: FROM Alabama Alliance Lecture Series 2015

Corinne E. Augelli-Szafran, Ph.D. Director, Chemistry Department Southern Research April 14, 2015

1 Drug Discovery Pipeline

Bench………….to………….Bedside Southern Research

Some facts:

• 10% of the compounds make it to • 70% of these compounds make it to Phase 1 • 20% of Phase 1 compounds make it to market • Odds are < 10% of making it to market • 30% of new drugs return cost of development • 6 yrs from idea to First In Human (FIH) • 8 yrs from FIH to market approval •Total of ~ 12-15 yrs to get to market •$802 MM cost of drug to market

-AlzForum.org ~2007 2 Clinical Candidate Success Rate

In General:

•10% of the compounds make it to preclinical development

•70% of the compounds make it to Phase 1

•20% of Phase 1 compounds make it to market

Safety Major Causes of Attrition Safety: Preclinical & PI Market Potential Displacement Pharmacology: P2 Chemistry Biopharmaceutics

T. Wood, " Challenges“, QSAR & Chemoinformatics Conference, 2009 3 FDA Drug Approvals 1996-2007

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0 Infectious Disease Cardiovascular Cancer Neurodegeneration Disease ‘96 - ‘99 ‘00 - ‘03 ‘04 - ‘07

Source: Thompson Centerwatch 4

4/23/2015 © 2010 Harvard NeuroDiscovery Center / Collaborating to cure neurodegenerative disease A Few StepsChallenges to Clinical Trials

Clinical Trial

In vivo efficacy In vivo toxicity (MTD) Formulation CNS penetration Pharmacokinetic profiling Solubility Hepatocyte stability in mice and human Metabolic stability in mice and human Selectivity Potency Intellectual Property Lead identification 5 Guidelines to Drug-Like Properties

STEP 2 / Optimization STEP 1 / Early Stage CNS DRUGS  % Bioavailability ( 30 )  Rule of 5 Brain Penetration  t ½ (> 2h, i.e., BID)  Structural ‘alerts’  Clearance  Ease of synthesis  Smaller is Better (MW = 300)  Nontarget selectivity profile  Solubility (>10 g/mL) µ  Log D (2-4)  Plasma protein binding  Log D (2-4)  Polar Surface Area < 70  hERG testing  MHep (>20% remaining)  < 5 Total H-Donors or Acceptors  P450 interactions (>3 µM )  HHep ((>20% remaining)  < 4 Total Rings, Rotatable Bonds  Pgp  IC (< 1 M ) 50 µ  < 3 Three Aromatic Rings  Mini-Ames  Minimum effective dose  Brain / Plasma (0.5 – 1)

POC

STEP 3 / Pre-Clinical Development  Genetic toxicology  In vivo studies / dose response  Side-effect profiling  Biomarker  Defined mechanism of action  Differentiation vs. known (AD) drugs

6 Physicochemical Properties MW = Molecular Weight •Mass of one molecule of that substance

PSA = Polar Surface Area •Surface sum over all polar atoms (oxygen and nitrogen), including also attached hydrogens; Used for optimization of cell permeability

Solubility •In PBS (Phosphate buffered saline) at pH 7.4 (µM)

Log D •Distribution (D) coefficient - ratio of the sum of the concentrations of ionized + un-ionized form of the compound in water and a hydrophobic solvent; measures differential solubility of the compound between these two solvents. •Partition (P) coefficient (Log P) - ratio of concentrations of un-ionized compound between the two solvents

Lipinski’s Rule of 5 . Molecular weight < 500 . cLog P < 5 (lipophilicity) . < 5 hydrogen bond donors 7 . < 10 hydrogen bond acceptors Pharmacokinetic Properties

MLM/HLM = Mouse/Human Liver Microsomes  % Compound Remaining @ 60 min (1h)

Liver microsomes •contain drug-metabolizing enzymes, e.g., CYP isoenzymes such as CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 3A4 •widely used as an in vitro model system to investigate metabolic fate of the compound

HEP= Hepatocytes (mouse or human)  Compound Remaining @ 120 min (2h)

Hepatocytes •liver cells •contain phase II enzymes, e.g. sulfatases, glutathione S- transferases, and UDP-glucuronosyltransferase •metabolite profiles obtained with hepatocytes usually yield more metabolites and more information about the metabolic fate of the test compound 8 ‘DRUGGABILITY’ ‘Ideal’ Properties of a CNS Drug

. Smaller is Better . 300 MW is the ideal

. Polar Surface Area of 45 . Average value for successful CNS drugs

. < 5 Total H-Donors or Acceptors

. < 4 Total Rings and Rotatable Bonds

. < 3 Three Aromatic Rings

9 ‘Structural Alerts’ – The Philosophy

•Structural alerts are associated with multiple examples of adverse in vivo outcomes.

•The chemistry, pharmacology and toxicology provides a strong rationale for a grouping to be "a structural alert" due to the potential for intrinsic reactivity, DNA intercalation, metal coordination (e.g., the heme in a CYP enzyme) or metabolic activation to a species capable of covalently binding to biological macromolecules.

•This binding could then lead to mutagenicity, CYP inhibition, direct toxicity, carcinogencity or idiosyncratic toxicity.

•The problem may occur anywhere between pre-clinical and the market.

•Some molecules incorporating a structural alert may never generate an adverse toxicological or CYP inhibition outcome. There are examples that include safe marketed drugs containing a structural alert

•Attrition of a compound due to an adverse outcome without a recognized structural alert in the molecule.

•A structural alert is not, on its own, predictive of an adverse outcome. Many other factors such as the clinical dose, route of drug clearance or the presence of metabolic routes that divert metabolism away from the structural alert need to be considered. 10 Hit to Lead Identification

Project:

“DISCOVERY AND DEVELOPMENT OF INHIBITORS OF GAMMA-SECRETASE FOR THE TREATMENT OF ALZHEIMER’S DISEASE”

Research done at:

Laboratory for Experimental Alzheimer Drugs (LEAD) Harvard Medical School Center for Neurologic Diseases, Brigham & Women’s Hospital

11 The Amyloid Hypothesis of AD Pathogenesis

APP Oligomerization or β β Amyloid- fibril production formation γ Aβ40 and Aβ42

Aβ Aβ42

Aberrations Neuronal Clinical AD in tau cell death

1. Selkoe, Dennis J. The Molecular Pathology of Alzheimer's Disease. Neuron (1991); 2. Selkoe, Dennis J. Amyloid β-Protein Precursor:New Clues to the Genesis of Alzheimer's Disease. Current Opinion in Neurobiology (1994); 3. Selkoe, Dennis J. Toward a Comprehensive Theory for Alzheimer's Disease. Hypothesis: Alzheimer's Disease is Caused by the Cerebral Accumulation and Cytotoxicity of Amyloid β-Protein. Annals of the New York Academy of Sciences (2000); 4. Selkoe, Dennis J. Alzheimer’s Disease Results from the CerebralAccumulation and Senile Plaque Cytotoxicity of Amyloid β − Protein. Journal of Alzheimer’s Disease ( 2001) . (Silverstain)

12 γ-Secretase and Aβ Production

APP Notch

Aβ β-secretase α-secretase cleavage cleavage

Extracellular α Disturb-S Notch signaling

Plasma β-S Membrane γ-Secretase Unwanted Side Effects •Intestinal cell differentiation Cytoplasmic •Gastrointestinal dysfunction

AICD NICD

Presenilin Nicastrin APH-1 PEN-2

13 γ-Secretase: Activity Profiles of Compounds

Aβ40 Aβ42 Notch

GSI Side Effects

GSM Preferred for NS GSI

? Required therapeutic window ? GSI: Gamma-secretase Inhibitor 14 GSM: Gamma-secretase modulator NS GSM: Notch-sparing gamma-secretase modulator Discovery of BMS708163

O O O O O O O S S Resolution N S N OH Br N (R) Br O (S) O Cl O F O NH NH F F Aβ40 IC50 = 3400 nM Racemate 1st Generation Aβ IC = 120 nM O O 40 50 S N Br 2nd Generation O (R) O NH

Aβ40 IC50 = 13 nM

open the ring

O O F Potency O O Stability O O S S S N Selectivity N N Cl Cl (R) O N O N O O O O NH NH2 N NH 2 N CF 2 NH2 CF3 3

Aβ IC = 4.1 nM Aβ40 IC50= 0.3 nM Aβ40 IC50 = 113 nM 40 50 Notch IC = 960 nM (230X) Notch IC50= 58 nM (190x) Notch IC50 = 560 nM (5X) 50 B/P =0.01 (low BBB penetration) RLM (19%), HLM (44%) @10 min incub 15 Drug Discovery of GSI-953

Potency O O O O S OH S OH N N Hit Lead H H Cl Cl

Aβ40 IC50= 294 nM Aβ40 IC50= 5549 nM Selectivity: 3.7 folds Selectivity: 10 folds

Potency Oxidation

CF3 CF3 F3C CF3 Stability Stability O O O O S S OH O O S S OH Cl N S S OH Cl N H Cl N H H Glucuronidation Aβ IC = 15 nM β 40 50 A 40 IC50= 16 nM Aβ40 IC50= 25 nM Selectivity: 14 folds Selectivity: 15 folds Selectivity: 10 folds

48 min (mice) 24 min (mice) 1 min (mice) >90 min (human) 8 min (human) 8 min (human)

16 Clinical Candidates Issues

• Notch selectivity • Brain penetration Potency/Efficacy Flurizan LY450139 • [Tarenfluribil] Toxicity BMS 708163 • • Cognitive decline • Half-life • Solubility • Molecular weight

Conclusions, Questions • Improper balance of the compound properties • Was dose selection accurate? • Did the preclinical PK/PD and animal data support and precisely define the clinical study and its design

17 γ-Secretase Chemical Matter

Me AD141 N Me H N N Cl Pyridopyrimidines N J. Zhang, et al., 235th ACS Mtg N MeS N MEDI 265 (April 2008) HN Cl N N N O H N O Me Gleevec Inhibitor 2

WJ Netzer, P Greengard, et. al. PNAS, 100 (2003) 12444 Rational Tocris Design AD33 Library (50 cpds) Aryl Amides Structure D. Lu, et al., 235th ACS Mtg Modification MEDI 263(April 2008)

O Me O N Me - N(CH2Ph)(C(Me)2

(Reactive) (Unstable) AD29 1366 1367 µ γ-Amino Alcohols IC50 = 60 M µ IC50 = 20 M H-X Wei, et al., 235th ACS Mtg MEDI 264 (April 2008) PC Fraering, et. al. JBC, 280 (2005) 41987 18 After >600 Analogs, End Results for….. γ-Amino Alcohols • Notch selectivity prominent • Low to moderate in vitro potency

Aryl Amides • Low in vitro potency • Some selectivity

Pyridopyrimidines •< 5 µM in vitro potency •Notch selective at 30 µM •But unstable and cytotoxic SAR Studies led to: •Biochemical assays fine-tuned and reliable •Drug discovery infrastructure established •In vitro screening concentration decreased Sulfonamide Chemical Matter Conversion of: Aryl Amides (AD33) to Aryl Sulfonamides O O O

N S R2 Aryl N

R1

1. Common replacement for amide 2. Sulfonamide conformation perhaps could offer more binding orientations ? 3. Converted naphthyl to aryl and alkylbenzyl amine to more diversified amines

Sulfonamide Results

Aβ40 Potency (in vitro) 16 µM to 230 nM ( ↑ 70-fold)

Aβ40 Potency (cells) 337 nM to 15 nM ( ↑ 20-fold)

Aβ42 Potency (cells) 278 nM to 18 nM ( ↑ 15-fold)

Notch Selectivity (in vitro) 17 µM to >100 µM ( ↑ 70-fold Aβ40)

Notch Selectivity (cells) 34 µM ( ↑ 400-fold Aβ42 and Aβ40) Lead Quality Attributes for Chemical Series

Sulfonamide Attributes Met 1 Potency: In vitro potency < 100 nM yes 2 SAR: Evidence of SAR with > 10X change in potency yes 3 Cellular activity / toxicity: Active / no toxicity yes 4 Selectivity: Versus Notch receptor yes 5 Safety: No toxicophores or reactive moieties yes Physicochemistry: In vitro ADME studies of similar 6 yes framework show solubility and absorption Synthesis: Synthetic chemistry flexibility is high; 7 yes amenable to rapid, highly productive analog synthesis 8 Intellectual property: Proprietary yes 9 Synthesis: Amenable to parallel synthesis yes

assessed ok assessed bad not assessed

21 Compound Profiles Selected for Mouse Testing

I. Iterative Medicinal Chemistry led to γ-Secretase Inhibitors that:

Block Aβ Production

Notch Selective

 Improved Drug-Like Properties than failed clinical candidates

II. Drug-Like Properties that differentiate LEAD compounds from Avagacestat are:

 Brain Penetration  Size  Log D  Solubility  Metabolic Stability

22 Results of 1st Study in Wild Type Mice

EXPERIMENTAL CONDITIONS • 3 month old Males, N=5 • P.O., 0.5% methylcellulose as vehicle • 100 mg/kg, t.i.d at 0, 6 h 12 h • Levels of Aβ in hippocampus were determined 4 h after last dose (at 16 h).

RESULTS • AD1231 and AD1130 significantly reduced Aβ in the hippocampus by blocking γ-secretase (44% and 41%, respectively).

• AD940 also significantly reduced Aβ (24%) in the brain but not as much as AD1231 and 1130.

• Avagacestat and AD1112 reduced Aβ but did not reach statistical significance (16% and 12%, respectively). Control

Avagacestat AD1130** 16% AD940* AD1231 ** 41% 24% 44% AD1112 12%

23 AD1231 versus AD1112 DATA 1231 1112

Aβ42 Elisacells IC50 nM 68 (4) 8 (3)

Notch Luccells IC50nM 28,600 (1) 4588 (3)

Not Luc /A 42 cells β 421 574 Elisacells

Notch Elisacells IC50nM 6995 (2) 350 (1) Not Elisa /Aβ42 cells 103 44 Elisacells Molecular Weight 426 422

Polar Surface Area 75 75

Solubility (µM) 303 305

Log D 1.6 2

Microsome Stability: 71 18 Mouse

Intrinsic Clearance 11 57

Microsome Stability: 47 4 Human Intrinsic Clearance 25 114

Hepatocyte Stability: 57 8 Mouse Intrinsic Clearance 10 34

Hepatocyte Stability: 52 26 Human

Intrinsic Clearance1 12 22 24 Sulfonamide SAR Overview

(+) Mono-aromatic ring (+) Heteroaryl (-) Bicyclic rings Subst. phenyl O O (-) Alkyl r S A N

R1 R2

(+) Aromatic and non-aromatic (+) para-Subst. aromatic Alkyl-aryl substitution Amide alkyl chains (-) Bicyclic rings (-) Di-subst. ring ortho-Substitution para-CF3

25 The Right Balance……

•Solubility •Molecular weight •Metabolic stability

•Potency •Brain penetration •Notch selectivity •Bioavailability •Toxicity •Half-life

‘BALANCED’ •Test in Animals OPTIMIZED γ–SECRETASE •Endpoint: POC MODULATORS Reduction of Aβ: Plasma, Brain, CSF A Few StepsChallenges to

Clinical Trial

In vivo efficacy ….Selection of Compounds for In Vivo Animal Testing…. In vivo toxicity (MTD) Formulation CNS penetration Pharmacokinetic profiling Solubility Hepatocyte stability in mice and human Metabolic stability in mice and human Selectivity Potency …..Intellectual Property Lead identification 27 Bridge the Gap Between..

ALZHEIMER’S DRUG ( ) DISEASE RESEARCH DISCOVERY

28 http://maps.google.com/maps; By allen kramer Southern Research (SR) Chemistry Department Capabilities for Medicinal Chemistry and Drug Discovery

Compounds that meet Activity/Efficacy Criteria Iterative Medicinal Chemistry Informatics •Electronic Notebooks Dotmatics Computational • Chemistry US Patent Intellectual x,xxx,xxx Property

Monastrol S1

ADP Lead Development

S2 & Optimization

Structural Biology Proof of Concept Parallel Protein Crystallography Animal Model Synthesis

“Making Drugs that Matter!” In Vitro Pharmacokinetics

Mass Directed Purification •In Vivo Pharmacokinetics •Toxicity Studies Nuclear Magnetic Resonance •Animal Efficacy Studies Exact Mass 29 Southern Research Medicinal Chemistry Research Projects

Disease Grant Type Project Status Antivirals U19 Flu, Flavi-, Corona- , and Alpha-viruses HTS NIAID Integrase-LEDGF Lead Opt NIAID NEF-Hck Hit ID Vaccine Adjuvants R21 Viral Lead Opt Parkinson’s ADDA LRRK2 Inhibitors Lead Opt ADDA 14-3-3-θ Lead Opt Alzheimer’s Bright Focus Fdn Tau Fyn Hit ID ALS MDF NFκ-B Lead Opt Diabetes ADDA TXNIP Lead Opt Cancer ADDA HO-1 Hit ID UAB Wnt Inhibitors Lead ID ADDA CD38 Lead Opt AIF Triplex Metastatic Protease Inhibitors Lead Opt RO1 TGF-β Adv. Lead Psychiatric Disorders R21 Dopamine Ligands Lead Opt Ischemia Reperfusion VA Hospital Chymase Hit ID

30 THANK YOU…

Corinne E. Augelli-Szafran, Ph.D. Director, Chemistry Department Drug Discovery Division Southern Research 2000 Ninth Avenue South Birmingham, AL 35205 205-581-2305 telephone [email protected]

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