Dosage-Response Curve Analysis for Drug Discovery

Introduction: This analysis is to evaluate how varying drug dosages affect the biological response in preclinical experiments. This analysis helps in identifying potent compounds and assessing their effectiveness based on dosage, IC50, and efficacy metrics.

 

Requirements: Create a Pyspark logic by Read the table “purgo_playground.dosage_response_analysis“. Aggregate the Compound statistics by using groupBy("compound_id"), the code computes with Average dosage (avg_dose_mg), Average response (avg_response_pct), Average efficacy score (avg_efficacy), Average IC50 (avg_ic50), Average AUC (avg_auc), Count of experiments per compound, Calculate the potency level based on avg_ic50, compounds are classified into High potency (avg_ic50 < 2.0), Moderate potency (2.0 ≥ avg_ic50 ≤ 4.0), Low potency (avg_ic50 > 4.0)

 

Final Output: Displays final results.

 

Unity Catalog: “purgo_playground.dosage_response_analysis”