Medications Dexamethasone, Remdesivir or Colchicine, used to treat COVID-19 patients, have significant interactions with other medications and the human genome. The study presented in this paper investigates how to use the Personalized Medicine Therapy Optimization Method (PM-TOM) to minimize these interactions in polypharmacy therapies of COVID-19 patients. We applied PM-TOM on the EMR database of Harvard Personal Genome Project (PGP), drug database DrugBank and Comprehensive Toxicogenomics Database (CTD) to analyze polypharmacy therapies augmented with these medications. The main finding is that these COVID-19 medications significantly increase the drug and gene interactions in partially optimized (or unoptimized) therapies, which is not the case in the fully optimized ones. For example, the test results show that in polypharmacy treatments for patients having between 3 and 8 conditions, the average number of drug and gene interactions in partially optimized therapies ranges from 3 to 18 after adding Remdesivir, 4.3 to 20 Colchicine, and 4.7 to 23 Dexamethasone. On the other hand, these interactions in fully optimized therapies range only 0.6 to 5.2, 1.2 to 7, and 2.7 to 11, respectively. These results suggest that polypharmacy therapies should be carefully examined before adding these medications. This recommendation applies to all other situations when polypharmacy patients may conduct new serious conditions, such as COVID-19, requiring additional medications with a high number of drug and gene interactions.