Consultant, Global Health Integrated Development/Quantitative Sciences

Bill and Melinda Gates Foundation

Professor of Medicine and of Molecular Pharmacology (Emeritus) Stanford University

Adjunct Professor of Bioengineering and Therapeutic Sciences

UCSF School of Pharmacy

Terrence F. Blaschke, M.D.

50% Adherence is Enough With Modern ARVs, Right?

• For the past 3 years I have been a consultant to the Bill and Melinda Gates

Foundation, involved in adherence studies overseen by Bruce Thomas of

The Arcady Group, a grantee of the Bill and Melinda Gates Foundation

• I have worked with the AARDEX Group and consulted for Proteus Digital

Health, both involved in developing and marketing adherence

technologies

• For the past 13 years I have been on the Board of Directors of DURECT

Corporation, a specialty pharmaceutical company involved in the

development of drug delivery platform technologies

Disclosures

Presentation outline:

• Review adherence definitions (“taxonomy”)• Discuss factors that impact dosing regimens• Define “Forgiveness” in quantitative terms• An analysis of dosing regimens for HIV drugs with short half-lives

• Example: dolutegravir

• Examples of dosing and dosing regimens, QD and BID• Importance of patterns, not percentages of adherence• TB treatment as an example• Conclusions

50% Adherence is Enough With Modern ARVs, Right?

NO!DISCLAIMER!!

I SUPPORT THE DEVELOPMENT AND VALUE OF LONG-ACTING DRUGS AND/OR FORMULATIONS!

THIS PRESENTATION WILL FOCUS ON THE TOPIC OF “FORGIVENESS”

Medication Adherence: TaxonomyThe process by which patients take their medications as prescribed

Time1. Initiation 2.Implement 3. Persist

25 % of patients do not initiate a new prescription

Daily, 15% of patientsdo not implement as

prescribed

During the first year, 40% of patients have discontinued

treatment

A new taxonomy for describing and defining adherence to medications.

Vrijens B et al., Br J Clin Pharmacol. 2012 May;73(5):691-705

Factors in designing a dosing regimen:• Drug potency• Drug half-life (T½)• Therapeutic Index

FORGIVENESS

Definition of “Forgiveness” (1)

Forgiveness (F) can be defined as “how long drug action continues at therapeutically effective concentrations after a last-taken dose”

or The post-dose duration of effective action minus

its recommended dosing interval.

“Forgiveness” (2)

Mathematically, forgiveness is the difference between the drug’s post-dose duration of action (D) and the prescribed dosing interval (I), or:

F = D – I (units: Time)

It can also be expressed as a ratio of the duration of action over the dosing interval:

D/I

“Forgiveness” (3)

• Forgiveness is dependent on the drug dose and the drug’s half-life (T½)

• One approach to extend forgiveness is dose-escalation, but that approach is often limited by dose-dependent toxicity. The impact of early discontinuation, however, is not offset by a few days of forgiveness.

Persistence: overall, 40% of patients with HIV will have discontinuedtreatment by month 12

Blaschke, Osterberg, Vrijens, Urquhart, Annual Review of Pharmacology and Toxicology, 2012.

(Data obtained from electronic monitoring (EM) of dosing)

Time to treatment discontinuation (days)

% o

f p

ati

en

ts p

ers

isti

ng

wit

hth

e t

rea

tme

nt

0 100 200 300

0

20

40

60

80

100

Osteoporosis

Hyperlipidemia

HIV

Diabetes

Breast cancer

Hypertension

Depression

N= 16,907pts – 95 Clinical Trials

Discontinuation at month12:• HIV: 40%

• Hyperlipidemia: 30%• Diabetes: 40%• Hypertension: 50%

DOSING REGIMENS AND FORGIVENESS

For drugs with relatively short half-lives, is once-daily dosing better than twice-daily?

Let’s look at an example of the dosing regimen for a patient with HIVstarting on dolutegravir

TIVICAY (dolutegravir tablets), for oral use

HIGHLIGHTS OF PRESCRIBING INFORMATION

Elimination:

Dolutegravir has a terminal half-life of approximately 14 hours and an apparent clearance

(CL/F) of 1.0 L per hour based on population pharmacokinetic analyses.

HIGHLIGHTS OF PRESCRIBING INFORMATION

Mean plasma concentrations of DTG (A) plotted on a semilogarithmic scale

Rashmi Mehta et al. Antimicrob. Agents Chemother. 2018

Mean plasma concentrations of DTG (A, 50 mg) plotted on a semilogarithmic scale by time after dosing. Insets show expanded

views of the shaded areas, which represent the first 24 h of PK sampling. The first concentration in each plot corresponds to the PK sampling at 0.5 h after dosing. Dotted gray lines denote the lower limits of quantification

Examples of dosing and dosing regimens, QD and BID

Possible consequences when patients vary their dosing intervalOccasional toxicity

Periodic loss of

effectiveness &

emergence of drug

resistance (HIV)

Blaschke, Osterberg, Vrijens, Urquhart. Ann Rev of Pharmacol and Toxicol 2012. 52:275-301.

Understanding Treatment Forgiveness

“Do Patients miss more doses when on a BID regimen” YES!...but…

Per

cen

t o

f p

atie

nts

tak

ing

at le

ast

the

pre

scri

bed

nu

mb

er o

f d

ose

s

Time elapsed since the start of monitoring (Days

94%

84%

QD

BID

Dosing times(hours)

Co

nce

ntr

atio

n(n

g/m

l)

450 500 550 600

02

00

04

00

06

00

08

00

0

QDBID

PK considerations for QD vs BID dosing:

Slide courtesy of Bernard Vrijens, AARDEX and Pharmionic Research Centre, Visé, Belgium

Pharmacokinetic projections of representative patients during a QD or BID dosing regimen assuming that the patients

maintain pharmacokinetic steady state. The y-axis shows the concentration of PI as a function of time.

The consequences of missing one QD or three BID doses are illustrated.

MEC

How frequent are those errors?

73% QD

Slide courtesy of Bernard Vrijens, AARDEX and Pharmionic Research Centre, Visé, Belgium

The cumulative percentage of QD and BID patients with dosing intervals greater than 36 h

54% BID

Patterns of poor adherence

• As illustrated earlier, non-persistence in many chronic diseases is the cause of therapeutic failure

• This is relatively easy to detect using pharmacy refill data

• Using “% Adherence” as a measure obtained from pharmacy refill data is not helpful in deciding how to intervene and improve adherence

• More granular data are needed for appropriate counseling of patients

• Patterns of poor adherence are more difficult to detect, may go on for long periods of time, and frequently lead to polypharmacy and the potential for drug toxicity

Implementation Examples: Each patient took 90-90%% of prescribed doses during a 12-month period

www.iAdherence.org HIV

Implementation Examples: Each patient took 75% of prescribed doses during a 3-month period

A few clinical studies

Conclusions. Although subjects assigned to QD regimens had better adherence, overall treatment outcomes

were similar in the QD and BID arms. Subjects with HIV RNA levels 100,000 copies/mL had better SVR withBID regimens at 48 weeks, which suggests a possible advantage in this setting for more frequent dosing.

Example: Lack of forgiveness of protease inhibitors

▪ TB relapse following use of HRZE has been <5% in clinical trials

▪ However, data from a meta-analysis of recent TB trials highlight substantial differences in relapse rates based on medication adherence

▪ Patients taking HRZE with <90% adherence had 5.6 times increased hazard ratio for TB relapse

Rifampin-based regimens are not very “forgiving”

Graph courtesy of Rada Savic

Months

Pro

po

rtio

n o

f p

atie

nts

Poor adherence greatly increases relapse after treatment completion

28

Forgiveness in Tuberculosis Therapy Studies

Data source: A patient-level pooled analysis of treatment-

shortening regimens for drug-susceptible pulmonary tuberculosis.

Nat Med. 2018 Nov;24(11):1708-1715.

• Contrary to popular belief, for drugs with half-lives of less than 24 hours, at the same total daily dose BID dosing may provide better coverage than QD dosing.

• Dosing patterns matter!

• For drugs with narrow therapeutic windows and the potential for generating resistance consider generating dosing histories and providing adherence interventions

• This applies especially in HIV, TB and many other infectious diseases

▪ We DO need more potent drugs (for many diseases) with longer half-lives and a wide therapeutic index!

Conclusions:

QUESTIONS?