The efficacy of existing antimalarials is threatened by parasite resistance, driving the need for a well-stocked pipeline of potential replacement therapies. A global effort to carry out phenotypic screening in live parasite assays has identified many promising hit compounds, but elucidating the targets of these compounds, often a necessary step in the hit-to-lead development process, has been slow. This is because target identification has rested primarily on one technique, in vitro evolution and whole genome sequencing (IVIEWGA), which is time consuming and difficult to scale. Large scale chemical-genetic screening, or chemogenomics, has facilitated rapid and scalable drug target identification in other organisms. To establish a chemogenomic screening system for target identification in asexual Plasmodium stages, I leveraged an existing library of P. berghei artificial chromosomes (PbACs), of which ~600 containing potential drug targets (transporters, enzymes, metabolic pathways) were engineered to possess a unique DNA barcode. These barcodes can be used to detect and quantify constructs within complex pools using a next generation sequencing (NGS) process termed barcode sequencing (BarSeq), allowing screening of multiple lines in parallel. I transfected PbACs into P. knowlesi parasites grown in vitro in human erythrocytes, establishing that PbACs are maintained stably over many generations and the encoded P. berghei genes are transcribed in recipient parasites, resulting in systematic target overexpression. P. knowlesi was chosen because of its extremely high transfection efficiency, which allowed pooled transfection of up to ~100 constructs at once, generating complex populations of mutant strains. These parasite pools were then exposed to antimalarial drug candidates, and the relative distribution of PbACs within the pool compared before and after < 2 weeks of drug treatment using BarSeq. Pilot screens probing for known gene-compound associations - DSM1-dhodh, KDU691-pi4k and NITD609-atp4 - identified those targets with high sensitivity in all cases, and in one case also identified other genes involved in the same mechanism of action pathway (rab11a). The remarkable sensitivity of the BarSeq approach also permitted the identification of some of these targets in vastly more complex pools of over 400 strains. I applied the system to a spectrum of approved and developmental antimalarial inhibitors with both known and unknown mechanisms of action, successfully identifying their targets in some cases, particularly those with an underlying copy number variation (CNV) resistance mechanism. In one case the approach elucidated a possible novel target, the parasite signal peptidase enzyme sec11. While downstream validation experiments were unable to confirm whether sec11 was indeed the target for its interacting compound, it could represent a promising druggable target in the parasite warranting further exploration. The PbAC/chemogenomics approach is highly sensitive at identifying targets and is adaptable to high-throughput approaches, thus represents a valuable early-stage tool to explore the mechanisms of action of antimalarial compounds.