1. The Role of Drug Metabolism Studies in Optimizing Drug Candidates
Kenneth Santone, PhD
Bristol-Myers Squibb
Metabolism and Pharmacokinetics / Pharmaceutical Candidate Optimization

2. Why All the Chemist's Wonderful Compounds Don't Become Drugs!
ALTERNATE TITLE:
Why All the Chemist's Wonderful Compounds Don't Become Drugs!

3. Our Focus Unmet medical need First in class Best in class
Need for efficiency and productivity enhancement

4. What are we faced with? Industrialization of pharmaceutical research
Unprecedented increase in identification of targets
Corresponding increase in throughput of chemistry
Blurring of traditional discovery-development interface
Focus and emphasis on “developability” (early go/no go decisions)
Improve success rate
Reduce development timeline
Necessity for increasing efficiency and productivity

5. Drug Discovery Paradigm Shift
‘Old’ Model
of Drug Discovery
Validated Hits
Detailed Physicochemical,
ADME &
Tox Workup
Development
Compound
Efficacy &
Selectivity
Testing
Hits
Lead
Candidates
Physicochemical, ADME
&
Tox
Workup
Selectivity Testing
Design
& Synthesis
PAT
Screening &
Predictions
‘New’ Model
More informed decision making during Lead Optimization, through quicker and earlier evaluation of PAT attributes

6. *why great compounds don’t always become drugs
The Hand-off from Drug Discovery to Development: The Top Ten Quotations We All Know and Love*
10. 9. 8. 7. 6. 5. 4. 3. 2. 1.
“The molecular weight? Why? Is that a problem?”
“We’ll need eight different capsule strengths for Phase I.”
“The compound is very potent in the in vitro screen but does not work well in the animal efficacy model.”
“Now that you mention it, our solutions were a little cloudy.”
“The compound is highly insoluble but Pharmaceutical Development will fix the problem.”
“BMS-XXXXXX is a highly potent and selective inhibitor of (the target). In mouse models, the optimal dose was 200 mg/kg.”
“Toxicity?! It’s not the drug; must be a metabolite unique to that animal species.”
“Animal bioavailability ranged from 65% to <1%, depending on species.”
“Gee, we didn’t have any problems when we gave it in DMSO.”
“It’s a great compound, but it has formulation problems.”
Partially adapted from R.A. Lipper
*why great compounds don’t always become drugs

7. Critical Interfaces in Drug Discovery*
Chemistry
Biology
Activity
Safety
Metabolism & Pharmacokinetics
Pharmaceutics
Optimized Compound
*Analytical Chemistry (Bioanalysis) involved in every one of these disciplines

8. * Absorption, Distribution, Metabolism, Excretion
Role of ADME* Studies
Selection of quality drug candidate for development
Developability
First-in-class vs. best-in-class
Crisp go/no go decisions
Optimization of drug discovery and early development processes
Multi-tiered approach for ADME studies
Equal partnership with all functional areas
Lead Discovery Biology Chemistry Pharmaceutics Drug Safety Analytical R&D Clinical Pharmacology Process Chemistry
Blurring of traditional discovery-development interface
* Absorption, Distribution, Metabolism, Excretion

9. Selection of Drug Candidates: Focus on Developability
Permeability
Transport
Metabolic stability
P-450 mediated drug interactions
PK/PD assessment
Distribution
Protein binding
Biopharmaceutics
Active/reactive/ toxic metabolites
In vivo PK/bioavailability in animals
Prediction of PK and efficacious doses in humans

10. Tiered-Approach for ADME Studies
Hits to Lead
In vitro Studies
Permeability
P450 inhibition
Metabolic Stability
In silico predictions
Objective
Develop SAR
Chemotype selection

11. Tiered-Approach for ADME Studies
Lead Optimization
In vitro Studies
Permeability/transport
P450 inhibition
Metabolic Stability
Reaction phenotyping
Protein binding
In vivo PK
Cassette dosing
Individual PK
Tissue penetration
Early biotransformation
Objective
Identify a lead compound
Feedback to chemistry/biology

12. Tiered-Approach for ADME Studies
Lead Selection
Absolute bioavailability in pharmacology/toxicology models
Dose dependency in PK
Mechanism of absorption
Assess potential for DDI
Characterization of metabolites, routes of elimination
Assess formation of active metabolites
Interspecies differences in metabolism and in vitro-in vivo correlation
Extrapolation of ADME properties to man from in vitro and in vivo data
Determination of PK/PD relationships; help selection of doses for First in Human studies
Objective
Characterize the lead compound
Identify risks/opportunities

13. How In Vitro Metabolic Stability Relates to Clearance?
TBC = CLhepatic + CLrenal + CLother
CLhepatic = CLmetabolism + CLbiliary
CLmetabolic = fB * CLintrinsic * Qh / fB * CLintrinsic + Qh
well stirred model of organ extraction
Intrinsic Clearance (CLi) = Vmax / Km = vo / Cu
through rearrangement of the Michaelis-Menton eqn, assuming drug conc is < Km
Depletion or Half-Life Method:
CLi = (0.693 * liver wt) / (in vitro t1/2 * amount of liver) 3

14. Tools to Predict Metabolic Clearance
In Vitro Systems
Liver microsomes
high throughput and most common
mostly oxidative (CYP & FMO)
S9 fraction
high throughput
Phase I & Phase II metabolism
Hepatocytes
low throughput
cell membrane/transporters
intracellular concentration
In Vivo Animal Clearance
In Silico
In Vitro - In Vivo Correlation 3

15. Metabolic Stability to Select Compounds with
Potentially Longer Half-Life
Human Metabolic Stability: Microsome vs Hepatocyte
0.4 R 2
= 0.8
0.3
Microsome Total Metabolic Rate
0.2
BMS:Y
0.1
0.0 -1 1 2 3 4 5
Hepatocyte Metabolic Rate
Lead compound is primarily glucuronidated in humans
Human in vitro systems with combination of oxidation and
glucuronidation employed for selection of back up

16. Major Reactions Involved in Drug Metabolism
OXIDATIVE REACTIONS (CYP, LM+NADPH)
N-Dealkylation: erythromycin, morphine, caffeine
O-Dealkylation: codeine, dextromethorphan
Aliphatic Hydroxylation: tolbutamide, midazolam
Aromatic Hydroxylation: phenytoin, amphetamine, warfarin
N-Oxidation: chlorpheniramine, dapsone
S-Oxidation: cimetidine, omeprazole
Deamination: amphetamine

17. Major Reactions Involved in Drug Metabolism
HYDROLYSIS REACTIONS (Esterase, ?LM+NADPH)
Ester Hydrolysis: aspirin, cocaine
Amide Hydrolysis: lidocaine, procainamide
CONJUGATION REACTIONS (Phase II, hepatocytes)
Glucuronidation: morphine, ibuprofen
Sulfation: acetaminophen
Acetylation: sulfonamides, isoniazid

18. Metabolic Stability Summary
Not all metabolism is hepatic.
Incubation concentration < Km balanced with assay sensitivity.
Need to correlate with in vivo model.
Fast in vitro clearance generally implies fast in vivo clearance, the reverse need not be true.
Confounding physical-chemical properties.
solubility, stability, purity, non-specific binding
Real concentration at enzyme active site?
protein binding, cell penetration, non-specific binding
In vitro systems generally underestimate CLi due to non-specific binding.
Can the stability be too good? Yes, in certain situations.
Many unknown factors to can contribute to a poor in vitro - in vivo correlation or poor estimation of human metabolic stability.
Nonetheless, in vitro methods are still the best method for predictions 15

19. Drug-Drug Interaction Summary
Major drug interactions are caused by either inhibition or induction of drug metabolizing enzymes.
Semi-quantitative predictions of drug interactions
many unknown factors
human ADME properties in vivo
Models provide numbers that must be placed in context with multiple factors:
therapeutic area
therapeutic index, route of administration
market competition
Animal models are not predictive of human interaction potential ???
Static nature of in vitro systems compared to the dynamic in vivo system
Mixtures of interaction mechanisms from the same compound are extremely difficult to predict:
reversible + irreversible inhibition
inhibition + induction

20. Assessment of Active Metabolites
Issue
Similar metabolism and in vitro activity profile but different in vivo
activity profile
Apparent PK/PD disconnect
Solution
Rapid in vitro metabolism and biological activity assays

21. Assessment of Active Metabolites
Structural identification of active metabolites
MS/MS indicated presence of monohydroxylation
NMR showed site of hydroxylation
Subsequent steps
Monohydroxylated metabolite synthesized
Activity and PK properties confirmed

22. Assessment of Reactive Metabolites
A number of functional (chemical) elements have been associated with problems in drug discovery leading to toxicity
Metabolic activation to reactive intermediates
Interference with metabolic processes
Clinical manifestations include (preclinical measure)
Cellular (hepatic) necrosis (animal toxicity)
Idiosyncratic toxicity (glutathione adducts, protein covalent binding, immunogenic response)
Drug-drug interactions (mechanism-dependent CYP inhibition)

23. Examples of Reactive Metabolites
Furans
Furan substructure is associated with toxicity (eg. aflatoxin) and with CYP inhibition (eg. bergamottin)

24. Examples of Reactive Metabolites
Thiophenes
Thiophene substructure has been associated with several types of toxicity (predominately hepatotoxicity). Other thiophene containing drugs: ticlopidine, clopidigrel, raloxifene.

25. Examples of Reactive Metabolites
Anilines, Nitroaromatics
Anilines are associated with a number of types of toxicity (eg. methemoglobinemia, skin rashes, etc.). Nitroaromatics are primarily activated by initial reduction, often in the gut, followed by N-oxidation.
Anilines of polycyclic aromatic systems are often potent mutagens and carcinogens (eg., naphthylamine, aminofluorene) through conjugation of the hydroxylamine and subsequent loss of the conjugate to leave a nitrenium ion.

26. Examples of Reactive Metabolites
Amines, alkylamines
The metabolism of amines or alkylamines is generally related to time- dependent inhibition of CYP enzymes, with the nitroso species forming a tight complex with the heme iron, known as a MI complex. Other compounds that undergo this type of transformation and inhibit CYPs are TAO, erythromycin and verapamil

27. Examples of Reactive Metabolites
Quinone, Quinoid
Quinone-like compounds can exert their effects through direct alkylation of nucleophiles or through redox cycling between their oxidized and reduced forms

28. Examples of Reactive Metabolites
Acetylenes
Acetylenes have been found to be time-dependent inhibitors of CYP enzymes.

29. Examples of Reactive Metabolites
Acyl glucuronidation formation
Acyl glucuronides have been implicated in both direct hepatic damage and idiosyncratic toxicities

30. Challenges and Opportunities
HTS screens for prediction of permeability, metabolic stability, metabolic reactivity and DDI
How are we using these data?
Retrospective analysis on return of investment
The numbers in gray zone!
Secondary assays for better predictability
Application of animal PK/bioavailability data for lead optimization
Adequacy of permeability and metabolic stability data
Animals vs. humans: quantitative and qualitative differences in ADME properties
Informed decision based on drug metabolism and pharmacokinetic data
Low bioavailability vs. oral efficacy
Role of metabolite(s), reactivity of metabolite(s)
Protein binding
In vitro- in vivo correlation in animals and extrapolation to humans
Issue of enzyme induction in humans
In-vitro models and predictability
False and real alarm from in-vivo animal data
HTS screens for prediction of permeability, metabolic stability and DDI
How are we using these data?
Any retrospective analysis on return of investment?
The numbers in gray zone!
Cost / benefit ratio?
Application of animal PK/bioavailability data for lead optimization
Adequacy of permeability and metabolic stability data
Animals vs. humans: quantitative and qualitative differences in metabolic clearance
Informed decision based on drug metabolism and pharmacokinetic data
Low bioavailability vs. oral efficacy
Short half-life vs long PD effects
Role of metabolite(s)
Long half-life vs short PD effects
Protein binding
In-vitro P-450 inhibition values and predictions for the potential of DDI in humans
What is our success rate?
Are these data used intelligently
Time-dependent and mechanism based inhibition – the relevance issue
Predator vs. prey issue
The IC50 values in gray zone
Lack of animal models

31. Challenges and Opportunities
Use of biomarkers
In-vivo biology, animals vs. humans
Development and validation of assays
Transfer from preclinical to clinical laboratories
Biomarkers = Surrogate marker = Efficacy/Toxicity
A balancing act of emerging science
The feedback loops
To and from chemistry
To and from biology
To and from drug safety
To and from pharmaceutics
To and from clinical pharmacology
Volume of data
Conversion of information into knowledge
Timing and availability

32. A Focused Application of ADME Studies
Active involvement earlier in the Discovery Process
Timely guidance to Chemistry to select chemotypes with desirable ADME properties
Maximize informed decision making during Lead Optimization
Improved ability to predict human metabolism and pharmacokinetics
Stronger partnerships with Drug Discovery and all areas of Pharmaceutical Development

33. Our Mission
To ensure that no development candidate fails in the clinic due to an
unforeseen metabolic or
pharmacokinetic property

34. Saeho Chong, Punit Marathe, Wen Chyi Shyu and Mike Sinz
Acknowledgements
David Rodrigues and Griff Humphreys
Saeho Chong, Punit Marathe, Wen Chyi Shyu and Mike Sinz
And finally ….