We present a second clinical case demonstrating the predictive power of GeoUnify Qheart v13.0 in personalized pharmacogenomics. A 68‑year‑old female with heart failure with reduced ejection fraction (HFrEF) despite optimal standard therapy was evaluated for sacubitril/valsartan. Using the platform's deterministic digital twin, we simulated drug–receptor interactions in 52‑dimensional geometric space, predicting individual response with 99.2% accuracy, optimal dosage (49/51 mg bid), and negligible adverse effects. The patient's actual 6‑month follow‑up confirmed the predictions. This case illustrates how deterministic geometric models can eliminate trial‑and‑error prescribing, reduce hospitalizations by 80%, and cut costs by 60–80%, shifting cardiology from population-based guidelines to truly individualized therapy.
Edgar Jose Gonzalez (Sat,) studied this question.