Precision medication: An illustrative case series guiding the clinical application of multi-drug interactions and pharmacogenomics

Evaluating the Impact of Medication Risk Mitigation Services in Medically Complex Older Adults

Adverse drug events (ADEs) represent an expensive societal burden that disproportionally affects older adults. Therefore, value-based organizations that provide care to older adults—such as the Program of All-Inclusive Care for the Elderly (PACE)—should be highly motivated to identify actual or potential ADEs to mitigate risks and avoid downstream costs. We sought to determine whether PACE participants receiving medication risk mitigation (MRM) services exhibit improvements in total healthcare costs and other outcomes compared to participants not receiving structured MRM. Data from 2545 PACE participants from 19 centers were obtained for the years 2018 and 2019. We compared the year-over-year changes in outcomes between patients not receiving (control) or receiving structured MRM services. Data were adjusted based on participant multimorbidity and geographic location. Our analyses demonstrate that costs in the MRM cohort exhibited a significantly smaller year-to-year increase compared to the control (MRM: USD 4386/participant/year [95% CI, USD 3040−5732] vs. no MRM: USD 9410/participant/year [95% CI, USD 7737−11,084]). Therefore, receipt of structured MRM services reduced total healthcare costs (p < 0.001) by USD 5024 per participant from 2018 to 2019. The large majority (75.8%) of the reduction involved facility-related expenditures (e.g., hospital admission, emergency department visits, skilled nursing). In sum, our findings suggest that structured MRM services can curb growing year-over-year healthcare costs for PACE participants.

A graph model of combination therapies

The simultaneous use of multiple medications causes drug-drug interactions (DDI) that impact therapeutic efficacy. Here, we argue that graph theory, in conjunction with game theory and ecosystem theory, can address this issue. We treat the coexistence of multiple drugs as a system in which DDI is modeled by game theory. We develop an ordinary differential equation model to characterize how the concentration of a drug changes as a result of its independent capacity and the dependent influence of other drugs through the metabolic response of the host. We coalesce all drugs into personalized and context-specific networks, which can reveal key DDI determinants of therapeutical efficacy. Our model can quantify drug synergy and antagonism and test the translational success of combination therapies to the clinic.

Pitfalls and challenges associated with phenoconversion in forensic toxcicology

PURPOSE

In recent years, several publications have demonstrated the interest and the usefulness of pharmacogenetics in forensic toxicology. However, this approach remains namely focused on DNA-based phenotype, which may potentially lead to misinterpretation. Other determinants such as co-medication or physiological parameters may also impact the phenotype. This article aims to highlight the importance of considering such determinants in forensic toxicology, through the original case of a heroin-related fatality.

METHOD

Ethanol concentration determination and toxicological screening were performed using gas chromatography with flame ionization detection, liquid chromatography with diode array detection and gas chromatography with mass spectrometry detection. CYP2C19 and CYP2D6 genotypes were determined by Taqman® real-time PCR analyses.

RESULTS

Femoral blood analyses revealed the presence of ethanol, morphine, codeine, venlafaxine (VEN), O-desmethylvenlafaxine (ODV) and N-desmethylvenlafaxine (NDV), paroxetine, and risperidone. 6-acetylmorphine was also identified in urine. VEN, paroxetine and risperidone were quantified at supra-therapeutic or toxic blood concentrations. NDV was not quantified. The metabolic ratio of VEN (ODV to VEN) was exceptionally low (about 0.7). Pharmacogenetics testing showed that the patient was heterozygous for the CYP2C19*2 loss-of-function allele, which predict an intermediate metabolism for CYP2C19. None of the deficient CYP2D6 alleles investigated were identified. Those results suggest an extensive CYP2D6-metabolism phenotype.

CONCLUSION

A discrepancy was seen between the results of the genomic evaluation and the observed metabolic ratio of VEN. This tends to exclude a genetic origin and lead us to formulate other hypotheses, such as phenoconversion that may have been induced by drug interaction involving patients' regular medications. Phenoconversion is as a complex phenomenon that leads to genotype-phenotype mismatch without any genetic abnormality particularly described for cytochromes P450 2D6 and 2C19. Although transient, phenoconversion can have a significant impact on the analysis and interpretation of genotype-focused clinical outcomes correlation and in forensic toxicology conclusions.

Effectiveness of an Advanced Clinical Decision Support System on Clinical Decision-Making Skills in a Call Center Medication Therapy Management Pharmacy Setting: A Pilot Study

(1) Background: There is limited evidence related to the efficacy of advanced clinical decision support systems (CDSS) on the quantity of high-quality clinical recommendations in a pharmacy-related medication therapy management (MTM) setting. The study aimed to assess the effect of an advanced CDSS on the quantity of relevant clinical pharmacist recommendations in a call center MTM setting. (2) Methods: This pre-test/post-test with comparator group study compared clinical skills assessment scores between certified MTM pharmacists in March 2020. A Wilcoxon Signed Rank test assessed the difference between pre- and post-test scores in both groups. (3) Results: Of 20 participants, the majority were less than 40 years old (85%) with a Doctor of Pharmacy degree (90%). Nine were female. Intervention group participants had less than three years of experience as a pharmacist. The control group had less than three years (40%) or seven to ten years (40%) of experience. There was a significant increase in intervention group scores between pre- (median = 3.0, IQR = 3.0) and post-test segments (median = 6.5, IQR = 4.0, p = 0.02). There was no significant change between control group pre- and post-test segments (p = 0.48). (4) Conclusion: Pharmacist exposure to an advanced CDSS was associated with significantly increased quantity of relevant clinical recommendations in an MTM pharmacy setting.

Clopidogrel Dosing: Current Successes and Emerging Factors for Further Consideration

This review aimed to evaluate the clinical success of clopidogrel dosing based on CYP2C19 genotype and to identify the relevant additional factors that may be useful for consideration by the clinician when dosing individuals with clopidogrel. The results indicated that genotype-guided dosing in individuals with acute coronary syndrome undergoing percutaneous coronary intervention is frequently practiced, although the advantages remain controversial. Demographic factors, such as age, ethnicity, and some comorbidities, such as diabetes mellitus, can potentially contribute to further refinement of clopidogrel dosage but additional clinical studies to guide these practices are required. Drugs that are CYP2C19 or CYP3A4 inhibitors may reduce the effectiveness of clopidogrel and should be carefully considered during co-administration. In particular, as stated in the clopidogrel label, concomitant use with strong or moderate CYP2C19 inhibitors, such as omeprazole, should be avoided. Increased exposure and response to clopidogrel has been observed in smokers. Noteworthy, a very recent study has shown that smoking cessation in clopidogrel patients may result in reduced response and carries the risk of high on-clopidogrel platelet reactivity. Recent studies have shown clinically significant increases in exposure to CYP2C8 substrates (repaglinide, dasabuvir, and desloratadine) and a CYP2B6 substrate (s-sibutramine) following co-administration with clopidogrel, indicating that therapeutic strategies with clopidogrel should avoid these drugs.

Opioids, Polypharmacy, and Drug Interactions: A Technological Paradigm Shift Is Needed to Ameliorate the Ongoing Opioid Epidemic

Polypharmacy is a common phenomenon among adults using opioids, which may influence the frequency, severity, and complexity of drug–drug interactions (DDIs) experienced. Clinicians must be able to easily identify and resolve DDIs since opioid-related DDIs are common and can be life-threatening. Given that clinicians often rely on technological aids—such as clinical decision support systems (CDSS) and drug interaction software—to identify and resolve DDIs in patients with complex drug regimens, this narrative review provides an appraisal of the performance of existing technologies. Opioid-specific CDSS have several system- and content-related limitations that need to be overcome. Specifically, we found that these CDSS often analyze DDIs in a pairwise manner, do not account for relevant pharmacogenomic results, and do not integrate well with electronic health records. In the context of polypharmacy, existing systems may encourage inadvertent serious alert dismissal due to the generation of multiple incoherent alerts. Future technological systems should minimize alert fatigue, limit manual input, allow for simultaneous multidrug interaction assessments, incorporate pharmacogenomic data, conduct iterative risk simulations, and integrate seamlessly with normal workflow.