Morphine Milligram Equivalents (MMEs)

Current Applications and Knowledge Gaps, Research Opportunities, and Future

Directions

June 7-8, 2021

Grace Chai, PharmD

Associate Director for Special Initiatives

Office of Surveillance and Epidemiology

CDER/FDA

What is an MME?

• Definition: The amount of milligrams of morphine an

opioid dose is equal to when prescribed. Calculating

MME

accounts for differences in opioid drug type and

strength.

www.fda.gov

https://www.cdc.gov/drugoverdose/opioids/terms.html. Accessed

4/28/2021

MMEs are increasingly being used to indicate abuse and overdose potential

and to set thresholds for prescribing and dispensing of opioid analgesics.

• To bring stakeholders together to discuss

the scientific basis of morphine milligram

equivalents (MMEs), which are widely used

as metrics in multiple areas throughout the

healthcare system

Purpose

• Describe the science underlying MMEs

• Describe uncertainties and complexities in

calculating/applying MMEs as:

– Opioid Conversion Factors

– Risk predictors for overdose/nonmedical use/opioid use disorder

• Discuss a research agenda to fill knowledge gaps to refine

and improve the use of MMEs across applications

Goals

Scientific Workshop

• Patients and Public Health

– The expanded and varied uses of MMEs and the

impact on patients reinforce the need to

understand and build the science of MMEs

• Focus is on describing and enhancing the science

– Discussion of specific regulatory actions, policies,

and applications of MMEs is not the focus of this

meeting

– Our goal is to facilitate a productive discussion to

better understand and advance the science

Opioid Conversion Factors

• Based on small clinical studies in limited populations

– Clinical Practice: Originally intended to assist clinicians in

determining initial dose when converting an individual patient’s

opioid therapy

• Resources (e.g., tables, online calculators) contain

different conversion factors

• Patient and drug characteristics

– Ex. Opioid tolerance, pharmacogenetics

– Ex. Partial agonists (buprenorphine), novel drugs (tapentadol)

MMEs and Risk

• Epidemiologic studies show convincing association between

increasing daily dose of opioid analgesics and increasing risk of

overdose

– Studies have generally used daily MME threshold categories to assess

risk (e.g., > 50 MME/day, > 90 MME/day)

but stated no clear threshold

• Studies have also examined the association between daily dose

and adverse outcomes (e.g., opioid use disorder/addiction,

misuse/abuse), but causality is unclear

Bohnert et al. Med Care 2016; 54(5):435-441

Disparate MME

Conversion Aids

(e.g., tables, e-

calculators)

State & Federal

Policy & Law

(e.g., Rx Limits)

Underlying

Data

Quality

Conversion

Factors

Professional

Societies /

Associations

Developed in collaboration with FDA OPSA – Blake Bannister

and Graham Thompson

Note: This model focuses in on the factors and relationships

most pertinent to discussion on MMEs at the Scientific

Workshop. It does not capture every factor or relationship

associated with MMEs.

Historical

design of

opioid trials

• Patient population &

size

• Intent of trial

Payer Coverage &

Reimbursement

Decisions (Private

& Govt)

• Pharmacogenetic variability

• Drug interactions

• Lack of universal morphine

equivalence

• Specific opioids (e.g., partial

agonists)

• Differing calculations

Use of MME

Conversion in

Prescribing &

Policy

Other

prescribing and

policy factors

New

research

on MMEs

Healthcare

Provider/System

Prescribing

Pharmacy

Dispensing

Scientific Basis for MMEs

Use by Stakeholders

Fed. Agency

Comms about

MME

Conversions

Access to

opioid

analgesics

E.g., prescribing and

dispensing:

• Initiating new

opioid therapy

• Changing therapy

• Tapering therapy

• Denying New

therapy

Health outcomes from

adverse events

related to opioid

analgesic use (e.g., OD,

OUD)

Health outcomes

related to pain

management (e.g.,

QOL, undertreated

pain)

Public’s perception of

opioid analgesics

Potential Outcomes

Public health

outcomes (e.g., illicit

use, suicide,

alcoholism,

overprescribing)

MME Influence Diagram

Expanding Scope of Influence

Industry &

Academic

Research (using

MMEs)

Conclusion

• Given the expanded and varied uses of MMEs, understanding

and building upon the science of MMEs is needed to refine

and improve the scientific basis for MME applications

– Scientific Workshop goals are to understand and seek to

improve the scientific basis of MMEs

– Inform a future research agenda

Meeting Materials

• Available Online

– Meeting agenda

– Speaker bios and disclosures

– Panel discussion questions

Agenda: Day 1

• Impact of Science on Real Life Experiences: Penney Cowan

• Overview of Current Applications and Uses of MMEs: Corinne Woods

• Calculating Conversations in Opioid Conversions: Mary Lynn McPherson

• Individual Patient & Medication Factors that Invalidate Morphine Milligram Equivalents: Jeffrey

Fudin

• Opioid Prescribing and the Opioid Safety Initiative in the Veterans Health Administration:

Friedhelm Sandbrink, Thomas Emmendorfer, Fran Cunningham

• Clarifying Questions

Lunch

• Overview of the Opioid NDC and MME Analytical File Compiled by CDC: Kun Zhang

• MHRA-UK work in development of MME tables: Justin Pittaway-Hay

• Improving information for opioids prescribers on the safest possible effective dose of morphine

or equivalent: a UK perspective: Maria Luisa Molinari

• Clarifying Questions

• Public Comment Session

Agenda: Day 2

• Welcome and Recap of Day 1: Grace Chai

• Opioid Conversion Information in Approved Labeling: Mary Therese O’Donnell

• Nonclinical Pharmacology and Toxicology Considerations Regarding Opioid Comparisons and Risk

Assessments (Basic Opioid Pharmacology 101): Dan Mellon and Donna Volpe

• MME calculations and Abuse liability considerations: Chad Reissig

• Clarifying Questions

• Relative potency of oral and intravenous oxymorphone compared to other µ opioid agonists in

humans: Shanna Babalonis

• Opioid Potency: Pharmacological and Nonpharmacological Factors: Sandra Comer

• Inches, Centimeters, and Yards: Overlooked Definition Choices Inhibit Interpretation of Morphine

Equivalence: Nabarun Dasgupta

• Clarifying Questions

Lunch

• Panel Discussions (FDA Co-Moderators: Judy Staffa and Jennifer Nadel)

Panel Discussion Questions

1) Discuss any potential knowledge gaps in the science underlying MMEs across

various applications.

a. Drug Considerations

b. Patient-Level

i. analgesia/opioid rotation/conversion

ii. risk predictor

iii. other

c. Population-Level/Public Health

i. risk predictor

ii. research

iii. other

2) Discuss types of studies and designs that may be helpful to address

knowledge gaps in the science across various applications.

3) Discuss additional factors that should be considered to inform/supplement

the use of MMEs, at a patient-level and/or population-level across the

various applications.

Panel Discussion Questions (cont’d)

4) Given the availability and variability of multiple MME conversion tables, analytical files, online

calculators, references, and tools, discuss the benefits and limitations of a common MME

reference table(s) (gold-standard) vs. multiple reference tables.

a. Discuss if a gold-standard reference table(s) is necessary

b. Discuss for what purpose(s) is it possible/feasible

5) Discuss calculation of MMEs (MME per day, etc.).

a. What are the challenges and knowledge gaps in the calculation of MMEs for patient care decisions?

b. Discuss whether different MME conversion factors or algorithm definitions are needed for certain

patient populations (e.g., opioid-naïve patients, patients with current opioid use), for use at the patient-

level or aggregate/population level.

6) What are other gaps in the science that haven’t been discussed; where and how can research

enhance/refine/develop knowledge about MMEs to support the varying applications and uses?

a. How should novel opioids and/or analgesics be considered in this paradigm?

7) Based on previous discussions, prioritize the research to fill the identified gaps.