Looking for the hit molecules that will make it to the...

Looking for the hit

molecules that will make

it to the market – in vitro

perspectives of industrial

drug discovery

Early Stage Drug Discovery in

Finland and in Oulu, September 13-14,

2016

Mervi Vasänge – who am I

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http://www.systemsvets.com/html/referenser.asp?id=3

http://swedishorphan-biovitrum.se/

http://www.jagsreport.com/logos/astrazeneca-logo.jpg

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• Where are we now ( 2010 and beyond) and why

• What lessions have we learned from this?

• Today´s trends in Drug Discovery and In vitro sciences


Topics for today’s talk

Year 1997 – for almost 20 years ago…

• The conference was about the paradigm shift that was ’at our

door’ and it would:

Drastically change the working processes

Shorten the time lines

Make it possible to produce drugs for indications that were

considered ’impossible’

Knock over large numers of pharma companies – those that hadn’t

been able to patent their propietary disease causing genes

In the end would only the biggest companies- through their

proactivity including mergers and fusions - stand as winners

- a small personal reflection

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• My first working day in Pharmacia & Upjohn (Uppsala) was kicked-off

with a huge internal conference for the whole R&D staff

So what was the ’paradigm shift’ in the mid 90’s?

HUGO (HGP) - Human Genome

(Organisation) project

• Aiming to map the human genome

• Non- commercial project initiated 1990 and

completed in 2003

• The Pharma industry considered that HUGO

would make it possible for companiest to

identify and patent disease causing genes :

– Race against time

– Work with model organisms (C.

elegans, Drosophila) to enable

patents before HUGO would finish


Simultaneously, technology development was

vast and fast


Miniaturized test formats to enable

testing of many compounds

Automatized robotic

systems saved

money and time

Advanced readers

enabled quantification of

a variety of biological

events

-10 10 30 50 70 90

110

0 32 64 96 128 160 192 224 256 288 320 352 384 Well

% i

nh

ibit

ion

Sample Buffer reference IT advances aided

handling of big

amounts of data

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The reductionist (target-driven) Discovery paradigm

From DDT i

early 1990

This is still principally valid today!

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So how have we succeeded in finding new drugs

since 90´s?


And this has happened even though we are

spending more money and resources


• Some challenges have been ’fixed’ … or are at least relatively

speaking in control


So what is the explanation to this?

Based on pragmatic and systematic

- Analysis of physiochemical properties

of Phase II drugs

- Aids in describing ’drug like’molecules –

attrition due to pharmacokinetic

problems has vastly decrease (oral drugs)

We are failing in efficacy… THE DRUGS DON’T

WORK


• Is it the target (mechanism)

• Is it the molecule


So where does it go wrong?

• Or maybe both?

• Has something led us astray?

• ”TV chemistry”

– No (limited) need for lab chemists anymore


A few science ’hypes’ during my career Partly

aswering

the previous

question

• ”HTS is the answer”

– Mean and lean screening machine

• Patent race for targets (model organisms)

– Only winners to survive

• Technologies

– FRET, DELPHIA, alpha-screen…equipment ’easy-fix’

• Size of compound collection

– The bigger the collection the higher the chance of winning

HTS and reductionistic drug discovery (worst

case scenario)

• Research model is built on mathematical attritions

calculations and the assumption that there is a linear

relationship between the number of initiated projects and

succesful clinical programmes

• Same thinking was the basis of the early HTS campaigns

- Over-simplifying biology


• In many companies this has lead to ’a dilution’ of resources through

initiation of more and more projects

Resembles the

’brick box’ toy

http://www.urbanliving.se/upl/img/full/173_114.jpg

The answers you get depend on the questions you ask


From the point of view of the biologist/ pharmacologist:

The key is to get the target (mechanism) and the assay(s)

right!

The target has to be ‘central’

enough for the disease – avoiding

redundency in the pathway

The assay has to measure a

relevant event in a relevant

background – and allow for

compound differentation

Some of the lessions learnt

And remember:

”One size does not fit all!”

- every target, mechanism, project is

unique

For higher succes rates and to nourish

the industrial drug discovery we

need to:

• Be humble for nature – we have only a

(small) portion of the answers

• Utilize the modern opportunities,

technologies and competences that

have evolved over the last

– BUT with distinction and good

judgement


The Huge Challenge of Drug Discovery

Scale (meters)

molecules pathways cells tissues humans

10-9 M 10-8 M 10-7 M 10-6 M 10-5 M 10-4 M 10-3 M 10-2 M 10-1 M 1 M

Human exposure Molecular targets

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• To ‘ratonalize’ human biology

• Complex; multiple modular, highly interconnected networks

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• ”How were new

medicines discovered”, Swinney and Anthony Nature

Drug Discovery 2011


An article that ’shook’ the industry

Definitions:

A genetic target based approach assumes that you understand

a biological system well enough to attribute disease to a specific

gene; one protein modification.

‘Phenotypic approach starts with function first’ the observation

of an organism displaying a certain phenotype for example in a

disease state. Compounds are then screened to find those that

can alter the phenotype. The mechanism for this would be found

later – and sometimes very late (or not at all!).

• A systematic mapping of the

discovery of NMEs during 10 years

• Classification according to

screening method used – Target based

– Phenotypic

• In reality, majority of drugs interact with multiple targets

• For many diseases, treatment with a single drug (single target)

is insufficient


Target based drugs

• Using biological systems to discover new drugs

– Target agnostic approach

• Neoclassic Drug Discovery – an even more modern approach

– The combination of using biologically complex model

systems & high throughput approaches (JAL & EB, 2013)

– Screening assays that are extraordinarily well

characterized

• Tool compounds

• Omics and genetic technologies

– Integration of target-based and phenotypic drug

discovery

So “Phenotypic Drug Discovery” is


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Mounting evidence suggests that capturing the biological

complexity of the disease state in the earliest in vitro assays

results in better clinical translation


So today…

Comparision … and a word of warning

- Phenotypic compound screening systems that

focus on the modulation of a disease-linked

phenotype in a target-agnostic manner

- More physiologically relevant

than target-based ones because they

are minimally cell-based, if not tissue- or

whole-organism–based.

- Furthermore, they offer the possibility of

identifying compounds acting through either

unknown targets or unprecedented molecular

mechanisms of action (MMOA) for known

targets.

- Target-based drug discovery

postulates a direct link between

the modulation of a target through a given

MMOA and the resolution or mitigation

of a disease state.


the ultimate success of the drug discovery process depends

in large part on whether the target or phenotype assayed in

the HTS is relevant to the disease indication being pursued

Let´s not make phenotypic approach into a hype!

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MVasänge/IVB Orion

DEVELOPING PREDICTIVE ASSAYS - ASSAY DEVELOPMENT RULE

OF THREE:

RIGHT/ DISEASE RELEVANT BACKGROUND (CELL, TISSUE)

RIGHT/RELEVANT STIMULI (DOES NOT CHOCK THE CELLS)

RIGHT/ CLINICALLY RELEVANT READOUT

Sci Transl Med. Vincent et al, 2015

Context is the Key

• Target validation

– Biology has a modular architecture

– Function depends on “context”

• Target selectivity (poly-pharmacy)

- Most drugs interact with more than one target

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Non-reductionistic

approach


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• Primary (human) cells, preferably patient-derived

– Often difficult to get hold on, blood cells most often used

• 3D models

– Starting with animal models and moving on to human

• iPSCs with the relevant disease phenotype


What are ”the context” of interest today

These systems were previously impossible to be used in primary

screening assays

Today the technology bases available including data handling capacities

make it possible

Even for big(gish) screens (larger companies)

• The aim of the STEMBANCC project is to generate and characterise 1 500 high

quality human induced pluripotent stem (iPS) cell lines that can be used by

researchers to study a range of diseases, including diabetes and dementia,

and test for drug efficacy and safety.


A lot is going on,

for example…

Orion:

Peptidergic

neurons

Cell types, pros and cons


Stem Cells Translational Medicine.

2014;3(4):500-509

Not only purely a screening asset


hiPSCs and clinical trials Disease-specific hiPSCs can potentially be used

as an in vitro arm for clinical trials as part of

demonstrating safety (phase I), drug efficacy in

human tissue (phase II), and safety and efficacy

in a diverse population (phase III

Late example for Alzheimer’s disease


Using iPSCs, HTS, and HCA could

allow for rapid analysis for

thousands of compounds and

disease hallmarks, as well as

various cellular contexts

affecting drug efficiency, or

chemical toxicity, for example.

- iPSCs can retain the patients' genotype

- enable the recapitulation of AD in a dish

- neurons derived from disease-specific iPSCs

Stem Cells International. 2016;2016:7828049

Today’s DD problems

• Same targets, in parallel, in secret

(duplication, wastage, patients being

unnecessarily exposed)

• Target validation is not often

enough done in patients

(preclinical assays have limited utility)

• No one organisation has all

capabilities

• Early IP is making it even harder (slows collaboration, restricts

competition, makes process more expensive)


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Thus another trend today…

Early preclinical research

Preclinical Research

Early Developm

ent

Late developm

ent Registration

Phase IV studies

Towards loosening up of the ’Big Hulks’


Big/Medium

Pharma

Academy

Small Pharma

CROs

partners

Co-ordination, leadership Execution, monitoring, analysis

Basic reserach, translational medicine

Innovation, partnership

Execution, monitoring, analysis

the pharma companies are

getting more open


Examples of ’how and what’ is in progress

AstraZeneca and Sanofi exchange over

200,000 chemical compounds

(NYSE: SNY). For more information please visit:

www.sanofi.com About AstraZeneca AstraZeneca is a

global, innovation-driven biopharmaceutical business

that focuses on ...

20 November 2015

• Collaborations

• In-licensings

• Partnerships

• Fee for service

• Consortia

• Open innovations

• …..


So industry and academia are closer and more

dependent on each other than ever before

• Many ideas and initiatives originate from published litterature

data


Recent problems arising – us and others

• Only a small

proportion of

experiments could be

repeated

• Amgen study – only 6 of the

53 (10%)

Begley & Ellis Nature 483,

531–533, 2012

• Bayer study – only 14 out of

67 (21%)

Prinz et al. Nat. Rev. Drug

Discov. 10, 712, 2011


Thus to use litterature data for validation and ideas can

be risky

More than 75% of protein

research still focuses on the 10% of proteins

that were known before the genome was

mapped

Kinases, ion channels and nuclear receptors

are the most common target classes explored

in academia

Around 65% of the 20,000 kinase papers

published in 2009 focused on the 50 proteins

that were the ‘hottest’ in the early 1990s

75% of the research activity on nuclear

hormone receptors in 2009 focused on the 6

receptors — out of the 48 encoded in the

genome — that were most studied in the mid

1990s


Another problem: even academia focuses on the

same targets/mechanisms – and big areas remain

uninvestigated

Many new potential targets

(particularly in oncology) base on

siRNA and mutation data that

remain uninvestigated

How bad is it then inside pharmas?


• We have come a fair way, learnt from our failures and shortcomings,

• AND have huge scientific and tecnological break-through assets

• AND we are finding new ways of collaboration and openess


Is it all bad…? NO, absolutely not!

• The trick is to use the available knowledge, experience,

technology, networks WISELY and treat each target/ project

idea as individuals, use unique discovery approaches

Looking for the hit molecules that will make it to the...

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