Target identification and selection

transcript

(Drug development science)

Péter Arányi, DSc

Contents

• Introduction: general landscape

• Molecular mechanisms – molecular

targets

• Target selection and validation

• Examples

• Screening and structure optimization:

Development Candidate (DC) properties

• Examples

TÁRSADALMI

IGÉNY

RESEARCH

CLINICAL

DEVELOP-

CLINICAL

DEVELOP-

PHASE I.

CLINICAL

DEVELOP-

PHASE II.

CLINICAL

DEVELOP-

PHASE III.

VALUE CHAIN OF DRUG DEVELOPMENT

UNMET NEED

FDA új gyógyszer regisztrációk

Mullard, 2015

FDA approved drugs 1930-2013

All indications 1453

Infectious

diseases

Cardiovascular

diseases

Oncology 193

Autoimmunity/

Inflammation

(Kinch, 2014)

FDA approved oncology drugs

(Kinch, 2014)

A LARGE PART OF DEVELOPMENT

COMPOUNDS FAIL

Lemorzsolódási görbe

preklinika I. Fázis II. Fázis III.Fázis NDA launch

Attrition curve

Reasons for attrition

The Innovative Medicines Initiative (IMI)

Research Agenda (2008)

Phase II failures 2008-2010

(Arrowsmith, 2011)

Phase II success rate ~ 20%

Phase III failures 2007-2010

83 (~50%) of submissions failed

Way to improve: avoid wishful thinking and rely on high quality science

(Arrowsmith, 2011)

EVOLUTION OF A DRUG

PREPA- RATION

AND SUBMISSION

OF NEW DRUG

APPLICATION

DOSSIER

MARKETING CLINICAL EVALUATION

IN MAN

PHASE I PHASE II PHASE III

P H A R M A C O V I G I L A N C E

Tolerance and

pharmaco-

kinetics

Biological activity and

research of a therapeutic

effect

Determination of the optimal

Confirmation of the

therapeutic effect and

tolerance

RESEARCH DEVELOPMENT BIRTH

1 to 2 years 1 to 2 years 1 to 2 yrs Contin. 6 to 8 years

50 3 10 5 000

molecules

RESEARCH INTO

CHEMICAL STARTING

POINTS

OPTIMIZATION PRECLINICAL EVALUATION IN VITRO AND IN

ANIMALS

• Conception

• Synthesis

SCREENING

• Intrinsic activity

• Selectivity

• Oral absoprtion

• Duration of action

1 to 2 years

• Chemical Process

• General Pharma- cology Profile

• Analytical Methods

• Stability

• Safety

• Metabolism and Pharmacokinetics

• Formulation

100000 50 1 10 3

Project mangement

• The course of drug development is

unpredictible, have realistic expectations for any

given project

• Running a drug development project is

Inherently difficult

• The larger the project the more numerous are

the problems

• Account for the fctors that may prevent success

• Take an objective view of the strategy

What kind of new drug do we

Molecular pathomechanism

• What does it mean

• How does it help drug discovery

• Examples

Haemophilia - thrombosis

Direct anticoagulants

Clot-bound factor Xa activity was

resistant to inhibition by antithrombin,

suggesting that the ability to directly

inhibit clot-associated factor Xa, with no

requirement for a cofactor, could provide

an effective and highly localized

approach to the prevention of thrombus

growth.

Apixaban, a direct Factor Xa inhibitor

Warfarin, a vitamin K antagonist

• Antagonizes γ-carboxylation of prothrombin and Factor VII

• (Strongly variable effect, difficult dosing)

Cell types involved in inflammation

How do we proceed?

New target

Internal

Literature

Validation

Selected Target

TSS & LG plan

HTS/MTS

Pre-program A2L Program DC

Use rational approaches and structural information to enhance

and facilitate Drug discovery and optimisation

Discovery approach

• „Biology driven”

• Exploiting an original biological target with

probable role in the pathomechanism

• NME should be found, which interacts with

the molecular target, defining the clinical

indication at the same time

Validating the target

• Full validation is only possible with clinical

results

• Partial validation on the basis of indirect

data (literature and experimental) – Association of genetic polymorphism with disease

– Gene expression in healthy and diseased tissues

– Dependence of cellular functions on the level of gene

expression

– Transgenic and GM animals

– Gene silencing (RNAi)

– Preliminary pharmacology

Technology intensive research

HPLC, GC, /MS

Bioanalyzer

Microarray scanner

Real-time PCR, PCR

Druggabbility

• Postulate: since the binding sites on

biological molecules are complementary with

their ligands in terms of volume, topology

and physicochemical properties, then only

certain binding sites on putative drug targets

will be compatible with high-affinity binding

to compounds with drug-like properties.

• Extension of this concept to a whole genome

analysis leads to the identification of the

druggable genome. This is the expressed

proteome predicted to be amenable to

modulation by compounds with drug-like

properties.

Druggability concept (Vistoli et al 2008)

Classes of molecular targets

• Receptors

– GPCR

– Ion channel-bound

– RTK

– intracellular

• Ion channels

• Enzymes

– Protein kinases/phosphatases

– Hydrolases

– Enzymes metabolizing signal molecules

• Signal molecules

• Transcription factors

Results of target reseach

1996 2006

successful targets

(at least 1 marketed

120 268

research targets

(no product on market)

~380 1267

Potential targets

(human + microbial +

viral)

1700 - 3000

Zheng et al. (2006)

Gene family distribution of drug

targets

Nuclear receptors

L-gated ion channel

V-gated ion channels

Penicllin binding

Myeloperoxidase.

Na-symporter

DNA topoisomerase

fibronectin

(Overington, 2006)

Molecular targets of FDA approved

drugs (2006)

GPCR Families (based on Analysis by Fredrikson et al; 2003)

CRHR2 CRF2

CALCRL CRLR

GRM2 mGlu2

GRM7 mGluR7

GLP1R GIPR

TM7XN1 GPR56 GPR97

PG, amine, opsin,

melatonin, EDF,

CB, MECA

Tachykinin, CCK,

NPY, AVP

SST, Gal,

Opioid, CC,

Thrombin,

LT, FSH

GPCR agonist drugs

• Morphine opioid analgesic

• Codeine opioid antitussive

• Salmeterol ß2 adrenerg asthma

• Buspirone 5HT1A (partial ag)

depression

• Sumatriptan 5HT1D migraine

Drug Receptor Indication

GPCR antagonist drugs

• Loratadin H1 allergy

• Cimetidine H2 ulcer

• Irbesartan AT1 hypertension

• Alfusosin α1 benign prostatic

hypertrophy

Drug Receptor Indication

(Levoye, 2007)

GPCR deorphanisation

An interesting target family: PKs

• 518 PKs coded in the human genome

• RTKs and intracellular signalling pathways

• Key role in cell proliferation and differentiated

cell functions

• Several oncogenes and cancer driver genes

code for PKs

• In vitro highly potent TK inhibitor series were

synthesized and are available

• The first TK inhibitor, Gleevec, approved in 2001

for CML and in 2002 for GIST

FDA approved cancer therapy

kinase inhibitors and mAbs

Kinase targeting oncology drugs

(Kinch, 2014)

FDA approved kinase inhibitors for

cancer therapy (examples)

Imatinib - Gleevec

Gefitinib - Iressa Afatinib - Gilotrif

FDA approved mAbs for cancer

Drug name, year of approval

2012 Perjeta (pertuzumab)

2013 Kadcyla (ado-

trastuzumab emtansine)

2013 Ganzyva (obinutu-

zumab)

2014 Cyramza

(ramucirumab)

2014 Keytruda

(pembrolizumab)

2014 Opdivo (nivolumab)

Indication

breast cancer

gastric cancer

melanoma

Difficulties in developing PK

inhibitor drugs • Toxicity and side effects: selectivity issue

– Competition at the ATP binding site

– Type I (DFG in) inhibitors are generally less

selective than type II (DFG out) inhibitors

• Resistance

– Redundance of the signalling pathways

• Drug combinations or dual activity inhibitors

– New mutations occurring during treatment

• Inhibitors of mutant kinases

Dendrogram of 518 human protein

kinases

Manning et al, (2002)

Molecular targets in NSCLC

Class I PI3K signalling pathway

Liu et al, (2009)

Genetic alterations in the PI3K

pathway in cancer

Liu et al, (2009)

Signalling pathways in the heart

(Lal et al, 2013)

Signalling pathways in cancer

and heart

nucleus

Plasma membrane RTK

cetuximab

erlotinib

idelalisib

Perifosine

everolimus

sorafenib

trametinib

preclinical

PD-1 signalling and effects

(Chinai et al 2015)

Efficacy of anti PD-1 antibodies

(pembrolizumab and nivolumab) shown

Orthogonal methods of target validation

• Genetic/epigenetic

– Differential gene expression in tissues/states • RNA

• protein

– KO gene

– Gene replacement by human ortholog gene

– Increased expression

– siRNA

Hardy & Peet, (2004)

Transcriptom map

(Caron et al 2001)

(11. human chromosome)

Proteomikai analízis (DIGE)

Orthogonal methods of target validation

• Chemical methods

– synthetic ligand

– mAB

– Aptamer

– Metabolic rescue (DHFR inhibitor trimetoprim

+ timidilát)

Hardy & Peet, (2004)

TECHNOLOGIES OF RESEARCH

HIGH THROUGHPUT SCREENING:

To cope with the high number of biological

targets provided by genomic

analysis and of compounds created by

combinatorial chemistry, it is

necessary to have rapid and efficient screening

tests.

Multiwell dish = microtiter plate

Screening flowchart

1st screen

Activity

2nd screen

selectivity

in vitro

metabolism

In vitro

absorption

In vivo pharma-

cology

In vivo pharma-

cology

In vivo pharma-

cology

passes

passes passes passes

passes

fails fails

New compounds

Prepared

combichem

New compounds

prepared

by parallel or

individual

synthesis

1 drug ≠ 1 target ≠ 1 phenotype

Screen systems – a comparison

High content screening

• Screen on living cells

• Fluorescent tags

• High resolution microscopy

• Parallel acquisition of data on different

properties

• Robotic handling

Predicting new targets for known

drugs • Drugs are not absolutely selective

• Polypharmacology defines 2nd (3rd) targets

• Similarity ensemble compares targets by the similarity of their ligands

• 3665 drugs compared against 65241ligands of 246 targets defined 184 new targets many of which unexpected

• 23 new drug-target associations experimentally confirmed

• The hallucinogen DMT known as σ1 ligand binds multiple serotonergic receptors with high affinity

Keiser et al, 2009

Targets for drugs

Chemical similarity between drugs

predicts affinities for unknown targets.

Some predictions verified experimentally:

ß1 antagonism by Prozac (transporter inhi-

bitor)

Inhibition of 5HT transporter by Vadilex

(NMDAR -ion channel - inhibitor)

H4 antagonism by Rescriptor (HIV reverse

transcriptase inhibitor)

Keiser, (2009)

Chemoinformatic drug repositioning may indicate new drug targets

Drug likeness (1/2)

• Various definitions of, and methods to predict,

drug-likeness have been proposed.

• Consensus is that drug-likeness is defined by

a range of molecular properties and

descriptors that can discriminate between

drugs and non-drugs for such characteristics

as oral absorption, aqueous solubility and

permeability. Computational property filters

can be used to rapidly assess the drug-

likeness of chemical libraries in silico before

purchase or synthesis.

Drug likeness (2/2)

• Orally administered drugs are likely to reside

in areas of chemical space defined by a limited

range of molecular properties.

• Lipinski’s ‘rule of five’. Historically, 90% of

orally absorbed drugs had

– fewer than five hydrogen-bond donors,

– less than ten hydrogen-bondacceptors,

– molecular masses of less than 500 daltons

– log P values (a measure of lipophilicity) of less than

A DC should be • Active against target (in vitro)

• Selective

• Stable (as a substance)

• Efficient in vivo (both in acute a chronic

administration)

• Displaying acceptable ADME features

• Displaying an acceptable side effect profile

• Non toxic

• Patentable

• Better than the competitors

AND THAT REQUIRES…

MULTIDIMENSIONAL STRUCTURE OPTIMISATION

Biologicals • Proteins, peptides

– Replacement therapy (insulin)

– Antibodies (antiTNFα…)

– IL-1Ra (anakinra)

• Oligosacchrides

– Heparin and derivatives

• RNA

– Antisense

– siRNA

– miRNA

• Gene therapy

• Stem cells

Examples

Natural protein Humulin

GM fehérje Lantus

mAbs Orthoclone

GM mAbs Remicade

Enzymes Pulmozyme

Vaccines TWINRIX

Aptamer Macugen

Diabetes

Kidney transplant

rejection

Crohn disease

Cystic fibrosis

Hepatitis A + rekombinant

hepatitis B

AR Macular degeneration

IgG1 antibody and related structures

H=heavy, L=light, VHH=camelid

IgNAR=shark ag receptor variable domain

ds=disulfid stabilizált

Antibody therapeutics, antibody

engineering, and the merits of

protein stability

S J Demarest* & S M Glaser (2008)

Popular mAb targets

Biopharmaceuticals in the

pipeline (2006)

2500 discovery phase

900 preclinical

1600 clinical phase

Drawbacks of biological drugs

• Limited therapeutic indications

• Parenteral administration (almost exclusively)

• Frequent unexpected AEs

• Safety and efficacy depends on production

process, may even change facility by facility

• High production cost/high price

• Expensive „generic” development: biosimilar

rather than generic

Biologicals – indispensable

therapeutics

• Substitution therapy for Proteins and/or

peptides

• Superior selectivity

• „non-druggable” biological targets

• Novel treatment options in case when the

available therapy falls short of need

Patenting

• Subject to the normal tests of

– 1) novelty,

– 2) inventive step and

– 3) industrial applicability.

• Patent expires 20 years from filing date

– In Europe, SPC can extend term for up to additional 5 years (see later!)

– Patent Term Extensions can exist in relation to US patents as well

• Patent protection is subject to renewal fees

Patent types

• Product Patents – Molecular

• Generic formula

• Specific formula – Salt

– Hydrates/Solvates/Anhydrous

• Process Patent – Methods for preparing the API

– Methods for preparing the formulation

• Use patent – Medical use patent

– Second/further medical indication

Oncology approvals

years (2006-2013)

all PKI

Oncology drugs approved in 2013

PK inhibitors mAbs other

Afatinib (angiokinase) Obinutuzumab (CD20) trastuzumab emtanzine

Ibrutinib (BTK) Denosumab (RANKL) lenalomide

Trametinib (MEK) pomalidomide

Regorafenib (VEGFR2-TIE) mechlorethamine

Dabrafenib (BRAF V600E) Ra223 dichloride

Colorectal cancer

• 160000 new diagnosis, 57000 deaths in the US each year

• EGFR - Cetuximab therapy (RAS) BRAF V600E mutations activate the MAPK signalling pathway

• Activating mutations of PI3K 1/3 of colorectal cancers (or IRS2 and AKT activating mutations in the same pathway)

Melanoma drugs

• Lifetime risk of developing melanoma: 2% of

men and women will have melanoma

• Metastatic melanoma fatal: 1 yr survival ~50%:

• The cytotoxic T lymphocyte antigen 4 inhibitor

ipilimumab, which takes the brakes off T cell

activation and thereby lowers the immune

system’s threshold for attack,

• BRAF V600E or V600K mutations: vemurafenib,

trametinib, dabrafenib

Non small cell llung cancer

• Lung cancer is the most common type of

cancer worldwide

• It caused about 160000 deaths in 2012

worldwide (~75% NSCLC)

• Lung carcinogenesis is multistep process,

many oncogenes mutated and/or

overexpressed and tumor suppressor

genes are altered

Molecular targets in NSCLC

EGFR targeted drugs in NSCLC

• Erlotinib

• Gefitinib

• Lapatinib &Erb-B2

• Afatinib blocks EGFRT790M

• Vandetanib &VEGFR

• Cetuximab

• Panitumumab

Other signal transduction

pathways driving NSCLC

and respective drugs

• C-Met crizotinib

• C-Kit sunitinib, dasatinib, imatinib

• PDGFR sunitinib, dasatinib, imatinib

• VEGFR bevacizumab, sunitinib,

sorafenib

For optimal results mutation details and

cancer genetics should be known

Cell types involved in inflammation

Cell types and kinases involved in

inflammation

• Tissue cells – Cytokines, mediators of

inflammation

• Monocytes, macrophages

– Cytokines, antigen

presentation

• T-cells – Cytotoxicity, TNF, IFN

• B-cells – Abs

Kinases mediating

these diverse cell

functions: Syk and Jak

Inhibitors:

• Syk: fostamatinib

• Jak: tofacitinib,

masitinib

Inflammatory diseases

• Rheumatoid arthritis

• Psoriatic arthritis

• Multiple sclerosis

• COPD

• Crohn disease

• Ulcerative colitis,

• etc

RA biologic and TK inhibitor

therapies

• Eight biologic agents are approved as first-line or second-line therapy in RA in 2013,

• five (adalimumab, certolizumab, etanercept, golimu-mab and infliximab) targeting tumor necrosis factor (TNF)

• three (abatacept, rituximab and tocilizumab) targeting co-stimulation of T cells, B cells, and interleukin 6 (IL-6).

• Syk inhibitor: fostamatinib

• Jak inhibitor: tofacitinib

Experimental drugs for RA

treatment • ABT-494 selective JAK-1 inhibitor

• Tofacitinib nonselective JAK-1/2/3 inhibitor;

serious side effects

• Baricitinib JAK-1/2 inhibitor serious side effects

• Sirukumab anti-IL-6 mAb

• Sarilumab anti-IL-6 Receptor mAb

• Clazakizumab humanized anti-IL-6 mAb

• QAL964 PI-3K inhibitor

• LY3090106 bispecific anti-IL-17 anti-(BAFF) mAb

Serious side effects of signal

transduction therapies • Infections

• Cancers

• Acute coronary syndromes

• Heart failure

• Immune reactions to biologics

Target identification and selection

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