Pancreatic adenocarcinoma (PAAD) is notorious for its limited treatment options and dismal prognosis

underscoring an urgent need for innovative therapeutic strategies. This study leverages advanced bioinformatics and a novel ChatGPT-4o evaluation framework to identify and validate SRC kinase as a significant drug target for PAAD. Initial bioinformatics screening illustrated SRC’s critical involvement in essential signaling pathways associated with the disease. Subsequently

the ChatGPT-4o framework provided an unbiased

efficient evaluation

emphasizing SRC’s role in disease mechanisms. Our findings reveal substantial overexpression of SRC in PAAD compared to normal pancreatic tissue

with expression levels escalating in line with tumor grade and stage. Protein expression analysis using the Human Protein Atlas dataset showed a statistically significant difference between PAAD samples and normal samples for SRC (

P

  1×10

-15

). Survival analysis using the Kaplan-Meier Plotter dataset further demonstrates a strong association between high SRC exp

ression and reduced survival

with hazard ratios of 1.45 (

P

 7.69×10

-3

) for overall survival and 2.15 (

P

  9.19×10

-5

) for disease free survival in advanced disease stages. SRC's involvement in key oncogenic pathways suggests its potential as part of combination therapies

enhancing the efficacy of existing treatments by targeting complementary mechanisms. This study shows the therapeutic relevance of SRC and demonstrates the effectiveness of combining innovative AI technologies with traditional bioinformatics to accelerate the discovery and validation of critical drug targets in oncology.