Coronavirus Disease 2019 (COVID-19) has been a global health crisis since it was first identified in December 2019. In addition to fever, cough, headache, and shortness of breath, an intense increase in immune response-based inflammation has been the hallmark of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) virus infection. This narrative review summarizes and critiques pathophysiology of COVID-19 and its plausible effects on drug metabolism and disposition. The release of inflammatory cytokines (e.g., interleukins, tumor necrosis factor α), also known as ‘cytokine storm’, leads to altered molecular pathophysiology and eventually organ damage in the lung, heart, and liver. The laboratory values for various liver function tests (e.g., alanine aminotransferase, aspartate aminotransferase, total bilirubin, albumin) have indicated potential hepatocellular injury in COVID-19 patients. Since the liver is the powerhouse of protein synthesis and the primary site of cytochrome P450 (CYP)-mediated drug metabolism, even a minor change in the liver function status has the potential to affect the hepatic clearance of xenobiotics. It has now been well established that extreme increases in cytokine levels are common in COVID-19 patients, and previous studies with patients infected with non-SARS-CoV-2 virus have shown that CYP enzymes can be suppressed by an infection-related cytokine increase and inflammation. Alongside the investigational COVID-19 drugs, the patients may also be on therapeutics for comorbidities; especially epidemiological studies have indicated that individuals with hypertension, hyperglycemia, and obesity are more vulnerable to COVID-19 than the average population. This complicates the drug-disease interaction profile of the patients as both the investigational drugs (e.g., remdesivir, dexamethasone) and the agents for comorbidities can be affected by compromised CYP-mediated hepatic metabolism. Overall, it is imperative that healthcare professionals pay attention to the COVID-19 and CYP-driven drug metabolism interactions with the goal to adjust the dose or discontinue the affected drugs as appropriate.

The inception of cancer treatment with chemotherapeutics began in the 1940s with nitrogen mustards that were initially employed as weapons in World War II. Since then, treatment options for different malignancies have evolved over the period of last seventy years. Until the late 1990s, all the chemotherapeutic agents were small molecule chemicals with a highly nonspecific and severe toxicity spectrum. With the landmark approval of rituximab in 1997, a new horizon has opened up for numerous therapeutic antibodies in solid and hematological cancers. Although this transition to large molecules improved the survival and quality of life of cancer patients, this has also coincided with the change in adverse effect patterns. Typically, the anticancer agents are fraught with multifarious adverse effects that negatively impact different organs of cancer patients, which ultimately aggravate their sufferings. In contrast to the small molecules, anticancer antibodies are more targeted toward cancer signaling pathways and exhibit fewer side effects than traditional small molecule chemotherapy treatments. Nevertheless, the interference with the immune system triggers serious inflammation- and infection-related adverse effects. The differences in drug disposition and interaction with human basal pathways contribute to this paradigm shift in adverse effect profile. It is critical that healthcare team members gain a thorough insight of the adverse effect differences between the agents discovered during the last twenty-five years and before. In this review, we summarized the general mechanisms and adverse effects of small and large molecule anticancer drugs that would further our understanding on the toxicity patterns of chemotherapeutic regimens.

Background/Objective(s): Many people in the United States (US) store medications, both prescription and over-the-counter, in their households. They may store medications in a designated location which could pose some convenience for the ease of use and access. However, most people may not know if their medications are stored properly to maintain stability and sterility. The objective of this study is to assess the medication storage locations in US households and evaluate appropriateness for each reported stored medication based on the published literature and drug information databases. Methods: 195 US Qualtrics panel members completed the National Household Medication Survey about medications stored at home and the number of residents in the household. This survey was a cross-sectional, self-administered, online survey completed through Qualtrics. The reported medications and their corresponding storage locations were categorized based on their appropriateness with moisture/humidity, temperatures and accidental exposure to children. The number of medications stored appropriately per household was recorded based on published literature, Lexicomp, Nature Made and Nature’s Bounty were consulted. Results: 154 (79%) households completed the survey. 75 (38.4%) households had at least one resident younger than 18 years old. 72 (46.8%) households stored at least one medication on a countertop. Only 28 (23.3%) households stored all their medications appropriately, while 92 (76.7%) households were storing at least one medication inappropriately. 34 (22%) households reported medications that were unidentifiable or no medications at all.  457 medications were reported by the 154 households. 13 of the households did not store any medications at home. 162-164 (~35%) of the medications were stored appropriately. 52 to 54 (~11%) medications had a moisture/humidity issue, 77 to 79 (~17%) had a temperature issue, and 42 to 44 (~9%) medications had both issues. 23 (5%) medications had an issue with a potential risk for accidental exposure to children, 6 (1.3%) had issues with both risk for accidental exposure to children and moisture/humidity, 8 (1.8%) had issues with both risk for accidental exposure to children and temperature, and 4 (0.9%) medications shared all three issues. Some numbers are reported with a range because certain medications have different storage recommendations based on formulation, so if a formulation wasn’t specified, both storage recommendations were taken into consideration. Conclusion: The findings suggest that many US households may be storing medications in inappropriate locations. In order to ensure medication stability and sterility and reduce the risk of accidental ingestion, pharmacists should proactively educate patients on proper storage of their medications and signs of degradation to avoid undesirable effects from the medications.

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Introduction Breast cancer is one of the most frequently diagnosed cancers in US. Its treatment regimens are complex as they involve premedications and concomitant medications, and can result in drug‐drug interactions (DDI). There are limited data available on cytochrome P450 (CYP)‐based drug interactions within the breast cancer regimens. The goal of the current study was to predict DDI between the drugs in the breast cancer treatment regimens. Methods Using the National Comprehensive Cancer Network (NCCN) guidelines the treatment regimens for breast cancer were identified. In silico DDI predictions were performed at steady state simulation using DDI module of the GastroPlus software provided by Simulation Plus Inc. The premedication and concomitantly administered drugs were evaluated as combinations with chemotherapeutic agents. Various enzyme inhibition kinetics parameters (e.g., Ki and EC50) required for simulation were obtained from the recent literature. Results Using the simulated and calculated gut and liver unbound perpetrator concentration during the steady state simulation, combinations of drugs showed differential DDI potential. Aprepitant, an antiemetic agent, showed moderate to strong inhibition when used with docetaxel, paclitaxel, abemaciclib and olaparib. In certain cases calculated liver perpetrator concentration showed a stronger inhibitory prediction of chemotherapeutic agents compared to simulated liver perpetrator concentration. Results obtained with netupitant varied from weak to strong inhibitory interactions with chemotherapeutic agents. Conclusions In silico analyses appear to confirm that breast cancer treatment regimens may interact with each other and influence plasma concentrations of chemotherapeutic agents. We conclude that toxicity or therapeutic failure from anticancer agents could be due to interactions within the breast cancer treatment regimens. Support or Funding Information The GastroPlus software 9.5 version was provided by Simulations Plus, Inc. (Lancaster, CA)