Integrating the Science of Opioids Into Regulated Testing

Presented byRon 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 MEDICINESeptember 24, 2017

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Problem

• 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

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Nora D. Volkow, M.D.

Director of National Institute on Drug Abuse

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Drug Abuse Warning Network (DAWN)

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

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Research Studies

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Oxycodone and Hydrocodone: Kinetic Relationships of Whole Blood to Oral FluidEdward 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, TN; 4Substance Abuse and Mental Health Services Administration, Division of Workplace Programs, Rockville, MD; 5RTI International, Research Triangle Park, NC

Prescription Opioid Abuse. II. Profiling Hydrocodone and Metabolites in Urine

Charles P. LoDico*1, Ronald R. Flegel1, 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, Baltimore, MD, USA

Prescription Opioids. I. Profiling Oxycodone and Metabolites in Urine

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, Baltimore, MD, USADisposition of Oxycodone and Hydrocodone in

Oral FluidRebecca 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 University, Department of Pathology, Immunology and Microbiology Nashville, TN, USA; 3RTI

International, Research Triangle Park, NC, USA; 4Substance Abuse and Mental Health Services Administration, Division of Workplace Programs, Rockville, MD, USA; 5Johns

Hopkins School of Medicine, Baltimore, MD, USA

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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

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Study Dosing Information

• 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

NOH

O OO

CH3

CH3

NHOH

O OOCH3

NHOH

OH OO

NOH

OH OO

CH3

Oxycodone (OC) Noroxycodone (NOC)

Oxymorphone (OM) Noroxymorphone (NOM)

Review of Oxycodone Metabolism (Urine, Oral Fluid and Blood)

CYP3A4

CYP2D6

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NH

O OOCH3

N

O OO

CH3

CH3

N

OH OO

CH3

Hydrocodone (HC) Norhydrocodone (NHC)

Hydromorphone (HM) Dihydrocodeine (DHC)

NH

O OHO

CH3

CH3

Review of Hydrocodone Metabolism(Urine, Blood, & Oral Fluid)

CYP3A4

CYP2D6 6-Ketoreductase

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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

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Note: Canada’s Legal Status 

• Oxycodone ‐ Schedule I

• Oxymorphone ‐ Schedule I

• Hydromorphone ‐ Schedule I

• Hydrocodone ‐ Schedule I

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Blood and Oral Fluid Results

Oxycodone and Hydrocodone:Comparison of Oral Fluid to Blood

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Noroxycodone & NorhydrocodoneComparison of Oral Fluid to Blood

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Cmax, OF/BL Ratios, Correlations16

OxycodoneOC 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 NAHydrocodone

HC NHC HM DHCOF 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 Correlation17

Hydrocodone Correlation18

Blood and Oral Fluid Kinetics19

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)

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Summary of Blood and Oral Fluid

• 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

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Urine Results

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Mean Excretion of OC and Metabolites & HC and Metabolites in Urine (Hydrolyzed)

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0

500

1000

1500

2000

2500

3000

3500

1 3 5 7 9 11 13 19 26 30 34 50

ng/m

LHours (Collection Period Midpoints)

HC

HM

NHC

DHC

0

500

1000

1500

2000

2500

3000

3500

1 3 5 7 9 11 13 19 26 30 34 50

ng/m

L

Hours (Collection Period Midpoints)

Total OC, ng/mL

Total OM, ng/mL

Total NOC, ng/mL

Total NOM,ng/mL

• OC and NOC generally became detectable in the 0-2 h collection period. OM generally became detectable in the 2-4 h collection period.

• OC and its metabolite concentrations usually peaked within 3–9 h, then declined.

• After 24 hours, 18 specimens contained detectable concentrations of 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.

• Total NOM concentrations were slightly higher than free concentrations.

• Total HM and DHC generally became detectable in the 2-4 h collection period.

• HC and metabolites’ concentrations peaked within 3-9 h post-dosing, then declined.

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0

1000

2000

3000

4000

5000

6000

1 3 5 7 9 11 13 19 26 30 34

ng/m

L

Hours (Midpoint)

Variability of HC Excretionin Urine (Hydrolyzed)

HC was present in 9 of 12 subjects’ specimens from the first collection period (0-2 h).

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Oxycodone: Mean Detection TimesTotal OC, OM, NOC and NOM in Urine (Time to last Positive by Cutoff)

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3.0

7.3

15.5

19.3

24.7

27.7

29.3

2.3

8.3

20.8

26.7

33.0

37.0

41.3

8.8

19.8

24.0

28.3

32.7

36.0

39.3

0.7

1.8

11.7

20.5

28.7

30.7

31.8

0 10 20 30 40 50

2000

1000

500

300

150

100

50

Hours

Cutoff, ng/mL

OCOMNOCNOM

• 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.

3.0

7.3

15.5

19.3

24.7

27.7

29.3

2.3

8.3

20.8

26.7

33.0

37.0

41.3

8.8

19.8

24.0

28.3

32.7

36.0

39.3

0 10 20 30 40 50

2000

1000

500

300

150

100

50

HoursC

utof

f, ng

/mL

OCOMNOC

0

15

30

45

0 500 1000 1500 2000

OCOMNOC

Oxycodone/Metabolite(s) Detection Times(Time to Last Positive)

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Hydrocodone: Mean Detection TimesTotal HC, HM, NHC and DHC in Urine, Time to last Positive by Cutoff

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2.8

4.0

9.0

12.2

18.2

20.5

27.7

0.3

2.0

5.2

12.0

14.3

25.5

4.5

9.3

17.3

21.7

29.0

33.0

39.7

1.3

4.8

7.3

16.3

0 10 20 30 40 50

2000

1000

500

300

150

100

50

Hours

Cutoff, ng/mL

HC

HM

NHC

DHC

• 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.

2.8

4.0

9.0

12.2

18.2

20.5

27.7

0.0

0.3

2.0

5.2

12.0

14.3

25.5

4.5

9.3

17.3

21.7

29.0

33.0

39.7

0.0

0.0

0.0

1.3

4.8

7.3

16.3

0 10 20 30 40 50

2000

1000

500

300

150

100

50

Hours

Cut

off,

ng/m

L

HCHMNHCDHC

Hydrocodone Detection Times(Time to Last Positive)

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0

15

30

45

0 500 1000 1500 2000

HCHMNHCDHC

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Cutoff Evaluation by Analyte* Number of Specimens with Individual/Combined Analytes at or above Cutoff

0

20

40

60

80

100

120

140

50 100 150 300 500 1000 2000

Num

ber o

f Spe

cimen

s ≥ Cutoff

Cutoff Concentration

OC

OM

NOC

OC/ OM

OM/NOC

OC/OM/NOC

0

20

40

60

80

100

120

140

50 100 150 300 500 1000 2000Num

ber o

f Spe

cimen

s ≥ Cutoff

Cutoff Concentration

HC

HM

NHC

DHC

HC/HM

• The combination of OC, OM, and NOC identified the largest number of specimens at each cutoff evaluated.

• Of the single analytes, NOC identified the largest number of specimens at each cutoff evaluated.

*Total analyte concentrations after hydrolysis

• Of the single analytes, NHC identified the largest number of specimens at each cutoff evaluated.

• Monitoring HC and HM only would decrease the number of specimens identified.

Mean Detection Timesof Oxymorphone by Cutoff

(time to last positive)

8.517

2629.2

41.547.5

50.7

0 10 20 30 40 50 60

2,0001,000

50030015010050

Hours

Cut

off C

once

ntra

tion,

ng/

mL

Oxymorphone & NOM Detection Time

Oxymorphone NOM

Mean Detection Times of Hydromorphone by Cutoff

(time to last positive)

11.323.7

36.747.0

51.052.352.3

0 20 40 60

2000100050030015010050

Hours

Cutoff, ng/mL

Hydromorphone Detection Times

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Oxycodone: Cutoff Evaluation by AnalytePercentage of Specimens Containing Analytes at or above Cutoff

Cutoff (ng/mL)

Confirmatory Analyte(s)

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.

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Results Overview:Oxycodone and Hydrocodone

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. 

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Solution

Reschedule Educate Monitor (REM)

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Polydrug

• 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/

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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

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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

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Thank YouDivision of Workplace Programs

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

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

Are There Any Questions?