DOSE RESPONSE ASSESSMENT (threshold effects)

BASIC PRINCIPLES a WHAT IS A THRESHOLD? IS A THRESHOLD? a CONSIDERATION OF TOXIC EFFECTS AT VARIOUS DOSE LEVELS a EFFECTS: GRADED AND MEASUREDGRADED AND MEASURED RESPONSE: QUANTAL AND COUNTEDQUANTAL AND COUNTED a SHAPE OF THE DOSE OF THE DOSERESPONSE CURVE CURVE a ESSENTIALITY CONSIDERATIONS a NO(A)EL DERIVATION vs. PROBABILISTIC APPROACHES aRisk assessment requires an evaluation of the full range of the doseresponse relationship aPrediction of risk at a given exposure aSafety assessment: Definition of a l l f b l hi h i k fevel of exposure below which risk of adverse effects is negligible aADITDI; RfDRfC (USEPA) DERIVATION OF THE ADITDI aCHARACTERIZATION OF CRITICAL EFFECT AND PIVOTAL STUDY aDETERMINATION OF THE NO OBSERVED(ADVERSE)EFFECT LEVEL (NOAEL) OR LO(A)EL aAPPLICATION OF SAFETYUNCERTAINTY FACTORS aCONSIDERATION OF 1 POINT ON DOSERESPONSE CURVE ONLYRESPONSE CURVE ONLY

DOSE RESPONSE RESPONSE

ASSESSMENT

(Threshold Effects)

Leonard Ritter Maged Younes/WHO

BASIC PRINCIPLES

WHAT IS A THRESHOLD?

CONSIDERATION OF TOXIC EFFECTS AT

VARIOUS DOSE LEVELS

EFFECTS: GRADED AND MEASURED

RESPONSE:

RESPONSE: QUANTAL AND COUNTED QUANTAL AND COUNTED

SHAPE OF THE DOSE

SHAPE OF THE DOSE RESPONSE CURVE RESPONSE CURVE

SHAPE OF THE DOSE

SHAPE OF THE DOSE RESPONSE CURVE RESPONSE CURVE

ESSENTIALITY CONSIDERATIONS

NO(A)EL DERIVATION vs PROBABILISTIC

APPROACHES

Basic Principles

Risk assessment requires an

evaluation of the full range of the

dose

dose response relationship response relationship

Prediction of risk at a given exposure

Safety assessment: Definition of a

level of exposure below which risk of

adverse effects is negligible

ADI/TDI; RfD/RfC (US

DERIVATION OF THE

ADI/TDI

CHARACTERIZATION OF CRITICAL

EFFECT AND PIVOTAL STUDY

DETERMINATION OF THE NO

DETERMINATION OF THE

NO OBSERVED

OBSERVED (ADVERSE) (ADVERSE) EFFECT EFFECT

LEVEL (NO[A]EL) OR LO(A)EL

APPLICATION OF

SAFETY/UNCERTAINTY FACTORS

CONSIDERATION OF 1 POINT ON

DOSE

DOSE RESPONSE CURVE ONLY RESPONSE CURVE ONLY

ACCURACY ISSUES

Dose spacing

Information at different exposure

levels

Slope of the dose-response curve

Shape of the dose-response curve:

linear, J-shaped, U-shaped

ADI = NOAEL

UNCERT FACTOR

Precision depends on the

adequacy of the methods

used Guidelines for

protocols and procedures

ensure reliable data

The value used depends on the adequacy of the safety database and whether the critical effect has been studied in humans

Assessment

Factors

Extrapolation Factors

Inter-species

Inhalation 3

LOAEL to

3 10 Factors

Database Factors

LOAEL to

Sub-chronic

Missing studies

Temporary ADI 2

3 or 10 TDI

Teratogenicity 5 or 10 Non-genotoxic

Risk

Management

Factors

Sub-group and Severity Factors

SPECIES DIFFERENCES

HUMAN VARIABILITY The use of uncertainty or safety factors

KINETICS DYNAMICS KINETICS DYNAMICS

Uncertainty or safety factors are used to extrapolate from a group of

test animals to an average human and from average humans to

potentially sensitive sub-populations Up to an additional 10x to protect children

US EPA Guidelines for Uncertainty

Factors

UNCERTAINTY FACTORS

COMMONLY USED

INTERHUMAN / INTRASPECIES

EXPERIMENTAL ANIMAL TO HUMAN

SUBCHRONIC TO CHRONIC

LO(A)EL TO NO(A)EL

INCOMPLETE DATABASE

FOR UNCERTAINTIES IN STUDY DESIGN)

ACCEPTABLE vs TOLERABLE

INTAKES

PRINCIPLES FOR DERIVATION ARE THE

PRINCIPLES FOR DERIVATION ARE THE

SAME

ADI: USED FOR COMPOUNDS

INTRODUCED INTENTIONALLY TO FOOD,

e.g FOOD ADDITIVES ACCEPTABLE IN

VIEW OF BENEFICIAL AFFECTS

TD(W)I: USED FOR COMPOUNDS

TOLERATED IF NOT AVOIDABLE, e.g

CONTAMINATS

ADI/TDI Exceeders

ABOVE “ADi” DOSE

REGION OF ADVERSE

"SAFE"

FOG OF UNCERTAINTY

"NOT SAFE"

REGION

OF NO

EFFECTS

ADVERSE EFFECTS

INCREASING DOSE

“ADI” DOSE

MATHEMATICAL MODELS

WHY?

⌧

⌧More accurate derivation of “NOEL/LOEL” More accurate derivation of “NOEL/LOEL”

⌧

⌧Effects at various exposure levels Effects at various exposure levels

BENCHMARK DOSE

BIOLOGICALLY BASED DOSE

BIOLOGICALLY BASED

DOSE RESPONSE MODELS (BBDR)

⌧

⌧Pharmacokinetics Pharmacokinetics

⌧

⌧Mechanisms of action Mechanisms of action

PHYSIOLOGICALLY BASED

PHARMACOKINETIC MODELS (PBPK)

BENCHMARK DOSE

What is a Benchmark Dose (BMD)? at s a e c a ose ( )

The statistical lower confidence limit on the dose

producing a predetermined level of change in an adverse

effect compared with the response in untreated animals.

Or in plain(er?) English

The 95% lower confidence on the dose that causes, for

example, a 10% increase in the number of animals

developing fatty liver compared with untreated animals.

A BMD is calculated by fitting a

mathematical dose-response model to

data.

Advantages of BMD

Approach

Not limited to doses tested experimentally; less p y;

dependent on dose spacing.

Takes into account the shape of the

dose-response curve.

Provides flexibility in determining biologically

significant rates (e.g., a 10% increase may be

appropriate for one response while a 1%

appropriate for one response while a 1%

increase is appropriate for a different response)

Gives incentive to conduct better studies because

more rigorous studies result in tighter

uncertainty bands, and thus, higher BMDs.

Disadvantages to the BMD

Possible to introduce error in model prediction of p

BMD if the models are used to extrapolate to low

doses without incorporating information on

mechanism.

Quantal data (e.g., tumor incidence or number of

pups with a deformity) and continuous data (e.g.,

changes in body/organ weight or serum enzyme

levels) are handled differently.

Unless the raw data from a study are available,

the ability to estimate a BMD may be limited by

the format of the data presented.

Choosing the Appropriate

Model

Calculation of a BMD does not involve extrapolation

far beyond the range of experimental data: not highly

dependent on the model used.

Models for quantal data estimate the probability of

response for each dose level Probability is assumed

to increase as dose increases.

Models for continuous data estimate the mean

response for each dose level compared to control

response for each dose level compared to control

Mean response can either increase or decrease as a

function of dose.

Goodness-of-fit analysis required to determine if a

model adequately describes the data, thus giving an

PURPOSE: TO COMPUTE THE

CONCENTRATION TIME

CONCENTRATION TIME COURSE OF COURSE OF

COMPOUND (& METABOLITES) IN

DIFFERENT COMPARTMENTS (ESPECIALLY

TARGET ORGAN)

CONSIST OF SEVERAL MASS BALANCE,

DIFFERENTIAL EQUATIONS AROUND

EACH COMPARTMENT DESCRIBING

BLOOD FLOW PERMEABILITY

EXTERNAL DOSE TOXIC RESPONSE

ABSORBED DOSE

PB-PK MODEL INCLUDING LOCAL METABOLIC BIOACTIVATION

CONCENTRATIONS IN

GENERAL CIRCULATION

CONCENTRATIONS

IN TARGET TISSUE

CLEARANCE

DISTRIBUTION TO NON-TARGET TISSUES

INTERACTION WITH

INTRACELLULAR CHANGES

-+

ANY LOCAL BIOACTIVATION

- not reflected by plasma

kinetic measurements CYTOPROTECTIVE MECHANISMS

INTERACTION WITH INTRACELLULAR TARGET(s)

-PBPK (2)

DATA NEEDED:

DATA NEEDED:

⌧

⌧PHYSIOLOGICAL INFORMATION PHYSIOLOGICAL INFORMATION

⌧

⌧PARTITION COEFFICIENTS PARTITION COEFFICIENTS

⌧

⌧METABOLIC RATES METABOLIC RATES

PROVIDES POSSIBILITY TO

ACCOUNT FOR BIOLOGICAL

ACCOUNT FOR BIOLOGICAL

PROCESSES

USE OF PBPK MODELS

STRENGTHS

Estimates of target organ dose in humans can be

based on in vitro data, without the need for

administration to humans

Species differences in blood flow to the target

organ can be modelled to reflect Cmax

Inclusion of organ blood flows will prevent

Inclusion of organ blood flows will prevent

misleading conclusions based on Km and Vmax

alone

USE OF PBPK MODELS (2)

WEAKNESSES

Estimates are based on in vitro data, from animals

and humans, which are frequently of questionable

provenance

Overall clearance estimates assume the tissue

distribution of metabolising activity, and routes of

elimination

Many physiological processes for humans are

based on the simple scaling of data for animals

Blood:tissue affinities for humans are usually

based on experimental data for animals, or octanol:

PROBABILISTIC

APPROACHES

Distribution of response and

Distribution of response and

exposure

Consider variability

May be different for different groups

of population

Monte Carlo Approaches

Probabilistic approaches to deriving

ADI/TDI (or RfD/RfC)

The distribution of the NOAEL may likely have

Probabilistic ADI/TDI

an average tendency

NOAEL ADI =

UF x MF

The distribution of the UF and MF will likely

have a skewed tendency where the chosen

Probabilistic ADI/TDI

ADI/TDI =

RfD/RfC Method Lewis et al (1990)

The resulting distribution of these subthreshold

estimates will likely be skewed, where the

calculated value is towards the conservative

end