enhancing molecule quality by combining fragments and ... · enhancing molecule quality by...
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Enhancing molecule quality by combining fragments and early pharmacy input
Simon Hodgson*
GSK, Stevenage, UK
*Current address – Stevenage Bioscience Catalyst
17th RSC/SCI Medicinal Chemistry SymposiumCambridge, UK. September 2013
Collaborative project between GSK and Astex
Gordon Saxty *Paul MortensonDavid NortonLee PagePhil DayCaroline RichardsonAnne CleasbyJoe CoyleRachel McMenaminDavid ReesChris MurrayJeff Yon
Simon Hodgson * Dave ClaphamKaren AffleckSimon TeagueEmma SherriffJon HutchinsonLinda RussellSorif UdinJoelle LeDon SomersAshley HancockHeather HobbsRobin CarrAndrew Leach * Co‐project leaders
Talk structure
• Background– Attrition
– Importance of Solubility
– DD approaches
• Application of FBDD and early pharm dev intervention ‐ PGDS example
Attrition – we can have an impact!
• Early example of how a major attrition factor of PK/ bioavailability changed 1991‐2000
• Early incorporation of DMPK reason for the improvement• But attrition challenges shifted further to clinical efficacy
Kola, Landis NRDD 2004
The War on Attrition
• Pre‐clinical to Phase III success = 4.3% survival rate; ‘Phase II graveyard’• 4‐5% Improvement will double output
• Caveat: clinical phase attrition is often multi‐factorial: ‘poor exposure’contributes to efficacy failure in Phase II
• Industry is moving from a ‘quantity’ to a ‘quality’ strategy
Data supplied by Phil Miller, Thomson Reuters© CMR International, a Thomson Reuters business
Industry Success Rates & Causes of Attrition 2006‐10
Pharma’s problems: Paul et al, Nat. Rev. Drug Disc., 2010, 9, 203; Scannell et al, Nat. Rev. Drug Disc., 2012, 11, 191
Courtesy P.Leeson
Phase II Attrition: Pfizer Data 2005‐2009 (n=44)Levels of Confidence in 3 ‘Pillars’: 1) Exposure at target site of action; 2) Binding to target; 3) Pharmacological response
• Low confidence in exposure in 18/34 non‐progressing molecules: “cannot conclude mechanism tested adequately in 43% of cases”
• Compound quality issue: formulation; DMPK; dose prediction; safety margin. Should be resolved prior to Phase II?
3 Pillars: Morgan et al, Drug Discovery Today 2012, 17, 419‐424
None or partially metn = 12
•12 failed to test mechanism•0 phase III starts
Exposure & Bindingn = 12
•5 tested mechanism•2 phase III starts
All metn = 14
• 14 tested mechanism• 12 achieved positive POC• 8 phase III starts
Binding & Pharmacologyn = 6
• 5 tested mechanism• 0 phase III starts
Pharmacological confidence
Expo
sure con
fiden
ce
LowLow
High
High
Courtesy P.Leeson
What Do Medicinal Chemists Actually Make?
• A 50‐year retrospective from J.Med. Chem• Mean properties for compounds appearing in JMC papers during
the first 5 years of publication and in the most recent 5‐year period
W Walters et al VertexJ. Med. Chem. 2011, 54, 6405–6416
Probing the links between in vitro potency, ADMET and physicochemical parameters
• Analysis using the ChEMBL database, which includes more than 500,000 drug discovery and marketed oral drug compounds
• Key findings– oral drugs generally don’t have low nanomolar potency (50 nM on average); – many oral drugs have considerable off‐target activity– in vitro potency does not correlate strongly with the therapeutic dose.
• These findings suggest that the perceived benefit of high in vitro potency may be negated by poorer ADMET properties
• ‘Catch22’ – chasing low dose (to obviate DD issues) by high target affinity (and DD methods) made properties worse!
P.Gleeson, A.Hersey, D. Montanari, J.OveringtonNRDD 2011
Developability Classification System (DCS): for Formulation Development.
Useful for Chemists to focus on!
• Importance of solubility, permeability and dose• Earlier BCS classification to DCS, uses FaSSIF solubility, and sub‐
divides class II further
J.Butler, J.Dressmann
Journal of Pharmaceutical Sciences, Vol. 99, 4940–4954 (2010)
DCS 2BN=8
DCS 3N=25‐27
DCS 4N=4
DCS 2AN=17‐34
DCS 1N=50‐65
Top 121 oral prescription medicines by DCS
Dose/Intestinal solubility (mL)
J.Butler J.Dressmann
Journal of Pharmaceutical Sciences, Vol. 99, 4940–4954 (2010)
Despite a wide recognition of the importance of solubility, pipeline drugs are not optimal
• Current portfolio of pipeline development drugs aimed at oral administration in comparison to marketed drugs, shows a strong trend towards drug candidates with low aqueous solubility
• ~90% of pipeline drugs fall into BCS classes II & IV
http://www.americanpharmaceuticalreview.com/Featured‐Articles/135982‐The‐Innovator‐Pipeline‐Bioavailability‐Challenges‐and‐Advanced‐Oral‐Drug‐Delivery‐Opportunities/
Ralph Lipp. Amer. Pharmaceutical Review Apr 2013
Poor solubility impacts from early to late stage drug discovery
• Early Discovery– In vitro assays – inaccurate assessment of potency and
variability– Low bioavailability
• Poor pre‐clinical efficacy
• Post Selection of Development Candidate– Inability to achieve pre‐clinical tox cover to support clinical
studies– Poor clinical efficacy/ insufficient or variable exposure to test
the mechanism– Formulation development cost and time increase
• For early clinical studies• Late stage attrition! Complex formulation development often delayed until after encouraging phase1/2
Approaches to addressing solubility
• Working with the Candidate– Salt formation might be enough– Particle size to increase dissolution rate– Complex formulation
• E.g Lipidic in capsule– Stabilised amorphous form
LatePass the problem on!
Approaches to addressing solubility
• Working with the Candidate– Salt formation might be enough– Particle size to increase dissolution rate– Complex formulation
• E.g Lipidic in capsule– Stabilised amorphous form
• Change the chemistry of the lead series– Pro‐drug the lead candidate– Structurally modify a poorly soluble series
LatePass the problem on!
Quite lateFurther LO resourceComplexity
Approaches to addressing solubility
• Working with the Candidate– Salt formation might be enough– Particle size to increase dissolution rate– Complex formulation
• E.g Lipidic in capsule– Stabilised amorphous form
• Change the chemistry of the lead series– Pro‐drug the lead candidate– Structurally modify a poorly soluble series
• Start in intrinsically more soluble chemical space !
LatePass the problem on!
Quite lateFurther LO resourceComplexity
Property comparison between leads derived from fragments vs. other approaches
Astex in‐house analysis comparing their fragment derived leads and hits with literature for same targets
C.Murray, M.Verdonk & D.ReesTIPS May 2012, Vol. 33, No. 5
P.Leeson, S.St‐Gallay,NRDD 2011, 10, 749–765
Properties taken from patent literature of 18 companies.Astex (fragments) vs. the other companies shows reduced logP and MW
Influence of discovery strategies on properties of drug candidates – not clear on solubility
• Analysis based on general literature, very diverse set • Fragments vs. HTS : Solubility higher for hits, but not leads
G.Keserü, Makara, NRDD 2009
Example with Haematopoietic Prostaglandin D2 Synthase (PGDS)
PGDS in the eicosanaoid pathway• PGDS inhibition could impact on a range of lipid mediators & receptors
potentially important in allergic and inflammatory diseases
Prostaglandin lipid pathways ‐ PGDS
Example PGDS inhibitors
• Typified by lipophilic Biaryl groups in the active site
HQL79 Pfizer Sanofi
US2008/0146569A1 WO2008/121670A1Matsushita, N. Jpn. J. Pharmacol. 1998,78,,1–10 & 11–22
N
F
O NH
N
F
FF
N
N N
O NHN
F
O
N
N NN
NH
N
F
O NH
N
NN N
N
1 232A
PGDS ‐Med Chem challenge and approach
• PGDS– binds lipid substrate– example inhibitors generally quite lipophilic
• Known inhibitors bind in lipophilic enzyme active site (Xray)
• Trial screening set on PGDS showed strong potency/logPcorrelation
• Hypothesis Structurally driven, fragment approach to increase chances for low
MWt leads with good solubility properties
• Early use of pharmacy to measure progress, decision making
The Astex Pyramid Approach
X‐Ray
INTEGRATED BIOPHYSICAL SCREENING
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
-6
-4
-2
0
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.10 20 40 60 80 100
Time (min)
µcal
/sec
Molar Ratio
kcal
/mol
e of
inje
ctan
t
305 310 315 320 325 330 335
1x105
2x105
3x105
4x105
5x105
Fluo
resc
ence
(a.u
.)
Temperature (K)
NMR
Tm
ITC
Astex PYRAMID™Screening
AstexProprietaryFragment Library
Targeted & Virtual ScreeningFragmentSets
STRUCTURE‐LED OPTIMISATION
Fragment‐to‐Candidate Chemistry
Astex Rule of 3™
FRAGMENT SELECTION
NH
N
ONH2
Cl
NN
NN
N
N NH2ClN NH2
N
NNH2
ClOH
NH
NH
NH2
O
OCl
NN
NH
S
Pharm Dev work to support selection of the Development Candidate
• Typically conducted on candidate/pre candidate– Full pH/solubility profile
– Full pH/solution state stability profile
– Solid state form• XRPD, DSC, TGA, GVS
– Solid state stability
– If required version and form assessment
– Formulation recommendations for formal toxicology studies and early clinical studies
Introduction of earlier Property Intervention for PGDS (after CLND)
• CLND solubility to triage compounds– High Throughput (1,000’s per week)– Screen out insoluble compounds to aid SAR– Precipitation from DMSO solution
• Early Pharm Dev intervention– Low throughput <10 per week– Solubility from solid in Physiologically relevant fluids
• Simulated Gastric Fluid (pH=1.6), Fed State Simulated Intestinal Fluid (pH=6.5), Fasted State Simulated Intestinal Fluid (pH=6.5), Water
– Solution state stability assessment• Chemical and Photostability
– Investigated Pharm Dev properties of early compounds• Identify solubility or stability challenge in series allowing chemistry effort to be
redirected to more promising areas• Inadequate PhysChem properties in the light of predicted dose could lead to
recommendation not to progress
PGDS Progression Profiles
ValidatedHits
DevelopmentCandidate
Confirmed Binding Mode (Xray)LE >0.3
Fragment OptH2L LEAD OPT
Small number seriesfor LO
‘N’ clusters
Novel seriesEnzyme/Cell 7‐8LE/LLE >0.3Stability/Solubility ProfileOral activity
Enzyme/Cell 6‐ 7LE/LLE 0.4
TractableppbCLND Sol(p450; X‐screen)
Multiple chemical series
Commit to LO
Fragment screen results
• Biophysical screening
• 76 validated hits– Confirmed by X‐ray
– Measurable activity in fluorescence polarisation binding assay
• IC50 >1000uM ‐ 0.5uM
• LE 0.26 – 0.52 kcal/mol/HAC
• LLEAT*0.23 – 0.50 kcal/mol/HAC
• => grouped into 10 clusters
* LLEAT, P.Mortenson, C.Murray, J. Comp‐Aided Mol Design, 2011, 25, 663
Cluster 1 – noteworthy example
• 4 is weak but efficient inhibitor• Small perturbation of protein• Induces disruption of intramol H‐bond of
Tyr152 phenol and Asp96 acid• Polar interactions in active site pocket• Fragment optimisation to 5, gave >10‐fold
potency increase
4IC50 =8.5uMLE 0.46; LLEAT 0.36
X‐ray Fragment Hit
5IC50 = 0.5uMLE 0.57; LLEAT 0.44
Fragment Optimisation
>10 fold
Cluster 2 – noteworthy example
• Fragment 6 also shows similar Asp96 & Try152 shift
• Polar interactions in active site pocket again
• Xray overlays show different binding of Biaryl in 6 compared with published Biaryl ligand 2
• CN overlays with carbonyl in 2
652% inhib @30uMLE ~0.44; LLEAT ~0.39
X‐ray Fragment Hit
Cluster 2 – fragment optimisation
• 7 has lower MWt, higher LE/LLE. Pyridyl‐N H‐bond to water• Filling pocket more optimally with c‐propyl• 8 occupies same binding as 6, but potency increased, high
efficiency
652% inhib @30uMLE ~0.44; LLEAT ~0.39
X‐ray Fragment Hit
758% inhib @100uMLE ~0.50; LLEAT ~0.50
Analogue Screening
8IC50 = 17uMLE 0.46; LLEAT 0.45
Fragment Optimisation
Cluster 2 – fragment growth and optimisation to orally active inhibitor
• X‐ray structural analysis suggested better growth vector opportunities with fragment 8. Target between 5‐ and 6‐pyridyl position
• 400 fold potency increase with 9. High LE/LLE maintained.• 9 too polar (clogP 0.7) !• LogP increased to attain good cell potency in 10
clogP 1.8; MW 337
8IC50 = 17uMLE 0.46; LLEAT 0.45
Fragment Optimisation
400 fold
10: AT24111/GSK296124A66% Inhibn. @10nMLE ~0.46; LLEAT ~0.45
Orally Active Lead
FBDD lead 10 has good solubility in a range of physiologically relevant media
pIC50 7.9 *8.3 7.7 8.8
LE ; LLE 0.43; 0.45 0.37; 0.38 0.44; 0.39
MW ; clogP 337; 1.8 381; 2.2 361; 3.3
Water (ug/ml) 52 (=150uM)
*1.2 17 4
SGF (ug/ml) 885 49 203
FeSSIF (ug/ml) 136 44 <1
FaSSIF (ug/ml) 109 31 5
SGF = Simulated gastric fluid (pH 1.6)FeSSIF = Fed simulated intestinal fluid (pH 6.5)FasSSIF = Fasted simulated intestinal fluid (pH 6.5) * C. Carron et al, ACS Med. Chem. Lett. 2010, 1, 59–63
10: AT24111/GSK296124A
DCS 2BN=8
DCS 3N=25‐27
DCS 4N=4
DCS 2AN=17‐34
DCS 1N=50‐65
Top 121 oral prescription medicines by DCS
Dose/Intestinal solubility (mL)
J.Butler J.Dressmann
Journal of Pharmaceutical Sciences, Vol. 99, 4940–4954 (2010)
FBDD lead 10 is orally bioavailable using a simple aqueous formulation, and inhibits PGDS in vivo
Inhibition of PGD2 in peritoneal cavity after oral dosing at 30mg/kg to mice
PK Parameter Compound 10
CLb (mL/min/kg) 33
T½ (h) 2.2
Vss (L/kg) 2.8
Tmax (p.o.) (h) 0.5
Cmax (p.o.) (ng/mL) 196
AUC0‐inf (ng.h/mL) 295
F (%) 19
fub 5.5%
Rat PK, from oral/IV dosing in aqueous formulation
Dosing: 1mg/kg IV; 3mg/kg poDrug conc in blood
All animal studies were ethically reviewed and carried out in accordance with Animals (Scientific Procedures) Act 1986 and the GSK Policy on the Care, Welfare and Treatment of Animals
FBDD approach identified several series with favourable properties
• With FBDD approach, strong focus on LE/LLE and upper limit of MWt• Potencies </= 10nM achieved with MWt 300‐400• Additional solubility dimension => highlights further series strengths
MW vs potency Solubility vs potency
Conclusions• Solubility is a key parameter in drug development
– Impact on bioavailability, dose, complexity of formulation, Drug Development cost, time, attrition (late failure!)
• Good solubility property has ‘suffered’ due to focus on high target affinity, compound library properties, and DD approach. Pipeline drugs carry risk.
• Fragment based drug discovery approach successfully generated multiple series with good properties in lipophilic target – PGDS
• Identification of novel protein movement/H‐bonding disruption, & novel fragment polar binding interactions in lipophilic active site
• X‐ray guided fragment optimisation, optimal vector growth, and early pharmacy input combined to give a PGDS inhibitor series with favourable properties (LE/LLE, MWt, logP, Solubility and DCS class )
Conclusions• Solubility is a key parameter in drug development
– Impact on bioavailability, dose, complexity of formulation, Drug Development cost, time, attrition (late failure!)
• Good solubility property has ‘suffered’ due to focus on high target affinity, compound library properties, and DD approach
• Fragment based drug discovery approach successfully generated multiple series with good properties in lipophilic target – PGDS
• Identification of novel protein movement/H‐bonding disruption, & novel fragment polar binding interactions in lipophilic active site
• X‐ray guided fragment optimisation, optimal vector growth, and early pharmacy input combined to give a PGDS inhibitor series with favourable properties (LE/LLE, sol, MWt, logP)
• Orally active from simple aqueous formulation – ‘proof of the pudding’