The Toxicologist - Society of Toxicology

852 UNDERSTANDING STRUCTURAL AND PHYSICAL
CHEMICAL DRIVERS OF DRUG TOXICITY: UTILITY
AND TRANSLATABLE VALUE.
D. P. Hartley 1 and M. Kansy 2 . 1 Genentech, South San Francisco, CA and 2 F.
Hoffmann-LaRoche AG, Basel, Switzerland.
Given the demands on drug discovery teams to produce effective, specific, and safe
new molecules, toxicologists are now finding themselves with new responsibilities
in the drug discovery setting as part of lead optimization teams. To be effective
members of these teams, toxicologists are now required to gain awareness and experience
in recognizing potential structural and physicochemical properties of compounds
that often lend to certain off-target toxicities, such as off-target receptor activities,
QT-interval prolongation, phospholipidosis, enzyme induction, liver
injury, and genotoxicity. The understanding of structural attributes of compounds
that may drive specific liabilities will enhance the toxicologist’s contributions by enabling
active collaboration with chemists to inform synthesis of new molecules to
gain a safety advantage over previous molecules. To this end, in vitro assays (e.g.,
hERG channel inhibition, pharmacology ligand binding panels, enzyme induction,
and transporter inhibition), coupled with specific mathematical or statistical models,
and pharmacophore models (e.g., hERG channel and PXR activation) can be
effective at instructing chemical modifications to attenuate the potential for activity
against specific toxicological endpoints a priori. Furthermore, new in silico approaches
in chemoinformatics are proving useful for predicting off-target polypharmacology
by mapping potential drug-target interactions through ligand-based similarities.
Similarly, mapping adverse drug reactions to chemical space may hold
promise for predicting specific features of compounds that lead to adverse drug reactions
in humans. Finally, detailed assessments of pharmacokinetic or physical
chemical drivers of tissue accumulation are improving our understanding of in
vitro—in vivo correlations. Overall these approaches demonstrate the importance
and utility of understanding structural motifs and physicochemical properties of
compounds that lead to off-target activity.
853 CLINICAL TRANSLATIONAL VALUE OF
PHARMACOLOGICAL PROMISCUITY OBSERVED IN
IN VITRO SAFETY PROFILING.
L. A. Urban 1 , S. Whitebread 1 , J. Hamon 2 , K. Azzaoui 2 and D. Mikhailov 1 .
1 Center for Proteomic Chemistry, NIBR, Cambridge, MA and 2 Center for Proteomic
Chemistry, NIBR, Basel, Switzerland.
In vitro safety profiling of a large number of pharmacological targets has recently
gained significant contribution to drug discovery. Extensive panels of biochemical
and functional assays addressing single targets in native or engineered cellular environment
provide large volume of data. In vitro safety profiling determines whether
compounds affect off-targets associated with ADRs and their pharmacological
promiscuity. In silico tools made it possible to deconvolute and interpret these data
and combine the chemistry and pharmacology space. Integrated assessment of data
today includes ADME, metabonomics and epigenetic considerations.
We focus here on pharmacological promiscuity, an important element of early profiling.
Excluding psychiatric drugs, marketed medicines show little promiscuity.
Most of these drugs are safe in the clinic, while those with high hitrate show more
serious ADRs and often attract black box warnings or labels.
Analysis of compounds from different phases of drug discovery show on average
higher pharmacological promiscuity then marketed drugs and high attrition rates
associated with safety during late preclinical development and in clinical trials show
that they are more likely to fail to reach the clinic.
Pharmacological promiscuity can be associated with physicochemical properties
(logP,PSA). In addition structural features of molecules can be recognized within
SAR for promiscuity over a broad range of targets/target families. We will highlight
association of SAR with off-target activities which could be successfully mitigated
during drug discovery. In vitro-in vivo correlations, determination of PD/PK-based
estimates of safety index and corresponding clinical therapeutic index should be
part of drug discovery decision trees and flowcharts. These preclinical forms of evaluations
place in vitro safety pharmacology data in clinical context and investigate
whether a molecule within a particular structural class could satisfy requirements
for a medicine.
854 PREDICTING DRUG OFF-TARGETS UNDERLYING
ADVERSE EVENTS.
M. Keiser 1, 2 and B. Shoichet 2 . 1 SeaChange Pharmaceuticals, Inc., San Francisco, CA
and 2 Pharmaceutical Chemistry, University of California, San Francisco, San
Francisco, CA. Sponsor: D. Hartley.
Chemically similar drugs often bind biologically diverse targets, yet most drugs are
presumed selective at therapeutic concentrations. To investigate this assumption,
we used the Similarity Ensemble Approach to compare several hundred approved
drugs against a panel of over 170,000 ChEMBL ligands organized into thousands
of sets according to the targets they modulate. Novel off-target drug activities consistent
with adverse events were predicted and confirmed in pharmacological assays.
In several cases, the drug’s novel target may be more consistent with the adverse
event than are any of its previously known targets. The chemical similarity approach
used here is systematic and comprehensive, and may find use for illuminating
side effects of approved drugs.
855 EARLY SAFETY PROFILING IN DRUG DISCOVERY:
HOW STRUCTURAL AND PHYSICOCHEMICAL
COMPOUND CHARACTERISTICS INFLUENCE THE
SAFETY PROFILE OF DRUG CANDIDATES.
M. Kansy and H. Fischer. Nonclinical Safety, F. Hoffmann-La Roche Ltd., Basel,
Switzerland.
The determination and optimization of drug compound characteristics in fast feedback
loops is an important activity in the lead identification (LI) and lead optimization
phase (LO) of drug discovery research. Usually in vitro assays are applied
at these phases. With the increasing number of available safety relevant measurement
results predictive (in-silico) models for safety assessments can be developed.
The combined application of in silico and specific in vitro methods allows the overall
reduction of wet lab experiments and the prediction of potential safety liabilities
of candidate molecules before they are synthesized (virtual compounds). Thus, the
influence of compound structural and property changes on the safety profile can be
partly evaluated. Compounds with improved overall quality can be selected and
cost as well as attrition rate be reduced. The talk will focus on newest achievements
in the early assessment of safety liabilities by in silico tools with focus on phospholipidosis,
phototoxicity, cardiovascular toxicities. The importance of amphiphilic
vector calculations for phospholipids prediction will be emphasized. New multivariate
in silico models based on UV-characteristics and compound properties will
be described and several computational models for prediction of cardiovascular
safety liabilities discussed.
856 PHARMACOKINETIC DRIVERS OF TOXICITY FOR
SMALL MOLECULES: EVALUATING PLASMA-TISSUE
CONCENTRATION RELATIONSHIPS.
D. Diaz. Investigative Safety Assessment, Genentech, South San Francisco, CA.
Plasma drug exposures are routinely used in the interpretation of animal toxicity
data. In reality, target tissue exposures can be much higher than plasma exposures,
which could have implications in the understanding of in vivo toxicities and in the
determination of in vivo-in vitro correlations. Examples will be presented in which
in vitro-in vivo correlations and differences in species sensitivity can be better understood
by considering target organ exposures. Systematic analysis of tissue drug
levels for a group of structurally diverse small molecules reveals large differences in
tissue distribution; in addition, tissue exposure levels show improved correlation
with toxicity compared to plasma exposure levels. Analysis of pharmacokinetic parameters
for these compounds indicates that tissue distribution can be roughly predicted
by taking into consideration the volume of distribution (Vss) and the clearance
(CLp) of a particular molecule. These findings suggest that consideration of
these pharmacokinetic parameters could potentially help provide more relevant and
translatable safety information.
857 MAPPING ADVERSE DRUG REACTIONS IN
CHEMICAL SPACE.
J. Scheiber. Pharmacology Research & Early Development Informatics, Disease &
Translational Informatics, Pharmacology Research and Early Development (pRED),
Penzberg, Germany. Sponsor: D. Hartley.
This talk will introduce a novel method that links substructures of drug molecules
to adverse drug reactions (ADRs) on a large scale. By leveraging the content of the
Pharmapendium database we were able to generate statistical models for many
ADRs based on chemical substructures. For the modeling we used the well-established
Scitegic fingerprints as input for a Naïve Bayesian classifier. For each of the
models we extracted the most significant chemical fragments so that a map of these
could be generated. Each adverse drug reaction is represented by a node and is
linked to other ADRs if they share at least one significant fragment. These results
are then visualized by using Cytoscape, the state-of-the-art network visualization
SOT 2011 ANNUAL MEETING 183