Innovations in Drug Discovery - Novartis Institutes for BioMedical Research

Pharmaceutical Innovation – a personal perspective:
how we got here and now where do we go?

Sanjeev Thohan, PhD
March 28, 2013

Overview…

 Historical perspective
 Target prosecution and safety
 Leverage
 Today and beyond…

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2 Sthohan | March 2013 | Pharma Innovation | Confidential

4000 years of medicine


Serendipity to deliberate drug discovery….
 In the past, drugs were at times discovered in a
haphazard, or even accidental way, with
pharmaceutical companies encouraging employees
to take vacations in exotic locations and bring back
dirt, fungus and other organic material, with tests
then done on animals to see what the outcome would
be… Gavin MacBeath, Harvard University, (2003).

 Multidisciplinary efforts intersecting at a common
ground of ―target-driven-drugs‖ that are a
consequence of deliberate research and
development…


Historical perspective – influential pharmaceuticals
Medicine year Importance
Morphine 1827 Commercialized by a pharmacy (Merck), pain management (Germany)

Aspirin 1897 Synthetic salicylic acid was commercialized (Germany)

Ether 1842 General anaesthetic, transformed surgery (US)
Arsphenamine 1910 Syphillis Treatment (Hoechst, Germany)
Insulin 1922 1st hormone therapy, transformed diabetes management

Penicillin 1929 Transformed the treatment of microbial diseases

Chlorpromazine and 1950 Transformed management of psyschosis. (France) (Belgium)
Haladol & 1958
Estrogen+ Progestin 1961 Birth Control Pills, deep social impact (USA)

Digoxin 1962 Changed treatment of heart failure and hypertension (Germany)
(France)
Furosemide 1993 Loop diuretic, effective treatment of hypertension

Atorvastatin 1996 Cholesterol lowering medicine (USA)
HAART 1996-7 Transforming effect on AIDS patients
L-Dopa (Sweden); Hydrocortisone; Viagra (1996, USA); Ritalin

New Medicines Increase Longevity
“They can mean an extra three months or five months or a year-
another Christmas with the family, another season to plant a garden,
another passage in the life of a child.”
—Donna St. George on new targeted cancer therapies, The Washington Post, 2004

2.5
40% of Increase in Life Expectancy
Increase in Longevity Due to
New Drug Launches
Number of Years Increased Longevity

Total Increase in Longevity 1.96
2.0

1.65

1.5 1.37

1.07
1.0
0.76 0.79
0.70
0.57 0.62
0.56
0.45
0.5 0.30
0.23
0.12

0.0
1988 1990 1992 1994 1996 1998 2000 Data source: Lichtenberg. National Bureau
of Economic Research Working Paper No.
9754 (Cambridge, MA: NBER, June 2003).
11

Pharmaceutical Lifecyle


Biotech: larger share of innovative approved drugs

Innovativeness of FDA approved drugs (2001 – 2007)

Source: USFDA


Drug Approvals 2012

Mullard, NatRev DD 2013

 39 new drugs last year, marking a 15-year high. Most
approvals since 1997 (↑33% over the last 20 years).
 20 of 2012 approvals were first-in-class agents


So how do we get there?

It‘s a team effort……

Discovery processes: Target identification strategies

 Gene expression profiling
 Focused proteomics, e.g. activity-based protein profiling
 Pathway analysis – pathway databases, e.g. GeneGo Metacore & Ariadne
 Phenotype analysis – phenomic database
 Functional screening (siRNAs, shRNAs)
 Genetic association
 Scientific Literature


Properties of an ideal drug target
 Target is disease-modifying and/or has a proven function in the
pathophysiology of a disease.
 Modulation of the target is less important under physiological conditions or in
other diseases.
 If the druggability is not obvious (e.g. as for kinases) a 3D-structure for the
target protein or a close homolog should be available for a druggability
assessment.
 Target has a favorable ‗assayability ‘ enabling high throughput screening.
 Target expression is not uniformly distributed throughout the body.
 A target/disease-speciﬁc biomarker exists to monitor therapeutic efﬁcacy.
 Favorable prediction of potential side effects according to phenotype data
(e.g. in k.o. mice or genetic mutation databases).
 Target has a favorable IP situation (no competitors on target, freedom to
operate).


Therapeutic approaches: target modulation

Traditional Novel – Good IP position
 Small Molecules  Antibody drug conjugates
• Enzymes, receptors, transcription  Stapled or stabilized
factors, ion channels, transport
proteins, protein-protein interfaces proteins
 Biologics  Nanotechnology
• Extracellular proteins, trans-  Repurposed/repositioned
membrane receptors, cell surface drugs
receptors, substrates and
metabolites
 Patent extension
 Nucleic Acids
• RNAi


Discovery Processes: Lead Optimization


Drug Failures in Ph II-III

Phase II failures 2008-2010 Phase III failures 2007-2010

Nature Reviews Drug Discovery 10, 328-329 (May 2011) Nature Reviews Drug Discovery 10, 87 (February 2011)

Leading reasons for adverse events:
• cardiovascular toxicity
• hepatotoxicity


Population Responses

What we use in research models
Intrinsic variability
• Drug-target or metabolite target interaction
• Type of target transduction
• Access at the biophase
• Delivery and input rate
• Metabolism and pheno/genotype
• Disease and homeostasis
What is • Placebo response
Extrinsic Variability
• Drug-drug interactions
• Interactions with endogenous substances


Elements of early safety assessment
• In vitro Safety Pharmacology:
– Human target based: associated with clinical adverse reactions
• GPCRs
• Nuclear hormone receptors
• Ion channels  Risk Assessment and Mitigation
• Transporters
• Kinases
- Integration with ADME and PK data
- Computer-assisted Drug Design (SAR)
• Proteases
-Clinical annotation
• Other enzymes
-Bioinformatics and network prosecution
• Phenotypic and Organ-toxicity
– Cell- & tissue-based
• Cardiomyocyte-based assays
• Hepatotoxicity
• Hematotoxicity
• Neurotoxicity
• Genotoxicity


How to identify targets for safety profiling?
Reverse translation

Therapeutic effect A
Relevance to EFPC

Common ADR Molecular target Cmax
AC50
General application

Therapeutic effect B
Define coverage

EFPC: effective free plasma concentration
AC50: concentration necessary to achieve
50% activity @ off-target, in vitro


Predicting targets based on ADRs
Requirements
• Large-scale computational effort to predict the activity of marketed drugs against
adverse drug reaction (ADR) targets
• In vitro profile of marketed drugs
• Biomarker for the off-target related ADRs a d
• Extrapolation to drug candidates to predict ADRs in silico

a
Side effect profile of
d Side effect profile of Pr

chlorotrianisene synthetic estrogens
Prenylamine

Chlorotrianisene

Chlorotrianisene

e

e

Domperidone
Lounkine et al. Nature (2012)
b
b

Prescription drug cocktails?
There is a chance to enhance side effects by taking several promiscuous compounds

Do we take this into account?


Proof of Target – ADR link: 5HT2b agonism - VHD

Common feature: 5HT2b agonism
Clinical landscape of VHD
Restrictions
Withdrawn Withdrawn
30

Fen- Phen

Dose dependent effect! Kvernmo, 2006

Specifics of 5HT2b-related VHD
 Long latency development, but irreversible*
 Hard to detect/diagnose in the clinic
 No signal in short regulatory animal studies
 Needs special in vivo experimental design to
confirm manifestation


Combination therapy profiles
Look for caution signals and common pathways
Pimozide Risperidone Zolpidem Alprazolam Fluphenazine Haloperidol


Type 2 Diabetes mellitus treatment landscape
Monotherapy add add

Obese metformin sulfonylurea exenatide or Insulin or
glitazone

Non-obese Sulfonylurea exenatide or Insulin or
or metformin glitazone

elderly Low dose secretagogue Switch to simple insulin ---
regimen

Asian glitazone metformin Sulfonylurea or
Insulin or Exenatide*
(*not approved w glitazone)

 Multidrug regimen for diabetes can become more complex with atherogenic
dyslipidemia, hypertension, and prothorombotic/proinflammatory states
• Cholesterol management (simvastatin)
• ACE inhibitors (enalapril)
• Low dose aspirin


Combination therapy profiles
metformin sitagliptin pioglitazone simvastatin enalapril


Drug Innovation – ―the new‖
 New tools to do things
• reagents to explore biological phenomena or new types of drugs, such as aptamers,
chimeric proteins, peptidomimetics, multi-valent antibodies, etc.
 New ways to measure things
• techniques of scientific observation and measurement, including new visualization
methods, multiplexed assays, real-time biological kinetics measurements and others.
 New ‗things‘ themselves
• devices, including the use of new materials with novel properties.
 New ways to handle and extract insights from experimental
observations
• advances in bioinformatics, data integration, knowledge management, artificial
intelligence and others.


Leveraging the existing

New IP?....

Repositioning
"New technologies however enable the systematic evaluation of any drug or mechanism of
action against any disease."
 Aris Persidis of Biovista is in the process of filing for novel use patents for 12 drugs with
potential in Parkinson's, Alzheimer's, epilepsy, depression and sleep disorders.
 Clive Morris, head of the new opportunities division at AstraZeneca, existing medicines
that have already been in clinical trials can skip the early phase of drug development
and go straight into phase two (mid-stage) trials, which can save three to five years.
AstraZeneca is now testing a failed diabetes and obesity drug for use as a glaucoma
treatment.
 AstraZeneca (October 2012) made 22 failed medicines available to academics through
a partnership with the Medical Research Council and it also struck a £180m partnership
with its bigger rival GlaxoSmithKline in May to boost the faltering development of new
antibiotics, dubbed NewDrugs4BadBugs.

"Typically, repositioning is done by accident, or in a limited way,―
-between 2007 and 2009, 30% of all newly marketed medicines
were either existing drugs or new formulations of old drugs.
- - Aris Persidis (Biovista - 2012).


Repositioning
 The safety advantage.
• Existing drugs that are either approved or have been shown to be safe in late-stage trials, but have failed to meet
end points of their originally-targeted indications, can leverage their inherently reduced development risk into
potentially new indications. Since safety accounts for approximately 30% of drug failures in clinical trials, this is a
significant development advantage that repositioned drugs enjoy.
 The money savings advantage.
• Relaunching a repositioned drug averages $8.4 million, whereas to relaunch a new formulation of an existing drug
in its original indication costs an average $41.3 million. NCE/NME development averages more than $1.3 billion
(160 million times less investment). Repositioning is in a completely different league of investment needed to
create a new drug product in the market.
 The market potential advantage.
• Potential for market success depends on numerous factors, including market need, competition, differentiation, an
excellent product, IP barriers, payer acceptance, compliance and a successful market strategy. These factors
apply for repositioned drugs in the same way as they do for NCE/NME drugs as well.
 The return on investment potential.
• Portfolio strategy: it is prudent to have a reasonable stable of repositioned drugs under development as a portfolio,
to allow for attrition due to potential lack of efficacy (but not safety), when any drug is tested in clinical trials.
 The out-licensing potential.
• Pharmaceutical companies are said to be exploring new models to out-license some of their clinical drug
candidates that may have been shelved for whatever reason. Benefits: met end points and have proven
themselves to be safe. Repositioning grants a pharmaceutical company specific and novel business development
possibilities for out-licensing.


Repositioning
Original Use Repurposed
Aspirin (Bayer) - 1897 Inflammation and pain antiplatelet drug for treating and
preventing heart attacks and strokes
Ibuprofen (Boots) -1960 Anti-inflammatory Hangovers, rheumatoid arthritis, and
Parkinson's disease prevention?
Galantamine (Sopharma) Plio paralysis/ Alzheimers
1960’s - USSR anesthesia

Zidovudine (GSK) 1964 Oncology HIV/ AIDS

Rogaine (Pfizer) - 1976 High blood pressure hair loss

Mifepristone (RU486) - 1980 Pregnancy termination Antipsychotic, major depression

Gemzar (Lilly) - 1980s Antiviral cancer drug

Cymbalta (Lilly) - 1990 Antidepressant fibromyalgia

Finasteride (Merck) -1993 Benign prostatic Hair loss
hyperplasia
Topiramate (JNJ) - 1996 Epilepsy Obesity

Viagra (Pfizer) -1996 Heart disease Erectile dysfunction
Pulmonary Arterial Hypertension

Repositioning: explore alternative indications for existing drugs
Bioinformatics-based approaches have the potential to offer systematic
insights into the complex relationships among drugs, targets and
diseases necessary for successful repositioning.

 Network modeling links repositioning objects in a
network format.
 The network biological relevance is measured by the
purity of identified modules and topological parameters
such as ―betweenness centrality and closeness.‖
 The network can be used to predict novel repositioning
opportunities.
Liu, et.al., DDT 2012

Biologics: 907 medicines and vaccines in development - 2013
 338 cancer therapeutics that target
several different types of solid tumors,
leukemia and lymphoma. Monoclonal
antibodies account for 170 of the 338
products in development.
 176 candidates in development for an
array of infectious diseases, including 134
PhRMA Productivity report 2013
vaccines.
 71 medicines for autoimmune diseases, such as lupus, multiple sclerosis
and rheumatoid arthritis.
 58 treatments for cardiovascular diseases, such as congestive heart
failure and stroke.
 Other diseases include diabetes, digestive disorders, genetic disorders,
neurologic and respiratory disorders


Protein-protein interactions
Today:
 high-quality interaction
networks of reasonable
coverage are available
for only a small number
of interaction types and
model organisms, thus
limiting the evolutionary
trajectories. Limiting our
understanding.

Yama and Burk. Nat rev mol cell biol 2009

Future opportunities: shift from static 2D to comparative spatiotemporal
network.
Higher density data with greater resolution means more opportunity.

Tools of nanotechnology
 Liposomes
 Nanoparticles
 Polymeric micelles
 Dendrimers
 Nanocantilever
 Carbon nanotubes
 Quantum dots

Misra, 2010, DDT

Stapled peptides
Can stapled peptides solve the ―undruggable
space?‖
 Historical perspective:
• Not orally available in active form
• Lack the ability to enter cells
• Inactivated by proteases, filtered from the blood by the
kidneys within minutes.

A stabilized α-helix (pink) binds to a
key portion of the HIV capsid (blue),
as shown in an NMR structure. A
hydrocarbon side-chain cross-link
(yellow) helps this helix enter cells.
Drahl, CEN. Volume 86 Issue 22 (2008)

http://www.aileronrx.com


New Technology: Histopathology imaging

 Whole slide images of histology sections resolved into
distinct patches (e.g., viable tumor, necrosis) so that
each patch can be linked with the outcome.
 Computed code, from the learned representation, is
then utilized to classify patches from a curated library of
images.
 Evaluation over 1400 and 2500 samples of glioblastoma
multiforme and clear cell kidney carcinoma indicates a
performance of 84% and 81%, respectively.

Color coding is black
(tumor), pink (necrosis),
and green (transition to Processes are computationally demanding
necrosis). Solutions may be in High Perfomance
Computing – AI learning.

Opportunities for innovation
 FIPNet (fully integrated pharmaceutical network) model of drug development,
in which the core capabilities of different stakeholders in the development
process are leveraged. CRO, contract research organization

Katin, Clin Pharmacol Ther. 2010 March; 87(3): 356–361.


Sharing?
 Securely profile every compound
ever synthesized against every
assay with multiple computational
models in a collaborative manner,
using standard technologies
without structural disclosure.
 There is a need for a universal
platform for collaborative drug
discovery and development that
will allow researchers to
collaborate, while retaining refined
IP rights.

Bunin & Ekins, DDT 2011

―Integrated specialization‖
Operate within natural workflows or with minimal interruption to research individuals/teams.
Securely and selectively collaborate with anyone or any organization with truly
complementary and best in class capabilities… Bunn and Ekins DDT 2011


Questions and thoughts


Innovations in Drug Discovery - Novartis Institutes for BioMedical Research

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