Personalized Oxycodone Dosing: Using Pharmacogenetic Testing and Clinical Pharmacokinetics to Reduce Toxicity Risk and Increase Effectiveness

3D printing processes in precise drug delivery for personalized medicine

With the advent of personalized medicine, the drug delivery system will be changed significantly. The development of personalized medicine needs the support of many technologies, among which three-dimensional printing (3DP) technology is a novel formulation-preparing process that creates 3D objects by depositing printing materials layer-by-layer based on the computer-aided design method. Compared with traditional pharmaceutical processes, 3DP produces complex drug combinations, personalized dosage, and flexible shape and structure of dosage forms (DFs) on demand. In the future, personalized 3DP drugs may supplement and even replace their traditional counterpart. We systematically introduce the applications of 3DP technologies in the pharmaceutical industry and summarize the virtues and shortcomings of each technique. The release behaviors and control mechanisms of the pharmaceutical DFs with desired structures are also analyzed. Finally, the benefits, challenges, and prospects of 3DP technology to the pharmaceutical industry are discussed.

Physiologically based pharmacokinetic modeling of ritonavir-oxycodone drug interactions and its implication for dosing strategy

The concomitant administration of ritonavir and oxycodone may significantly increase the plasma concentrations of oxycodone. This study was aimed to simulate DDI between ritonavir and oxycodone, a widely used opioid, and to formulate dosing protocols for oxycodone by using physiologically based pharmacokinetic (PBPK) modeling. We developed a ritonavir PBPK model incorporating induction and competitive and time-dependent inhibition of CYP3A4 and competitive inhibition of CYP2D6. The ritonavir model was evaluated with observed clinical pharmacokinetic data and validated for its CYP3A4 inhibition potency. We then used the model to simulate drug interactions between oxycodone and ritonavir under various dosing scenarios. The developed model captured the pharmacokinetic characteristics of ritonavir from clinical studies. The model also accurately predicts exposure changes of midazolam, triazolam, and oxycodone in the presence of ritonavir. According to model simulations, the steady-state maximum, minimum and average concentrations of oxycodone increased by up to 166% after co-administration with ritonavir, and the total exposure increased by approximately 120%. To achieve similar steady-state concentrations, halving the dose with an unchanged dosing interval or doubling the dosing interval with an unaltered single dose should be practical for oxycodone, whether formulated in uncoated or controlled-release tablets during long-term co-medication with ritonavir. The results revealed exposure-related risks of oxycodone-ritonavir interactions that have not been studied clinically and emphasized PBPK as a workable method to direct judicious dosage.

A potential paradigm shift in opioid crisis management: The role of pharmacogenomics

Pharmacogenetic investigations into the opioid crisis suggest genetic variation could be a significant cause of opioid-related morbidity and mortality. Variability in opioid system genes, including single nucleotide polymorphisms, manifest after pharmacogenetic testing, as previously invisible risk factors for addiction and overdose. Pharmacodynamic genes regulate opioid-sensitive brain networks and neural reward circuitry. Pharmacokinetic genes expressed in drug metabolic pathways regulate blood levels of active vs. inactive opioid metabolites. Elucidating the complex interplay of genetic variations in pharmacokinetic and pharmacodynamic pathways will shed new light on the addictive and toxic properties of opioids. This narrative review serves to promote understanding of key genetic mechanisms affecting the metabolism and actions of opioids, and to explore causes of the recent surge in opioid-related mortality associated with COVID-19. Personalised treatment plans centred around an individual's genetic makeup could make opioid-based pain management and opioid use disorder (OUD) treatments safer and more effective at both the individual and system levels.

Designing and conducting proof-of-concept chronic pain analgesic clinical trials

Introduction:

The evolution of pain treatment is dependent on successful development and testing of interventions. Proof-of-concept (POC) studies bridge the gap between identification of a novel target and evaluation of the candidate intervention's efficacy within a pain model or the intended clinical pain population.

Methods:

This narrative review describes and evaluates clinical trial phases, specific POC pain trials, and approaches to patient profiling.

Results:

We describe common POC trial designs and their value and challenges, a mechanism-based approach, and statistical issues for consideration.

Conclusion:

Proof-of-concept trials provide initial evidence for target use in a specific population, the most appropriate dosing strategy, and duration of treatment. A significant goal in designing an informative and efficient POC study is to ensure that the study is safe and sufficiently sensitive to detect a preliminary efficacy signal (ie, a potentially valuable therapy). Proof-of-concept studies help avoid resources wasted on targets/molecules that are not likely to succeed. As such, the design of a successful POC trial requires careful consideration of the research objective, patient population, the particular intervention, and outcome(s) of interest. These trials provide the basis for future, larger-scale studies confirming efficacy, tolerability, side effects, and other associated risks.

Conversion factors for assessment of driving impairment after exposure to multiple benzodiazepines/z-hypnotics or opioids

AIMS

Norway has introduced legal concentration limits in blood for 28 non-alcohol drugs in driving under the influence cases. As of 2016 this legislation also regulates the assessment of combined effects of multiple benzodiazepines and opioids. We herein describe the employed methodology for the equivalence tables for concentrations of benzodiazepines/z-hypnotics and opioids implemented in the Norwegian Road Traffic Act.

METHODS

Legislative limits corresponding to impairment at blood alcohol concentrations (BAC) of 0.02%, 0.05% and 0.12% were established for 15 different benzodiazepines and opioids. This was based on a concept of a linear relationship between blood drug concentration and impairment in drug naïve users. Concentration ratios between these drugs were used to establish conversion factors and calculate net impairment using diazepam and morphine equivalents.

RESULTS

Conversion factors were established for 14 benzodiazepines/z-hypnotics (alprazolam, bromazepam, clobazam, clonazepam, etizolam, flunitrazepam, lorazepam, nitrazepam, nordiazepam, oxazepam, phenazepam, temazepam, zolpidem and zopiclone) and two opioids (methadone and oxycodone).

CONCLUSIONS

Conversion factors to calculate diazepam and morphine equivalents for benzodiazepines/z-hypnotics and selected opioids, respectively, have been operative in the Norwegian Road Traffic Act as of February 2016. Calculated equivalents can be applied by the courts to meter out sanctions.

Individualized Hydrocodone Therapy Based on Phenotype, Pharmacogenetics, and Pharmacokinetic Dosing

OBJECTIVES

(1) To quantify hydrocodone (HC) and hydromorphone (HM) metabolite pharmacokinetics with pharmacogenetics in CYP2D6 ultra-rapid metabolizer (UM), extensive metabolizer (EM), and poor metabolizer (PM) metabolizer phenotypes. (2) To develop an HC phenotype-specific dosing strategy for HC that accounts for HM production using clinical pharmacokinetics integrated with pharmacogenetics for patient safety.

SETTING

In silico clinical trial simulation.

PARTICIPANTS

Healthy white men and women without comorbidities or history of opioid, or any other drug or nutraceutical use, age 26.3±5.7 years (mean±SD; range, 19 to 36 y) and weight 71.9±16.8 kg (range, 50 to 108 kg).

MAIN OUTCOME MEASURES

CYP2D6 phenotype-specific HC clinical pharmacokinetic parameter estimates and phenotype-specific percentages of HM formed from HC.

RESULTS

PMs had lower indices of HC disposition compared with UMs and EMs. Clearance was reduced by nearly 60% and the t1/2 was increased by about 68% compared with EMs. The canonical order for HC clearance was UM>EM>PM. HC elimination mainly by the liver, represented by ke, was reduced about 70% in PM. However, HC's apparent Vd was not significantly different among UMs, EMs, and PM. The canonical order of predicted plasma HM concentrations was UM>EM>PM. For each of the CYP2D6 phenotypes, the mean predicted HM levels were within HM's therapeutic range, which indicates HC has significant phenotype-dependent pro-drug effects.

CONCLUSIONS

Our results demonstrate that pharmacogenetics afford clinicians an opportunity to individualize HC dosing, while adding enhanced opportunity to account for its conversion to HM in the body.