Development, Characterisation and Application

of PET radiotracers

02 May 2018

Nisha Kuzhuppilly Ramakrishnan

Molecular Imaging Chemistry Laboratory

Wolfson Brain Imaging Centre

Department of Clinical Neurosciences

Contents

• An introduction to PET

• Development of novel radiotracers

• Pharmacokinetic modelling of PET data

Positron Emission Tomography (PET)

• An imaging modality where molecules tagged

with radioactivity are

• tracked within the body

• used to produce quantitative three-

dimensional images

• used to measure biological functions

• Radiotracer / PET probe: A molecule labelled

with a positron emitting nuclide (e.g., 18F, 11C, 15O, 64Cu, 68Ga)

Su et al., The British Journal of Psychiatry, 2016

• Radiotracers are biomarkers

• that interact specifically with receptors, enzymes, transporters, misfolded

proteins etc.

• to image physiological, biochemical and pharmacological functions at a

molecular level in vivo.

Positron Emission Tomography (PET)

http://jens-maus.de/ftp/langner_mscthesis.pdf

Radiotracer development

• Target identification (TSPO, MAO-B, RAGE etc for neuroinflammation)

• Lead identification: literature, modification of drugs for the target, computational

modelling based on the structure of the target

• High affinity for target; e.g., for clear image visualization

• High selectivity for target; e.g., to reduce visualizing off-target processes

• Low non-specific binding; e.g., to decrease background

• Appropriate lipophilicity; e.g., to cross blood-brain-barrier

• Known metabolism; e.g., glucose

• Chemical synthesis of precursors and standards

• Radiosynthesis

• Reproducible radiolabelling methods; e.g., robust and fast

• High specific (molar) activity

Radiosynthesis

6

Radiopharmacology

Small Animal PETHotcells

Modules

Cyclotron

Radionuclides

Organic

chemistry laboratory

Novel small molecules

EvaluationRadiosynthesis

Radiotracer evaluation

• Preclinical evaluation

• In vitro: in cells, human or animal tissues

• Ex vivo: e.g. biodistribution studies

• In vivo: scanning in healthy animals and animal models of disease

• Entry and distribution in tissue of interest

• Kinetics in the region of interest (ROI) and in blood

• Formation of metabolites, especially radiometabolites

• Quantification of specific binding to the target using pharmacokinetic modelling

• Regulatory approval

• Translation to the clinic

• Clinical use

A pre-clinical study

Development of PET probes: A lengthy process

10

PRECLINICAL

WORK

Radioligand

development

Small animal

PET

CLINICAL

WORK

First in man

PET studies

CLINICAL

APPLICATIONS

Routine

diagnosis and

monitoring

therapy

Translation from

laboratory animals

to humans

Mathematics in PET

• Pharmacokinetics

• Pharmakon "drug" ; Kinetikos “movement”

• What the body does to the drug/tracer

• ADME:

• Absorption, Distribution, Metabolism,

Excretion

PET Data for kinetic modelling

• Time Activity Curve (TAC) from Regions of Interest (ROIs)

• From dynamically reconstructed PET scan image

• Input function

• Arterial input TAC

• Requires Arterial canulation

• Corrections

• Radioactive metabolites

• Plasma protein binding

• Image derived input: Reference region TAC

• Region devoid of specific binding

• Mathematical model is used to

describe observed data

• Model driven

• Compartmental models

• Data driven

• Graphical analysis

Modelling

Assumptions

• Tracer assumption: The PET measurement does not influence the physiology/

molecular interactions

• Low mass of the tracer

• Steady state: The measurement is performed when the physiology/ molecular

interactions is in a steady state

• Blood sugar during FDG scan

• Drug concentration during receptor occupancy study

• Instantaneous mixing: Each compartment is homogeneous with respect to

tracer concentration

Compartment models

• Kinetic compartments are not necessarily identical to

physical spaces

K1

CFk2

Brain

freePlasma

CP

k3

k4 CS

Brain

bound

Brain

Non-specific

k5 k6

CNS

Compartment models

Single tissue compartment model (1-TCM)

◦ Cerebral blood flow

K1

CTk2

BrainPlasma

CP

CT = CF + CNS + CS

What information do we get?

• Single tissue compartment model

• Volume of distribution VT

• Ratio of concentrations in tissue (CT) and plasma (CP)

K1

CTk2

BrainPlasma

CP

VT = K1/ k2

Compartment models

• Two-tissue compartment model

• Reversible

• Irreversible

K1

CFk2

Brain

freePlasma

CP

k3

k4CS

Brain

boundK1

CFk2

Brain

freePlasma

CP

k3

k4CS

Brain

bound

K1

k2

ND =

F +

NS

Plasmak3

k4S

What information do we get? : Receptor binding

K1

CFk2

Brain

freePlasma

CP

k3

k4CS

Brain

bound

• total Distribution Volume, VT = (K1/k2) * (1+k3/k4)

• Non-displaceable Distribution Volume, VND = K1/k2

• Non-displaceable Binding Potential, BPND = k3/k4

• Proportional to Bmax/Kd

• VT = VND (1+ BPND)

• Individual k values may be too variable

Receptor numbers & function

Flow & permeability

Simplification: Linearisation

• Patlak plot: Irreversible

• Logan plot: Reversible

http://www.bic.mni.mcgill.ca/~rgunn/PK_Course_2003/PKM_Manual_Web.pdf

Simplification: Reference tissue models

• Simplified Reference Tissue Model

• No displaceable component in the reference

region

• One tissue compartment kinetics in the target

and reference region

• Blood volume contribution to the tissues is

negligible

• Same VND in target and reference region

• Outcome measure BPND

Lammertsma and Hume, Neuroimage. 1996

Salinas et al., J Cereb Blood Flow Metab. 2015

SRTM in a NIMROD study

• [18F]AV-1451 to image misfolded protein Tau in AD, PSP, and healthy controls

Passamonti et al., BRAIN, 2017

Further information on PET kinetic modelling

• PET Pharmacokinetics course manuals: 2003 and 2007 versions

available online

• http://www.nrm2018.org/nrm-conference/pet-pharmacokinetics-course/

Current challenges

• Lead selection: Computational models

• Making PET truly non-invasive: avoiding blood sampling in the absence

of reference regions

Thank you!

WBIC - MICL WBIC - RPU

NIMROD Neuroimaging of Inflammation in Memory and Other Disorders

Bevan-Jones et al., BMJ Open. 2017