Drug–Drug Interactions and Pharmacogenomic Evaluation in Colorectal Cancer Patients: The New Drug-PIN® System Comprehensive Approach

Abstract

Drug–drug interactions (DDIs) can affect both treatment efficacy and toxicity. We used Drug-PIN® (Personalized Interactions Network) software in colorectal cancer (CRC) patients to evaluate drug–drug–gene interactions (DDGIs), defined as the combination of DDIs and individual genetic polymorphisms. Inclusion criteria were: (i) stage II-IV CRC; (ii) ECOG PS (Performance status sec. Eastern coperative oncology group) ≤2; (iii) ≥5 concomitant drugs; and (iv) adequate renal, hepatic, and bone marrow function. The Drug-PIN® system analyzes interactions between active and/or pro-drug forms by integrating biochemical, demographic, and genomic data from 110 SNPs. We selected DDI, DrugPin1, and DrugPin2 scores, resulting from concomitant medication interactions, concomitant medications, and SNP profiles, and DrugPin1 added to chemotherapy drugs, respectively. Thirty-four patients, taking a median of seven concomitant medications, were included. The median DrugPin1 and DrugPin2 scores were 42.6 and 77.7, respectively. In 13 patients, the DrugPin2 score was two-fold higher than the DrugPin1 score, with 7 (54%) of these patients experiencing severe toxicity that required hospitalization. On chi-squared testing for any toxicity, a doubled DrugPin2 score (p = 0.001) was significantly related to G3–G4 toxicity. Drug-PIN® software may prevent severe adverse events, decrease hospitalizations, and improve survival in cancer patients.

An Example of Personalized Treatment in HR+ HER2+ Long Survivor Breast Cancer Patient (Case Report)

“…The idea of personalized therapy is becoming increasingly popular, not only based on molecular targets, but also preventing any drug-drug-gene interactions (DDGIs), which could lead to serious adverse reactions, especially in patients who receive polypharmacotherapy due to comorbidities [1].…”

“…Thanks to the supportive treatments, especially in favor of hepatic detoxification, and the reduction of the dosage of drugs, we were able to guarantee the patient an excellent therapeutic adhesion. However, the possibility to use an easy-to-use pharmacogenomics tool such as Drug-PIN software [1] to prevent toxicities during cancer treatment through the evaluation of both clinical and genomic factors, as well as by taking into account the use of concomitant drugs, could ensure the application of personalized medicine and better compliance with treatments. Further studies are necessary for the identification of predictive factors of toxicity of treatments used in order to ensure maximum benefit to patients and minimum toxicity of proposed therapies.…”

“…The idea of personalized therapy is becoming increasingly popular, not only on the basis of molecular targeted therapy, but also by considering any potential drug-drug-gene interaction (DDGI) to prevent adverse events during cancer treatment, in order to improve patients outcome [1]. Based on this consideration, the pharmacogenomics profile to define the DDGI and the use of smart software to easily understand the risk of toxicity during treatment could be very useful in personalized cancer management.…”

Individualized Drugs’ Selection by Evaluation of Drug Properties, Pharmacogenomics and Clinical Parameters: Performance of a Bioinformatic Tool Compared to a Clinically Established Counselling Process

“…The patient's parameters evaluated by the Drug-PIN CDSS are: age, sex, body mass index, smoking, alcohol and caffeine consumption, diagnosis, creatinine, transaminase level, pharmacogenomic markers; the drug-related parameters evaluated by the Drug-PIN are: drug-drug interactions, official drug labels, disease guidelines. 17,18 The process for automated poly-therapy optimization consists of four steps: ì) loading of all the available patient's parameters, including demographic, phenotypic and genotypic data, on the "patient information" form; ìì) loading the names of the drugs composing the baseline poly-therapy on the "therapy" form; ììì) reviewing eventual medication problems detected by the system; the extent of the medication problem is expressed by a numerical value, the Drug-PIN score, and highlighted by a color code ranging from green (low-risk drug cocktail, score range 0-20) to yellow (moderate risk drug cocktail, score range 21-60) and to red (high-risk drug cocktail, score >60); iv) exchanging drugs in the baseline cocktail choosing among the proposed list of alternative drugs (eg, same therapeutic target). The proposed alternative drugs are ranked according to the extent of improvement in the Drug-PIN score, allowing rapid optimization of the baseline therapy.…”

“…Recently, a Clinical Decision Support Systems (CDSS) for patient-sized drug selection was released, the Drug-PIN system. 17,18 Interestingly, the system embeds information from multiple knowledge bases and sources, including the international commission CPIC (Clinical Pharmacogenetics Implementation Consortium), 19 reporting the functional effect on drug disposition of validated pharmacogenetic markers; the Beers-and PRISCUS-Lists, 20,21 which consider age-related drug problems; the drug-labels themselves, which list clinically relevant DDIs. Further, the CDSS takes into account the effect played on drug action by patient's renal and liver functionality.…”