Abstract
The most useful application of PET imaging in CNS drug development is to measure occupancy of new drug
candidates at target binding sites (e.g., receptors, transporters, and enzymes). These target occupancy (TO)
studies -often starting in primates and progressing to Phase 1 in humans - are very helpful for in vivo dose-
finding, deciding whether to advance a candidate compound to more costly later phase trials, and optimizing
the design of later phase studies. Current State of the Art: A common and informative approach to analysis of
TO data is the “Lassen plot”. The Lassen plot yields two point estimates: a fractional occupancy of the target
by the drug (ODrug) and the nondisplaceable uptake of the tracer (VND). Assumptions underlying this popular
method are that (a) both measures are uniform across the whole brain and (b) the PET tracer binds to the
identical population of target sites as the candidate drug. Technology Gap: There are important cases in
which one or more assumption of the Lassen plot is violated. In such cases, (1) the outcome of the TO study
may be biased, (2) manual intervention may be required, (3) proper interpretation will depend on prior
knowledge of the spatial distribution of target subtypes, and in any case, (4) the standard method offers little to
no information on regional variation in ODrug.
Basic development in the lab: In our research group at Yale, we have developed an extension of the
standard Lassen plot that provides information about local variation in ODrug and VND. The outcomes of our
new “Lassen Plot Filter” (LPF) algorithm are voxel-by-voxel estimates of ODrug, VND and EC50 (i.e., `occupancy
images', `nondisplaceable uptake, and drug affinity, images'). We believe these novel images represent much
more informative outcomes of TO studies than standard measures for identifying precise locations of maximal
specific action of drugs. For example, when assumptions are violated, occupancy images will be less biased
than point estimates. The new images could serve as richer endpoints to drive go/no-go decisions on
candidate compounds based on drug action at specific brain locations of greatest therapeutic interest.
Academic-Industrial Partnership. Our industrial partner, a company with extensive experience in conducting
TO studies, will provide us with very valuable archival data in humans and nonhuman primates for testing and
validating our LPF algorithm.
In the present project, we will (1) Analyze simulated data with known occupancy distributions. (2) Re-analyze
archival data that represent different cases and/or violations of standard assumptions. (3) Perform
circumscribed studies in primates to confirm the biological interpretations of our new images. The work will be
complete when we have fully characterized and optimized the performance of our LPF algorithm. In the long
term, our goal is for a validated version of our voxel-by-voxel analysis of TO studies, to be adopted widely, to
the benefit of end-users, to speed drug development.