Integrating the Science of Opioids Into Regulated Drug Testing

Home , Norhydrocodone, Noroxycodone, Noroxymorphone

Integrating the Science of Opioids Into Regulated Testing

Presented by Ron R. Flegel, B.S., MT(ASCP), MS. , Director Division of Workplace Programs Center for Substance Abuse Prevention Substance Abuse and Mental Health Services Administration

2017 MID‐ATLANTIC REGIONAL CONFERENCE IN OCCUPATIONAL & ENVIRONMENTAL MEDICINE September 24, 2017 Problem 3 • National Opioid Overdose Epidemic – Drug overdose is the leading cause of accidental death in the US, with 52,404 lethal drug overdoses in 2015. Opioid addiction is driving this epidemic, with 20,101 overdose deaths related to prescription pain relievers, and 12,990 overdose deaths related to heroin in 2015

– Source: http://www.asam.org/docs/default‐source/advocacy/opioid‐addiction‐disease‐facts‐figures.pdf Nora D. Volkow, M.D.

Director of National Institute on Drug Abuse Drug Abuse Warning Network (DAWN) 5

Drug‐Related Emergency Department (ED) Visits • ED visits involving misuse or abuse of pharmaceuticals increased 128 percent between 2004 and 2011, from 626,470 visits in 2004 to 1,428,145 visits in 2011 • ED visits involving adverse reactions to pharmaceuticals taken as prescribed increased 86 percent between 2005 and 2011, from 1,250,377 visits in 2005 to 2,301,059 visits in 2011

• Source: http://www.samhsa.gov/data/sites/default/files/DAWN096/DAWN096/SR096EDHighlights2010.pdf Research Studies

Oxycodone and Hydrocodone: Kinetic Relationships of Whole Blood to Oral Fluid Edward J. Cone1, Rebecca Heltsley2, David L. Black2,3, Ronald R. Flegel4, Charles P. LoDico4, and John M. Mitchell5

1Johns Hopkins School of Medicine, Baltimore, MD; 2Aegis Sciences Corporation, Nashville, TN; 3Vanderbilt University, Department of Pathology, Immunology and Microbiology, Nashville, Prescription Opioids. I. Profiling Oxycodone and TN; 4Substance Abuse and Mental Health Services Administration, Division of Workplace Metabolites in Urine Programs, Rockville, MD; 5RTI International, Research Triangle Park, NC Ronald R. Flegel*1, Charles P. LoDico1, Rebecca Heltsley2, David L. Black2,3, John M. Mitchell4, and Edward J. Cone5

1Substance Abuse and Mental Health Services Administration, Division of Workplace Programs, Rockville, MD, USA; 2Aegis Sciences Corporation, 515 Great Circle Road, Nashville, TN, USA; 3Vanderbilt University, Department of Pathology, Immunology and Microbiology Nashville, TN, USA; 4RTI International, Research Triangle Park, NC, USA; 5Johns Hopkins School of Medicine, Disposition of Oxycodone and Hydrocodone in Baltimore, MD, USA Oral Fluid Rebecca Heltsley*1, David L. Black1,2, John M. Mitchell3, Charles P. LoDico4, Ronald R. Flegel4, and Edward J. Cone5

1Aegis Sciences Corporation, 515 Great Circle Road, Nashville, TN, USA; 2Vanderbilt Prescription Opioid Abuse. II. Profiling University, Department of Pathology, Immunology and Microbiology Nashville, TN, USA; 3RTI International, Research Triangle Park, NC, USA; 4Substance Abuse and Mental Health Hydrocodone and Metabolites in Urine Services Administration, Division of Workplace Programs, Rockville, MD, USA; 5Johns Charles P. LoDico*1, Ronald R. Flegel1, Rebecca Heltsley2, David L. Black2,3, Hopkins School of Medicine, Baltimore, MD, USA John M. Mitchell4, and Edward J. Cone5

6 Study Overview

• Conduct a dosing study under IRB approval and informed consent with healthy, drug-free volunteers

• Characterize the time course of appearance and disappearance of oxycodone and hydrocodone •Oral fluid • Blood •Urine

• Additional studies were completed for oxymorphone and hydromorphone

7 Study Dosing Information 8

• Oxycodone • Single dose, one OxyContin® tablet, 20 mg oxycodone HCl (total = 17.9 mg OC) • Hydrocodone • Single dose, two Norco® tablets, each containing 10 mg hydrocodone bitartrate (total =12.1 mg HC) and 325 mg acetaminophen • 20 mg HC bitartrate (12.1 mg HC) 8 Review of Oxycodone Metabolism (Urine, Oral Fluid and Blood) 9

N CH3 NH OH CYP3A4 OH

O O H3CO O H3CO O Oxycodone (OC) Noroxycodone (NOC)

CYP2D6

N CH3 NH OH OH

HO O O HO O O Oxymorphone (OM) Noroxymorphone (NOM) Review of Hydrocodone Metabolism (Urine, Blood, & Oral Fluid) 10

N CH3 NH

CYP3A4

O O H3CO O H3CO O Hydrocodone (HC) Norhydrocodone (NHC)

CYP2D6 6-Ketoreductase

N CH3 N CH3 H

HO O O H3C O O OH Hydromorphone (HM) Dihydrocodeine (DHC) Results: Adverse Events

• No serious AEs • Mild to moderate: OC, 8 (4M/4F); HC, 6 (2M/4F) • Nausea: OC, 5; HC 6 • Vomiting: OC, 4; HC 3 • Lightheadedness: OC, 4; HC, 4 • Itching: OC, 2; HC, 1 • Other minor reports: antecubital soreness, irritability, shaky, and feeling high 11 Note: Canada’s Legal Status 12 • Oxycodone ‐ Schedule I

• Oxymorphone ‐ Schedule I

• Hydromorphone ‐ Schedule I

• Hydrocodone ‐ Schedule I Blood and Oral Fluid Results

13 Oxycodone and Hydrocodone: Comparison of Oral Fluid to Blood 14 Noroxycodone & Norhydrocodone Comparison of Oral Fluid to Blood 15 Cmax, OF/BL Ratios, Correlations

16 Oxycodone OC NOC OM NOM OF Cmax (N) 132.7 (12) 18.7 (12) 1.6 (7) ND BL Cmax (N) 20.6 (12) 15.6 (12) ND 6.4 (6) OF/BL Ratio 5.4 (12) 1.0 (12) NA NA OF:BL, r 0.719 (12) 0.651 (12) NA NA Hydrocodone HC NHC HM DHC OF Cmax (N) 207.7 (12) 12.8 (12) ND 6.4 (12) BL Cmax (N) 49.3 (12) 18.7 (11) ND ND OF/BL Ratio 3.2 (12) 0.7 (11) NA NA OF:BL, r 0.733 (12) 0.423 (11) NA NA Oxycodone Correlation

17 Hydrocodone Correlation

18 Blood and Oral Fluid Kinetics

Oxycodone Hydrocodone

Kinetic Parameter OC NOC HC NHC

Oral fluid T1/2, hr (N) 4.6 (12) 8.3 (12) 4.4 (12) 6.2 (9)

Blood T1/2 hr (N) 5.6 (11) 11.8 (11) 4.5 (12) 7.7 (11) Summary of Blood and Oral Fluid

20 • OC and HC appeared in OF and BL within 15-30 minutes after oral administration • Because OC was an extended release preparation, entry into oral fluid was slower and concentrations remained elevated longer relative to HC • The profile of appearance and disappearance was similar but analytes were detected for longer times in OF • OF concentrations were considerably higher for parent drug in OF compared to urine • Nor metabolite concentrations were similar in OF and BL • Kinetic parameters were similar • Correlations were high but not predictive • Notably, O-demethylated metabolites (OM, HM) were in low or non-detectable concentrations • The N-demethylated metabolites were present at similar times as the parent drug but were generally in lower concentrations • A pilot study of blood hydrolysis (n=2) revealed somewhat higher concentrations of OM (data not shown) 20 Urine Results 21 Mean Excretion of OC and Metabolites & HC and Metabolites in Urine (Hydrolyzed)

3500 3500

3000 3000 Total OC, ng/mL 2500 2500 Total OM, ng/mL HC

Total NOC, ng/mL 2000 HM 2000 NHC Total NOM, ng/mL 1500 ng/mL 1500 ng/mL DHC 1000 1000

500 500

0 0 1 3 5 7 9 11131926303450 1357911131926303450 Hours (Collection Period Midpoints) Hours (Collection Period Midpoints)

• OC and NOC generally became detectable in the 0-2 h collection period. OM generally became detectable in the 2-4 h collection period. • Total HM and DHC generally became detectable in the 2- • OC and its metabolite concentrations usually peaked within 3–9 h, then 4 h collection period. declined. • HC and metabolites’ concentrations peaked within 3-9 h • After 24 hours, 18 specimens contained detectable concentrations of post-dosing, then declined. both OM and NOC, with no OC. • Generally, total concentrations of OC and NOC were similar to free concentrations. • Total OM concentrations were substantially greater than free concentrations. 22 • Total NOM concentrations were slightly higher than free concentrations. Variability of HC Excretion in Urine (Hydrolyzed) 23

6000

5000

4000

3000 ng/mL

2000

1000

0 13579111319263034 Hours (Midpoint)

HC was present in 9 of 12 subjects’ specimens from the first collection period (0-2 h). Oxycodone: Mean Detection Times Total OC, OM, NOC and NOM in Urine (Time to last Positive by Cutoff) 24

Hours 0 1020304050

3.0 2.3 2000 8.8 0.7 7.3 8.3 1000 19.8 1.8 OC 15.5 20.8 OM 500 24.0 11.7 NOC 19.3 ng/mL

26.7 300 28.3 NOM 20.5 24.7 33.0 150 32.7

Cutoff, 28.7 27.7 37.0 100 36.0 30.7 29.3 41.3 50 39.3 31.8

• Mean detection times for NOC were 5 to 12.5 hours longer than mean OC detection times at all cutoffs. • Using cutoffs up to 2000 ng/mL, mean detection times for OM were 1 to 12 hours longer. than mean OC detection times. However, using the 2000 ng/mL cutoff, the mean detection time for OC was 0.7 h longer than the mean OM detection time. 24 Oxycodone/Metabolite(s) Detection Times (Time to Last Positive)

Hours 0 1020304050

45 3.0 OC OC 2000 2.3 OM 8.8 OM NOC 30 7.3 NOC 1000 8.3 19.8 15 15.5 500 20.8 0 24.0 0 500 1000 1500 2000 19.3 300 26.7 28.3 24.7 150 33.0

Cutoff, ng/mL Cutoff, 32.7 27.7 100 37.0 36.0 29.3 50 41.3 39.3 25 Hydrocodone: Mean Detection Times Total HC, HM, NHC and DHC in Urine, Time to last Positive by Cutoff 26

Hours 0 1020304050

2.8 2000 4.5

4.0 1000 0.3 9.3 HC

9.0 2.0 HM 500 17.3 NHC 12.2 ng/mL

5.2 300 21.7 DHC 1.3 18.2 150 12.0 Cutoff, 29.0 4.8 20.5 14.3 100 33.0 7.3 27.7 25.5 50 39.7 16.3 • Mean detection times for NHC were 1.7 to 12.5 hours longer than mean HC detection times at all cutoffs. • Mean detection times of HC were longer than mean HM and DHC detection times at all cutoffs. 26 Hydrocodone Detection Times (Time to Last Positive)

Hours 0 1020304050 2.8 2000 0.0 HC 4.5 HC 0.0 HM 45 HM 4.0 NHC 0.3 NHC DHC 1000 9.3 0.0 DHC 30 9.0 2.0 500 17.3 15 0.0 12.2 5.2 300 21.7 0 1.3 0 500 1000 1500 2000 18.2 12.0 150 29.0 Cutoff, ng/mL Cutoff, 4.8 20.5 14.3 100 33.0 7.3 27.7 25.5 50 39.7 16.3 27 Cutoff Evaluation by Analyte* Number of Specimens with Individual/Combined Analytes at or above Cutoff

28 *Total analyte concentrations after hydrolysis 140 140

120 120

100 100 Cutoff Cutoff ≥ ≥ OC 80 80 HC OM HM

NOC Specimens

Specimens 60 60 NHC of

of OC/ OM DHC OM/NOC 40 40 HC/HM Number Number OC/OM/NOC 20 20

0 0 50 100 150 300 500 1000 2000 50 100 150 300 500 1000 2000 Cutoff Concentration Cutoff Concentration

• The combination of OC, OM, and NOC identified the • Of the single analytes, NHC identified the largest largest number of specimens at each cutoff evaluated. number of specimens at each cutoff evaluated. • Of the single analytes, NOC identified the largest • Monitoring HC and HM only would decrease the number of specimens at each cutoff evaluated. number of specimens identified. Mean Detection Times of Oxymorphone by Cutoff (time to last positive)

Oxymorphone & NOM Detection Time

50 50.7 100 47.5 150 41.5 300 29.2 500 26 Oxymorphone NOM 1,000 17 2,000 8.5

Cutoff Concentration,Cutoff ng/mL 0 102030405060 Hours Mean Detection Times of Hydromorphone by Cutoff (time to last positive)

Hydromorphone Detection Times 50 52.3 100 52.3 150 51.0 ng/mL 300 47.0 500 36.7 1000 23.7 Cutoff, 2000 11.3 0204060Hours Oxycodone: Cutoff Evaluation by Analyte Percentage of Specimens Containing Analytes at or above Cutoff 31

Confirmatory Analyte(s)

Cutoff (ng/mL) OC OM NOC OC/OM OM/NOC OC/OM/NOC 50 81 87 97 98 98 100

100 77 93 98 97 100 100

150 75 95 98 96 100 100

300 74 85 100 92 100 100

500 60 61 97 70 100 100

1000 38 25 100 42 100 100

2000 35 30 100 35 100 100

• Monitoring OC and OM identified 98% of specimens at a cutoff of 50 ng/mL, 97% at 100 ng/mL, 96% at 150 ng/mL, and 92% at 300 ng/mL. • Higher percentages of specimens were identified by monitoring NOC in addition to OC and OM at cutoffs greater than 300 ng/mL. Results Overview: Oxycodone and Hydrocodone 32

Oxycodone • All BL specimens (immediately before OC dosing) were negative (less than LOQ) for all analytes. • OC was detected in specimens from the first collection period (0–2 h) for 11 of the 12 subjects. • The initial appearance of OC was frequently accompanied by NOC in the same specimen. • NOC was generally the most abundant metabolite and was frequently present in higher concentrations than OC.

Hydrocodone • HC and NHC were initially detected in the majority of subjects’ specimens within 2 hours of drug administration. HC was most frequently detected in combination with NHC. • NHC was the most abundant metabolite and was often present in higher concentration than HC.

32 Solution

Reschedule Educate Monitor (REM) Polydrug

34 • The evidence shows that over 90% of so‐called opioid overdose deaths are the result of polydrug poisoning. • mixing heroin with another drug such as alcohol, benzodiazepines, cocaine, or opioid painkillers is extremely deadly • In reality, twice as many opioid poisoning deaths in the US involve painkillers as involve heroin. And let me reiterate that whether heroin or a painkiller is involved, over 90% of these deaths involve drug mixing. Figure 1 shows the CDC data for drug poisoning deaths in the US in 2013. • The safest heroin is 100% pure prescription heroin which can be obtained at heroin maintenance programs in Europe. When the purity is known then the safe dosage can be calculated. Uncertainty in heroin purity in the US is a contributing factor to opioid poisoning deaths which could be eliminated by prescription heroin as is done in sane countries. • Source: http://www.rehabs.com/pro‐talk‐articles/how‐the‐media‐is‐fueling‐the‐so‐called‐opioid‐overdose‐epidemic/ CURES

• Deaths from opioid overdose in California have climbed steadily over the last decade; nationally, opioid painkillers accounted for more than 70% of the 23,000 pharmaceutical deaths in 2013. • Solution ‐ implementing CURES, a database which is used to fight prescription drug misuse in the State of California. • State Sen. Richard Lara’ bill would finally require doctors to do prescription pill checks before prescribing more pills • The Cures database addresses only part of the problem, according to a 2013 federal survey, two thirds of the people abusing pharmaceuticals had not been prescribed the drugs • Cures can help physicians and pharmacies identify those who are pill shopping from doctor to doctor, while helping states track down doctors who are overprescribing narcotics • Only about 10 % of those who can prescribe these drugs have even signed up to use CURES • The California Medical Assn., has resisted any mandate on its members to consult database, arguing that the Legislature shouldn’t meddle in the practice of medicine • Lara’s bill –simply holds doctors and other prescribers responsible for checking Cures when the potential for pill shopping is at its highest • The database would also help doctors protect themselves from the habit of resourceful drug misuse Retrieved from: http://www.latimes.com/opinion/editorials/la‐ed‐pills‐database‐20150508‐story.html CURES

• Controlled Substance Utilization, Review and Evaluation System (CURES) and Controlled Substance Prescriptions

• CURES IS CALIFORNIA'S PRESCRIPTION DRUG MONITORING PROGRAM (CALIFORNIA HEALTH & SAFETY CODE 11165)

• Note: Effective July 1, 2016, all California‐licensed pharmacists and all California‐licensed prescribers with DEA numbers must be registered to access CURES. To register, please visit https://pmp.doj.ca.gov/pmpreg/.

Source: http://www.pharmacy.ca.gov/licensing/cures.shtml 37 Thank You Division of Workplace Programs

Ron R. Flegel, BS., BSMT (ASCP), M.S.

Please Visit our Website http://workplace.samhsa.gov/

37 Are There Any Questions?