How does hydrocodone metabolized

Other drugs in the opioid class, such as fentanyl, meperidine, methadone, and opiate antagonists such as naloxone, are not detected. The Pharmacological Basis of Therapeutics. Biomedical Publications; Ther Drug Monit. Langman LJ, et al: Clinical Toxicology. Chromatographic separation was performed using an acetonitrile—formic acid—water gradient running at 0.

Five microliters of the solution was injected for each specimen. All spectra were collected using positive electrospray ionization. Multiple reaction monitoring MRM mode was used for quantitation. Scan time was set to ms. In MRM mode, two transitions were used to identify and quantitate a single compound.

A quantitative transition was used to calculate concentration based on the quantifier ion and a second transition was used to ensure accurate identification of the target compound based on the ratio of the qualifier ion to the quantifier ion. Hydrocodone and hydromorphone were obtained from Cerilliant Corp. Round Rock, TX. A four-point calibration curve was created by using a linear fit and forcing the line to go through the origin.

Descriptive statistics and graphical analyses were conducted with Microsoft Excel Microsoft Corp. Single values for hydrocodone, hydromorphone, and metabolic ratio [hydromorphone] divided by [hydrocodone] were also calculated for each subject by log-transforming the data, calculating an average and a standard deviation within a subject, and back-transforming the values.

Data from the first visit were used from each subject who took hydrocodone but not hydromorphone for pain. Subjects with detectable concentrations of morphine, codeine, and heroin metabolite 6-monoacetylmorphine were excluded due to interference with hydrocodone metabolism 9. Subjects with concentrations below the lower limit of quantitation for one analyte, either hydrocodone or hydromorphone, were plotted to determine the percent frequency of the population that are ultra-rapid or poor metabolizers.

Figure 2 is a flow chart of patient selection for the study. From this group, 53, subjects reportedly taking hydrocodone, and no other medications that would lead to formation of hydromorphone or hydrocodone, were included for further study. If a subject had multiple visits, only their first visit was analyzed to prevent skewing the data toward subjects with multiple visits.

In addition, a separate analysis to determine within-subject variability included urine specimen results from subjects with five or more visits 1, total visits. Flow chart of patient selection. The excretion observations showed that the range of concentration values was quite large. For that reason, logarithmic representations of the data were used.

The data are plotted logarithmically and approximate a Gaussian distribution. The median was 1. These statistics are summarized in Table I. The logarithmic plot also approximates a Gaussian distribution. The median was 0. These statistics are also summarized in Table I. These statistics describe the range of values expected of patients prescribed hydrocodone. The next analysis was performed to establish whether or not the metabolic pathway for conversion of hydrocodone to hydromorphone was saturable.

This implies that the formation of hydromorphone was concentration-dependent, but because there was not a one-to-one ratio, the pathway may be saturable. An alternative explanation is that the metabolite has not had time to reach steady state. A second way to examine the question was to use the metabolic ratio. In an attempt to correct for the lack of hydrocodone dose information, the variance in metabolism and metabolic ratio were calculated from a narrow range of excreted hydrocodone concentrations excluding the extremes of concentrations to try to capture subjects taking the most common doses.

To examine this concept, a slice of the range of values around the median hydrocodone concentration of Figure 4 A was used. For the selected hydrocodone concentration range median log value of 0.

The variance is the square of the standard deviation SD. The variance was A similar analysis was performed using the corresponding metabolic ratios for the same range of hydrocodone concentrations.

Again, an approximated Gaussian distribution of values was observed. The SD was 0. The large population base allowed determination of the percent of ultra-rapid and poor metabolizers.

For this analysis, ultra-rapid metabolizers were defined as those patients whose urine excretion pattern contained no hydrocodone in the presence of high concentrations of hydromorphone.

A sigmoidal plot Figure 5 A was used to estimate the number of patients with no hydrocodone versus increasing concentrations of hydromorphone. The resulting estimation for the prevalence of ultrarapid metabolism was approximately 0.

In contrast, considering patients forming no hydromorphone as poor metabolizers, a similar sigmoidal plot analysis Figure 5 B revealed an estimate of the prevalence of poor metabolizers of 4.

However, some subjects described as poor metabolizers may include those that ingested their hydrocodone directly before voiding a specimen and thus did not have sufficient time to metabolize hydrocodone to hydromorphone. Inter-subject variability was examined by comparing variability in concentrations from specimens obtained from the first visit of all subjects. Intra-subject variability was assessed by examining the specimens available from patients with five or more visits to the physician's office.

For hydrocodone excretion concentrations, inter-subject variability was fold and intra-subject variability was fold Table II. Using the same analysis for hydromorphone excretion, a fold variability between-subjects and a fold within-subjects variability were observed Table II. The metabolic ratio [hydromorphone] divided by [hydrocodone] represents the metabolism of hydrocodone for a subject at a point in time.

The variability of metabolic ratio between subjects was fold and within subjects was fold. Baselt, R. American Association of Medical Review Officers. MRO Alert , 8 , Cone, E. Drug Metabolism and Disposition, 6 , Current Pharmacogenomics , 3 , Food and Drug Administration, Heltsley, R.

Prevalence Patters of Prescription Opiates and Metabolites. Hydrocodone stimulates the mu-opioid receptor, inhibits the release of transmitters from sensory neurons and alters pain transmission. In , the American Association of Poison Control Centers' National Poison Data System NPDS reported 11, poisoning cases that involved hydrocodone alone, 26, poisoning cases that involved hydrocodone in combination with other drugs and 21 hydrocodone-associated deaths 1.

Adverse or toxic effects of overdose include stupor, muscle flaccidity, respiratory depression, hypotension and coma 2. Hydrocodone is marketed as an extended release oral formulation and as a combination product with acetaminophen or ibuprofen. The combination products are classified as Schedule III controlled substances. Other hydrocodone metabolites detected in human urine include dihydrocodeine, isodihydrocodeine, dihydromorphone and isodihydromorphone 3 , 4.

Genetic polymorphisms of CYP2D6 result in a phenotypic classification ranging from poor to ultra-extensive metabolizers 7. Patients who are CYP2D6 poor metabolizers may experience variable hydrocodone side effects, efficacy and dependence 8 , 9. Inter- and intrasubject variability of urinary hydrocodone has been reported to be and fold, respectively Numerous factors are known to influence inter- and intrasubject variability of hydrocodone and metabolites.

Plasma concentrations of hydromorphone are higher in men, whereas women have higher norhydrocodone plasma concentrations The influence of these factors on hydrocodone, hydromorphone and norhydrocodone concentrations has not been extensively studied in urine.

Understanding which factors and the extent of such factors in influencing hydrocodone concentration variability is important in possibly explaining differential response patterns in patients. The purpose of this retrospective data analysis was to evaluate the effects of sex, age, urinary pH and concurrent use of CYP2D6 and CYP3A4 inhibitors on urinary hydrocodone, hydromorphone and norhydrocodone mole fractions. Urine specimens were collected at pain physician practices from patients on opioid therapy for routine drug monitoring purposes.

In brief, an Agilent series binary pump SL LC system, well-plate sampler and thermostatted column compartment paired with an Agilent Triple Quadrupole Mass Spectrometer and Agilent Mass Hunter software were used for the analysis of hydrocodone, hydromorphone and norhydrocodone. Chromatographic separation was performed using an acetonitrile—formic acid—water gradient running at 0. Five microliters of the solution was injected for each sample.

All spectra were collected using positive electrospray ionization. Multiple reaction monitoring MRM mode was used for quantitation. Scan time was set to ms. In the MRM mode, two transitions were used to identify and quantitate a single compound. A quantitative transition was used to calculate concentration based on the quantifier ion, and a second transition was used to ensure accurate identification of the target compound based on the ratio of the qualifier ion to the quantifier ion.

Hydrocodone, hydromorphone and normorphone were obtained from Cerilliant Corp. A four-point calibration curve was created by using a linear fit and forcing the line to go through the origin.

In order to compare the parent drug and metabolite in urine, creatinine normalized data were converted into moles Mole fractions of hydrocodone, hydromorphone and norhydrocodone were then determined by multiplying the molecular weight and dividing by 1, For the age analysis, specimens were divided into three groups: 16—39 years, 40—64 years and 65 years and older For the evaluation of urinary pH, specimens were divided into three groups: 3.

Descriptive statistics were conducted with Microsoft Excel Microsoft Corp. Mole fractions were log-transformed to achieve a normal distribution. Data are summarized in Table I. Significant differences in hydrocodone, hydromorphone and norhydrocodone mole fractions were observed.

Hydrocodone mole fractions were highest in the year and older age group compared with the other age groups. The hydromorphone mole fractions were similar across the evaluated age groups, whereas norhydrocodone mole fractions were highest in the to year age group. There were 38,, 7, and 2, specimens with urine pH of 3. Hydromorphone and norhydrocodone mole fractions were higher in the neutral and basic urinary pH groups Table II. There were 3, patients with a physician-reported CYP2D6 inhibitor medication.

There was no difference in hydrocodone mole fractions between the CYP2D6 inhibitor group and the control group. There were patients with a physician-reported CYP3A4 inhibitor medication. Hydrocodone, hydromorphone and norhydrocodone mean mole fractions during concurrent use of a CYP3A4 inhibitor were 0.