Alpha Fold 3 represents a revolutionary advancement in understanding protein structures and their interactions with other biomolecules, such as lipids, carbohydrates, and DNA. This deep learning network significantly enhances our ability to simulate biological processes, potentially transforming how we model organs digitally. By leveraging DNA information, we can simulate individual cells, tissues, and even whole organs, enabling precise tracking of illnesses, diagnoses, and therapies through a digital twin of the patient. This approach could substantially improve drug efficacy, as currently, only 20-30% of FDA-approved drugs work effectively for prescribed patients. Historically, many drugs have been inadequately tested for their effects on women, leading to high rates of market withdrawal. In silico medicine aims to personalize treatment, predicting drug effectiveness before administration. Overall, Alpha Fold 3 and its successors could greatly enhance medical outcomes by providing tailored healthcare solutions grounded in advanced simulations.