Measuring project success and Shannon's maxim: the enemy knows the system

Measuring project success
and Shannon's Maxim: "the
enemy knows the system"
Jeremy Edmunds
Dec 2017

Medicinal Chemistry in 21st Century
Available Info. Type of Screen
IsoStar - CSD
PIPER/ATLAS
Jeremy Edmunds, Immunology | Dec 2017| Confidential | © 2017AbbVie 2

Assessing project progression or tractability within discovery
Within Immunology we usually have 3 projects in lead optimization and
10 projects in the target selection phase
• Tool compound
identification
• In vitro assay
development
• Design & Synthesis
• ADME
• Pharmacology
• Safety/tolerability
• Process Chemistry
• GLP Toxicology
Design
Synthesis
Data
Stage gates
Functions
To date we have no objective process to assess project progression to IND

Several literature approaches assess the quality of chemical matter, but there
are only limited tools to chart project progression and resource spend

Notable : Quantifying, Visualizing, and Monitoring Lead Optimization
Andrew T Maynard et al., GlaxoSmithKline
Statistical framework to quantify and visualize the progress of LO projects
Maynard, A. T. and C. D. Roberts (2016). "Quantifying, Visualizing, and Monitoring Lead Optimization." J Med Chem 59(9): 4189-4201

Evaluate Maynard methodology
AIDEAS Platform: Bioǀia’s Pipeline Pilot/Tibco Spotfire:
1. Murcko clusters
2. ECFP6 similarities and Shannon entropy
3. iSCORE

Assigning compounds within data packages to Murcko clusters
as a surrogate for series definition
Murcko fragments are molecular scaffolds which form the
backbone of a compound. A compound is abstracted into
its Murcko fragment scaffold on the basis of ring, linker,
framework and side chain atoms. Each molecule is
assigned to exactly one scaffold. It is computationally
much simpler to abstract compounds into given Murcko
scaffolds than to cluster a large library of compounds
Compounds assigned to
several Murcko series

Pipeline pilot routines used for calculating Shannon Entropy and
ECFP6 matrix similarity
Shannon Entropy
ECFP6 matrix Similarity
Reference fingerprints calculated
on ALL project compounds
Shannon entropy
values independent
of series designation
Each compounds mean value is
dependent on series designation
meanECFP6
Shannon

iSCORE: Multi-Parametric Score
• Teams define Properties/Parameters and Weight required in scoring
• Project teams set the Desired value/thresholds
• Includes error margins
iScore1- 1- P  ^1/ Wi i 



 i1
 n iw
Example FunctionUser value = desired value : then P=0.5
User value = desired value +/- 6SD: then P=1

EXAMPLE 1 - PKC  Th1/Th17 biology play critical role in the initiation
and maintenance of psoriasis, inflammatory bowel disease and rheumatoid arthritis
PKC IC50 = 0.06
 M IL-2 Cell EC50 =
0.3  M
PKC IC50 = 0.02
 M IL-2 Cell EC50 =
0.12  M
Chronic in vivo efficacy
IL-2 Cell EC50 = 0.016  M
Excellent oral exposure
Low Cmax, high Cmin
Moderate chronic in vivo efficacy
Fragment
PKC IC50 = 453
 M
IL-2 cell assay: CD3/CD28-stimulated production of IL-2 in human T-blasts
In vitro biology :
PKC , PKC enzyme; PKC cell
In vivo Rat
PK
Rat CV
In vivo
efficacy AIA
PKC selectivity & Kinome
In vitro ADME :
RLM/HLM - Fu,Micr MDCK; Sol;
CEREP, hERG
CYP inh, TDI, DDI
Compounds
In vivo Rat
PD Con A
In vivo Rat
Tox

PKC theta: Lead optimization: 3046 compounds
cLogP
Murcko Cluster #
ShannonEntropy
ECFP6 Mean
R^2: 0.79

Diversity of PKC theta project compounds (Shannon entropy) with
corresponding composite of MPO (iSCORE)
MovingAverageiScore
MovingAverageShannonEntropy
#1
#5
#2
#3
#4
#3 – rapid onset of adverse symptoms and animal deaths with dosing at 100 mpk (BID) for > 10 days
# 5 – improved peak/trough PK, however, poor therapeutic index
Sufficient diversity with poor TI led to project stop

EXAMPLE 2 - JAK1 inhibitor

Number of unique compounds prepared per year within
reasonable calculated lipophilicity & molecular weight
Molecular Weight
ClogP
Mean ECFP6
ShannonEntropy
R^2: 0.83

Comparison of Shannon entropy and ECFP6 NxN mean matrix for
1674 JAK inhibitors
Similar trends in degree of similarity/dissimilarity calculated by moving average for
Shannon Entropy or ECFP6 fingerprints
MovingAverageShannonEntropy
MovingAverageECFP6

Janus kinase inhibitor (JAK) project
Project goal: achieve selective JAK1 clinical candidate
• During the course of the project 58 different assays were utilized to
measure JAK family member selectivity
• 12 enzyme and cellular assays dominated data collection

iSCORE: favorably increasing score with time
Clinical candidates
Missing values replaced by average
values across project compounds
MaxScore
Date
Property Operator Value Weight
Solubility / uM >= 1 1
Permeability 10E-6cm/s >= 1 1
HLM Clint L/hr/Kg <= 5 2
JAK1 hTF-1STAT3pEC50 >= 7 5
JAK1 HTRF 1 uM pIC50 >= 8 3
JAK1 HTRF 100uM pIC50 >= 8 3
JAK2 hUT-7 STAT5pEC50 <= 6 5
JAK2 HTRF 1 uM pIC50 <= 6 1
JAK2 HTRF 100uM pIC50 <= 6 1
JAK3 hTBlasts STAT5pEC50 <= 7 1
JAK3 HTRF 1 uM pIC50 <= 7 1
JAK3 HTRF 100uM pIC50 <= 7 1
MW <= 500 1
ClogP <= 5 1
TPSA <= 120 1

JAK clinical candidates align with higher scoring peaks
Clinical candidates
MaxScore
MovingaverageShannonEntropy
Date

Shannon entropy values by series definition
• Not surprisingly as the count of the compounds increases so does the median
Shannon entropy value (since similar compounds are prepared)
• Absolute Shannon entropy values reveal compound uniqueness
• Shannon entropy values for compounds are dependent upon the reference set
ShannonEntropy

Clinical candidates identified by profiling a diversity of
Compounds in rat/dog/monkey toxicity studies
Compounds with appropriate JAK1/JAK2
selectivity; efficacy; PK; CV safety;
to warrant rat, dog, monkey toxicity studies
Clinical candidates
ShannonEntropyMovingAverage

#
1
#2
#
3
#
4
#
5
#
6
#
7
#
8 #
9#10
#11
#12
#1 #2 #3
#5 #6 #8#7
#4
#9 #10 #11
#12
Absolute Shannon entropy values reveal the diversity of
Compounds selected for in rat/dog/monkey toxicity studies
iSCORE
ShannonEntropy

Summary
• The diversity of chemical matter being pursued on a project can be
evaluated relative to improvements in iSCORE
• iSCORE calculations limited by availability of data that influences efficacious
dose equation
Rumsfeld
• Known knowns: data that can be weighted and incorporated
• Knoǁ n unknoǁns: data that ǁ e knoǁ ǁ e don’t haǀ e, assign ǀ alues
• Unknown unknowns: criteria & values that can terminate a project..
• Useful to visualize the progress of a project up to and including stages of
assessing therapeutic index
• Implemented Shannon Entropy/ECFP quantification of similarity & iSCORE
within Spotfire so that similar projects can be compared periodically

Presented at the Global Pharma R&D
Informatics Congress.
To find out more, visit:
www.global-engage.com

Measuring project success and Shannon's maxim: the enemy knows the system

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