With a five-year survival rate of 9%, pancreatic ductal adenocarcinoma (PDAC) has the one of the worst prognoses of all cancers. Some limitations in the understanding of the disease are due to the lack of representative in vitro patient tumour models. In order to overcome this unmet preclinical need, this thesis outlines the establishment of a method for the development of organoid and isogenic matched primary cancer cell line models from patient derived xenograft (PDX) tumours. In order to create a patient-reflective yet versatile in vitro model, the matched primary cell line was developed further and subsequently generated organoids, termed cell line organoids (CLOs). These CLOs represent the phenotypic and transcriptomic profile of the original organoids and PDX tumour. Recent genome wide association studies (GWAS) and pathway analyses have implicated genes and single nucleotide polymorphisms (SNPs) from the maturity onset diabetes of the young (MODY) gene set and the Pujana ATM Pearson correlation coefficient (PCC) network in the development of PDAC. The biological functionality of the genomic variants identified from the GWAS-enriched pathways were assessed using in silico methods and experimental dual luciferase reporter assays. Genes in the MODY pathway such as hepatocyte nuclear factor-1 alpha/beta (HNF1A and HNF1B) act as transcription factors. Their role in cancer progression was assessed through single and double CRISPR knockouts in PDAC primary cell cultures. CUT&RUN (cleavage under targets and release using nuclease) was performed to identify genes regulated by HNF1A and HNF1B TFs. Additionally, targeting the DNA damage response (DDR) pathway in non-BRCA mutated PDAC was assessed using a novel drug which mimics the effect of a BRCA2 mutation. In conclusion, this thesis shows the development of novel, adaptable organoid models for functional validation of genomic variants in PDAC. Furthermore, biological investigation of GWAS pathway identified SNPs and genes from the MODY and Pujana ATM PCC pathways highlights the powerful nature of these tools in identifying genomic variants associated with PDAC. It also highlights the importance of functional experimental analysis to provide better understanding of their role in the development and progression of PDAC.