested on clinical samples from children admitted to a paediatric hospital in the Central African Republic. RESULTS: The PHARE pipeline achieved high recall and accuracy rates in all control datasets. The pipeline can be used on any gene and was tested with amplicons of the P. falciparum drug resistance marker genes pfdhps, pfdhfr and pfK13. CONCLUSIONS: The PHARE pipeline helps to provide a more complete picture of drug resistance in the circulating P. falciparum population and can help to guide treatment recommendations. PHARE is freely available under the GNU Lesser General Public License v.3.0 on GitHub: https://github.com/Fippu/PHARE.